diff --git a/.gitattributes b/.gitattributes index db224106266a1d1ecc852aced2d11c69b9946f91..75417c83af3d005b553ffae17b28ea447fcf5830 100644 --- a/.gitattributes +++ b/.gitattributes @@ -673,3 +673,4 @@ llava_video/lib/python3.10/site-packages/matplotlib/_tri.cpython-310-x86_64-linu llava_video/lib/python3.10/site-packages/matplotlib/backends/_tkagg.cpython-310-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text llava_video/lib/python3.10/site-packages/matplotlib/__pycache__/widgets.cpython-310.pyc filter=lfs diff=lfs merge=lfs -text llava_video/lib/python3.10/site-packages/matplotlib/__pycache__/colors.cpython-310.pyc filter=lfs diff=lfs merge=lfs -text +moondream/bin/python filter=lfs diff=lfs merge=lfs -text diff --git a/llava_video/share/terminfo/h/h-100 b/llava_video/share/terminfo/h/h-100 new file mode 100644 index 0000000000000000000000000000000000000000..0d0311b25678040919f80d020b9ae83843923ae3 Binary files /dev/null and b/llava_video/share/terminfo/h/h-100 differ diff --git a/llava_video/share/terminfo/h/h19-u b/llava_video/share/terminfo/h/h19-u new file mode 100644 index 0000000000000000000000000000000000000000..f01531faa42be8eddfa98cbca69b8986638870d1 Binary files /dev/null and b/llava_video/share/terminfo/h/h19-u differ diff --git a/llava_video/share/terminfo/h/hp2397 b/llava_video/share/terminfo/h/hp2397 new file mode 100644 index 0000000000000000000000000000000000000000..70ea75de59c7d50e6776d9b677fef950a18046ea Binary files /dev/null and b/llava_video/share/terminfo/h/hp2397 differ diff --git a/llava_video/share/terminfo/h/hp2621-nt b/llava_video/share/terminfo/h/hp2621-nt new file mode 100644 index 0000000000000000000000000000000000000000..6c88515da87b658ac80f584205f8cc3bb158bba1 Binary files /dev/null and b/llava_video/share/terminfo/h/hp2621-nt differ diff --git a/llava_video/share/terminfo/h/hp2626-ns b/llava_video/share/terminfo/h/hp2626-ns new file mode 100644 index 0000000000000000000000000000000000000000..d800ad327785db9a563974743da9bef94a0ab8e2 Binary files /dev/null and b/llava_video/share/terminfo/h/hp2626-ns differ diff --git a/llava_video/share/terminfo/h/hp98550a b/llava_video/share/terminfo/h/hp98550a new file mode 100644 index 0000000000000000000000000000000000000000..cd7c8a78892833ad7e1773e48668a17c9b1b14ae Binary files /dev/null and b/llava_video/share/terminfo/h/hp98550a differ diff --git a/moondream/bin/python b/moondream/bin/python new file mode 100644 index 0000000000000000000000000000000000000000..5e594a458f726d9ccfa7c1e312359663a25c79bd --- /dev/null +++ b/moondream/bin/python @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2ea10434255071448f619cdd851259db7aaa28afe26632d6eeed7a71fb15e543 +size 17225608 diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d753d445a7deee81f81f05d10f75082274690cc4 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cdist_forward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cdist_forward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cdist_forward(Tensor x1, Tensor x2, float p, int? compute_mode) -> Tensor") + static at::Tensor call(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); +}; + +struct TORCH_API _cdist_forward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, double, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cdist_forward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cdist_forward.out(Tensor x1, Tensor x2, float p, int? compute_mode, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cholesky_solve_helper.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cholesky_solve_helper.h new file mode 100644 index 0000000000000000000000000000000000000000..014971c6f8e9d8ad3b80c6317d5830864d6b8d86 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cholesky_solve_helper.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cholesky_solve_helper(Tensor self, Tensor A, bool upper) -> Tensor +inline at::Tensor _cholesky_solve_helper(const at::Tensor & self, const at::Tensor & A, bool upper) { + return at::_ops::_cholesky_solve_helper::call(self, A, upper); +} + +// aten::_cholesky_solve_helper.out(Tensor self, Tensor A, bool upper, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cholesky_solve_helper_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & A, bool upper) { + return at::_ops::_cholesky_solve_helper_out::call(self, A, upper, out); +} +// aten::_cholesky_solve_helper.out(Tensor self, Tensor A, bool upper, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cholesky_solve_helper_outf(const at::Tensor & self, const at::Tensor & A, bool upper, at::Tensor & out) { + return at::_ops::_cholesky_solve_helper_out::call(self, A, upper, out); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesce_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesce_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f23343092e8e64779628025405e2b40b33b41f86 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesce_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _coalesce_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _coalesce_sparse_cpu(const at::Tensor & self); +TORCH_API at::Tensor _coalesce_sparse_cuda(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_cuda_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..34aaef78de5cc840febc32f2f2d4d4049a3bceaa --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_ctc_loss_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity); +TORCH_API ::std::tuple _cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool deterministic, bool zero_infinity); + +} // namespace cuda +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c2d6e7dc74c4676cc843b5e85ab2c53c415455cb --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _cudnn_init_dropout_state_out(double dropout, bool train, int64_t dropout_seed, at::Tensor & out); +TORCH_API at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..892922f68b6d23cbe4ad41ad69e2741a81cffe95 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cudnn_rnn { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const ::std::optional &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, double, bool, bool, c10::SymIntArrayRef, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cudnn_rnn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state); +}; + +struct TORCH_API _cudnn_rnn_out { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const ::std::optional &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, double, bool, bool, c10::SymIntArrayRef, const ::std::optional &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cudnn_rnn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!))") + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const ::std::optional & weight_buf, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh.h new file mode 100644 index 0000000000000000000000000000000000000000..65c3ad82c12d498262755a9767b632f5711059c1 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_cosh.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_cosh(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_cosh(at::TensorList self) { + return at::_ops::_foreach_cosh::call(self); +} + +// aten::_foreach_cosh_(Tensor(a!)[] self) -> () +inline void _foreach_cosh_(at::TensorList self) { + return at::_ops::_foreach_cosh_::call(self); +} + +// aten::_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_cosh_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_cosh_out::call(self, out); +} +// aten::_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_cosh_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_cosh_out::call(self, out); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p.h new file mode 100644 index 0000000000000000000000000000000000000000..dc912733db67903fdf1924af79bfbdc70afe4667 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_log1p(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_log1p(at::TensorList self) { + return at::_ops::_foreach_log1p::call(self); +} + +// aten::_foreach_log1p_(Tensor(a!)[] self) -> () +inline void _foreach_log1p_(at::TensorList self) { + return at::_ops::_foreach_log1p_::call(self); +} + +// aten::_foreach_log1p.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log1p_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_log1p_out::call(self, out); +} +// aten::_foreach_log1p.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log1p_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_log1p_out::call(self, out); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum.h new file mode 100644 index 0000000000000000000000000000000000000000..8921fd5c2e393df3a23e96fd1462e44994f75bac --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_maximum.h @@ -0,0 +1,82 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_maximum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_maximum(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_maximum_Scalar::call(self, scalar); +} + +// aten::_foreach_maximum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_maximum_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_maximum__Scalar::call(self, scalar); +} + +// aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_maximum(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_maximum_List::call(self, other); +} + +// aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_maximum_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_maximum__List::call(self, other); +} + +// aten::_foreach_maximum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_maximum(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_maximum_ScalarList::call(self, scalars); +} + +// aten::_foreach_maximum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_maximum_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_maximum__ScalarList::call(self, scalars); +} + +// aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_maximum_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_maximum_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_maximum_List_out::call(self, other, out); +} +// aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_maximum_List_out::call(self, other, out); +} + +// aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_maximum_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_maximum_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_maximum_ScalarList_out::call(self, scalars, out); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..946bec271173fa5f4d2f0150300ac2ea24823d90 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_reciprocal_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_reciprocal { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_reciprocal") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_reciprocal(Tensor[] self) -> Tensor[]") + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_reciprocal_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_reciprocal_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_reciprocal_(Tensor(a!)[] self) -> ()") + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_reciprocal_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_reciprocal") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_make_dual_copy.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_make_dual_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..79fbe9b5ab8497f22711e4226654563bc3560fdc --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_make_dual_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_make_dual_copy(Tensor primal, Tensor tangent, int level) -> Tensor +inline at::Tensor _make_dual_copy(const at::Tensor & primal, const at::Tensor & tangent, int64_t level) { + return at::_ops::_make_dual_copy::call(primal, tangent, level); +} + +// aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _make_dual_copy_out(at::Tensor & out, const at::Tensor & primal, const at::Tensor & tangent, int64_t level) { + return at::_ops::_make_dual_copy_out::call(primal, tangent, level, out); +} +// aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _make_dual_copy_outf(const at::Tensor & primal, const at::Tensor & tangent, int64_t level, at::Tensor & out) { + return at::_ops::_make_dual_copy_out::call(primal, tangent, level, out); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c817e7547dbbccd3e6c165f24cb25583e4e1c406 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_make_per_tensor_quantized_tensor_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _make_per_tensor_quantized_tensor { + using schema = at::Tensor (const at::Tensor &, double, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_make_per_tensor_quantized_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_make_per_tensor_quantized_tensor(Tensor self, float scale, int zero_point) -> Tensor") + static at::Tensor call(const at::Tensor & self, double scale, int64_t zero_point); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point); +}; + +struct TORCH_API _make_per_tensor_quantized_tensor_out { + using schema = at::Tensor & (const at::Tensor &, double, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_make_per_tensor_quantized_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_make_per_tensor_quantized_tensor.out(Tensor self, float scale, int zero_point, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, double scale, int64_t zero_point, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_get_lengths.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_get_lengths.h new file mode 100644 index 0000000000000000000000000000000000000000..28a710f21233082b216a9715c0f3986d9245452e --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_get_lengths.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_nested_get_lengths(Tensor self) -> Tensor +inline at::Tensor _nested_get_lengths(const at::Tensor & self) { + return at::_ops::_nested_get_lengths::call(self); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_softmax_with_shape.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_softmax_with_shape.h new file mode 100644 index 0000000000000000000000000000000000000000..916d2524729d825a61cb2c39ecb5708dd032ff88 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_softmax_with_shape.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor +inline at::Tensor _nested_tensor_softmax_with_shape(const at::Tensor & self, const at::Tensor & query) { + return at::_ops::_nested_tensor_softmax_with_shape::call(self, query); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_from_tensor_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_from_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d47528546ca553326334616fb6ec9c2d76ee27e4 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_from_tensor_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _reshape_from_tensor(const at::Tensor & self, const at::Tensor & shape); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..24fe430ec34aa4bbc4f2a4a4dc9989fae34bf35a --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_efficient_attention_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _scaled_dot_product_efficient_attention { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, bool, double, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_scaled_dot_product_efficient_attention") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_scaled_dot_product_efficient_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_bias, bool compute_log_sumexp, float dropout_p=0.0, bool is_causal=False, *, float? scale=None) -> (Tensor output, Tensor log_sumexp, Tensor philox_seed, Tensor philox_offset)") + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, bool compute_log_sumexp, double dropout_p, bool is_causal, ::std::optional scale); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, bool compute_log_sumexp, double dropout_p, bool is_causal, ::std::optional scale); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy_compositeexplicitautogradnonfunctional_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6400cb646ca8eaf751f358070dc1c2c7c5f2f159 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _test_autograd_multiple_dispatch_view_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_to_cpu.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_to_cpu.h new file mode 100644 index 0000000000000000000000000000000000000000..9ad567d77f11f86fdf307c33e9ad0e7487cacc31 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_to_cpu.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_to_cpu(Tensor[] tensors) -> Tensor[] +inline ::std::vector _to_cpu(at::TensorList tensors) { + return at::_ops::_to_cpu::call(tensors); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..297db4dc307448bc44d48d7eeb9a97ff8553e828 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_native.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +TORCH_API at::Tensor _upsample_nearest_exact2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors); +struct TORCH_API structured__upsample_nearest_exact2d_out_cpu : public at::meta::structured__upsample_nearest_exact2d { +void impl(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +struct TORCH_API structured__upsample_nearest_exact2d_out_cuda : public at::meta::structured__upsample_nearest_exact2d { +void impl(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +TORCH_API at::Tensor _upsample_nearest_exact2d_quantized_cpu(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/acosh_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/acosh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..32ea1a6d9e22a70884e35d7d7139e6ed3fe2148e --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/acosh_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_acosh_out : public at::meta::structured_acosh { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a4dd3bfe5635f18a68b2a93117c1b0fb8fd2ad26 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API adaptive_max_pool3d_out { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::adaptive_max_pool3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "adaptive_max_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); +}; + +struct TORCH_API adaptive_max_pool3d { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::adaptive_max_pool3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "adaptive_max_pool3d(Tensor self, int[3] output_size) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef output_size); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/addr_compositeexplicitautograd_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/addr_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5cac7ec425f0a7b58b3764f479d14068897c258f --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/addr_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor addr(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addr_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addr_outf(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & addr_(at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/affine_grid_generator_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/affine_grid_generator_native.h new file mode 100644 index 0000000000000000000000000000000000000000..08e608404e4ddcf753d0a9e777561887b1a77462 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/affine_grid_generator_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor affine_grid_generator(const at::Tensor & theta, at::IntArrayRef size, bool align_corners); +TORCH_API at::Tensor & affine_grid_generator_out_symint(const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/align_tensors_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/align_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b039c5f6beb132596ff1d5ae9c302878ab95ac59 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/align_tensors_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API align_tensors { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::align_tensors") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "align_tensors(Tensor[] tensors) -> Tensor[]") + static ::std::vector call(at::TensorList tensors); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/any_compositeimplicitautograd_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/any_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d1c89b9aa8374aeb2c8d6ddaba291c8493ab26ec --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/any_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor any(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API at::Tensor & any_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_copy.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..dfa80ec13d0ad03d273737d74efc282c49c31d2d --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_copy.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::as_strided_copy(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor +inline at::Tensor as_strided_copy(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_copy::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt); +} +namespace symint { + template ::value>> + at::Tensor as_strided_copy(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_copy::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt); + } +} + +// aten::as_strided_copy(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor +inline at::Tensor as_strided_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_copy::call(self, size, stride, storage_offset); +} +namespace symint { + template ::value>> + at::Tensor as_strided_copy(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_copy::call(self, size, stride, storage_offset); + } +} + +// aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & as_strided_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt, out); +} +namespace symint { + template ::value>> + at::Tensor & as_strided_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt, out); + } +} + +// aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & as_strided_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset, at::Tensor & out) { + return at::_ops::as_strided_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt, out); +} +namespace symint { + template ::value>> + at::Tensor & as_strided_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset, at::Tensor & out) { + return at::_ops::as_strided_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt, out); + } +} + +// aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & as_strided_copy_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_copy_out::call(self, size, stride, storage_offset, out); +} +namespace symint { + template ::value>> + at::Tensor & as_strided_copy_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_copy_out::call(self, size, stride, storage_offset, out); + } +} + +// aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & as_strided_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset, at::Tensor & out) { + return at::_ops::as_strided_copy_out::call(self, size, stride, storage_offset, out); +} +namespace symint { + template ::value>> + at::Tensor & as_strided_copy_outf(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset, at::Tensor & out) { + return at::_ops::as_strided_copy_out::call(self, size, stride, storage_offset, out); + } +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool3d_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2ac493946bb9fdd7277e1f1008f8870967620185 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool3d_native.h @@ -0,0 +1,29 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_avg_pool3d_out_cpu : public at::meta::structured_avg_pool3d { +void impl(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, const at::Tensor & out); +}; +struct TORCH_API structured_avg_pool3d_out_cuda : public at::meta::structured_avg_pool3d { +void impl(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, const at::Tensor & out); +}; +TORCH_API at::Tensor mkldnn_avg_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, ::std::optional divisor_override=::std::nullopt); +TORCH_API at::Tensor & mkldnn_avg_pool3d_out(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & out); +TORCH_API at::Tensor avg_pool3d_quantized_cpu(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, ::std::optional divisor_override=::std::nullopt); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/baddbmm_meta.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/baddbmm_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..1a15d90db2ac7b26b28640f548150c2ae5a40ef5 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/baddbmm_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_baddbmm : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha); +}; + +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/broadcast_to_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/broadcast_to_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2e524cf21995319bc369397f91724fe2cbe72654 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/broadcast_to_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API broadcast_to { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::broadcast_to") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/bucketize_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/bucketize_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7d86b5a3f240721da103c6c20c4d59a87b3dc8e6 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/bucketize_native.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor bucketize_cpu(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); +TORCH_API at::Tensor & bucketize_out_cpu(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out); +TORCH_API at::Tensor bucketize_cuda(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); +TORCH_API at::Tensor & bucketize_out_cuda(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out); +TORCH_API at::Tensor & bucketize_Scalar_out(const at::Scalar & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out); +TORCH_API at::Tensor bucketize_cpu(const at::Scalar & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); +TORCH_API at::Tensor bucketize_cuda(const at::Scalar & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/channel_shuffle_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/channel_shuffle_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1ddd6fdc66988115293116a0f7d4496570e6683e --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/channel_shuffle_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API channel_shuffle { + using schema = at::Tensor (const at::Tensor &, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::channel_shuffle") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "channel_shuffle(Tensor self, SymInt groups) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt groups); +}; + +struct TORCH_API channel_shuffle_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::channel_shuffle") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "channel_shuffle.out(Tensor self, SymInt groups, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::SymInt groups, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt groups, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/cosh_cpu_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/cosh_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3867516ddcb4830284078f960ca3f885822b5c2c --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/cosh_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor cosh(const at::Tensor & self); +TORCH_API at::Tensor & cosh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & cosh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & cosh_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/elu_cuda_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/elu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..04a76e25109ac742777b3b46fe2d475f8d503b3d --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/elu_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor elu(const at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); +TORCH_API at::Tensor & elu_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); +TORCH_API at::Tensor & elu_outf(const at::Tensor & self, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, at::Tensor & out); +TORCH_API at::Tensor & elu_(at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); + +} // namespace cuda +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/eq.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/eq.h new file mode 100644 index 0000000000000000000000000000000000000000..633b869d0efda0480aefbeb7fc7b2e0a790e429a --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/eq.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::eq.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eq_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::eq_Scalar_out::call(self, other, out); +} +// aten::eq.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eq_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::eq_Scalar_out::call(self, other, out); +} + +// aten::eq.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor eq(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::eq_Scalar::call(self, other); +} + +// aten::eq.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eq_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::eq_Tensor_out::call(self, other, out); +} +// aten::eq.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eq_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::eq_Tensor_out::call(self, other, out); +} + +// aten::eq.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor eq(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::eq_Tensor::call(self, other); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/eye_cuda_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/eye_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ff56d09b88d47bbb04866c0bb736ff1a7deed90 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/eye_cuda_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & eye_out(at::Tensor & out, int64_t n); +TORCH_API at::Tensor & eye_outf(int64_t n, at::Tensor & out); +TORCH_API at::Tensor & eye_symint_out(at::Tensor & out, c10::SymInt n); +TORCH_API at::Tensor & eye_symint_outf(c10::SymInt n, at::Tensor & out); +TORCH_API at::Tensor & eye_out(at::Tensor & out, int64_t n, int64_t m); +TORCH_API at::Tensor & eye_outf(int64_t n, int64_t m, at::Tensor & out); +TORCH_API at::Tensor & eye_symint_out(at::Tensor & out, c10::SymInt n, c10::SymInt m); +TORCH_API at::Tensor & eye_symint_outf(c10::SymInt n, c10::SymInt m, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_cuda_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8553a6158d02dc5d7c1ff9b09dd19ce8c1b6a9e9 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple fake_quantize_per_tensor_affine_cachemask(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max); + +} // namespace cuda +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fftfreq_compositeexplicitautograd_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fftfreq_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9aadeecda67b12059dd3e118530adc6a6bb1e207 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fftfreq_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor fft_fftfreq(int64_t n, double d=1.0, at::TensorOptions options={}); +TORCH_API at::Tensor fft_fftfreq(int64_t n, double d, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & fft_fftfreq_out(at::Tensor & out, int64_t n, double d=1.0); +TORCH_API at::Tensor & fft_fftfreq_outf(int64_t n, double d, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautogradnonfunctional_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a93af795ba6130deb5c016110ec8d823fe028b72 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor fmod(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/hardshrink_meta.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/hardshrink_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..c7765a90e43a93fe516c5bcb608968ade1199504 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/hardshrink_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_hardshrink : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Scalar & lambd); +}; + +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4de83514317b1f429fce7c809a5db850a1f58859 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor hardsigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & hardsigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & hardsigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/igamma_compositeexplicitautogradnonfunctional_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/igamma_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..993156e810d1e7fb1576fda00cf1855602473f28 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/igamma_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor igamma(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igamma_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/is_vulkan_available_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/is_vulkan_available_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..07ed34586debb6dca3a0d3189a87b75e69491707 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/is_vulkan_available_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API is_vulkan_available { + using schema = bool (); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::is_vulkan_available") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "is_vulkan_available() -> bool") + static bool call(); + static bool redispatch(c10::DispatchKeySet dispatchKeySet); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_eigvalsh_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_eigvalsh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e2e52a0fd339abe814f4c140090d6d4461892fcf --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_eigvalsh_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor linalg_eigvalsh(const at::Tensor & self, c10::string_view UPLO="L"); +TORCH_API at::Tensor & linalg_eigvalsh_out(const at::Tensor & self, c10::string_view UPLO, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_cuda_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..32fbb5a1a10123e494665d5264630859c464c450 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor linalg_ldl_solve(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian=false); +TORCH_API at::Tensor & linalg_ldl_solve_out(at::Tensor & out, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian=false); +TORCH_API at::Tensor & linalg_ldl_solve_outf(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_norm.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..6ddd1af6f50748cf5d761908b7dd864b906d9b81 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_norm.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linalg_norm(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor linalg_norm(const at::Tensor & self, const ::std::optional & ord=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::linalg_norm::call(self, ord, dim, keepdim, dtype); +} + +// aten::linalg_norm.ord_str(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor linalg_norm(const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::linalg_norm_ord_str::call(self, ord, dim, keepdim, dtype); +} + +// aten::linalg_norm.out(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & ord=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::linalg_norm_out::call(self, ord, dim, keepdim, dtype, out); +} +// aten::linalg_norm.out(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_norm_outf(const at::Tensor & self, const ::std::optional & ord, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::linalg_norm_out::call(self, ord, dim, keepdim, dtype, out); +} + +// aten::linalg_norm.ord_str_out(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_norm_out(at::Tensor & out, const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::linalg_norm_ord_str_out::call(self, ord, dim, keepdim, dtype, out); +} +// aten::linalg_norm.ord_str_out(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_norm_outf(const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::linalg_norm_ord_str_out::call(self, ord, dim, keepdim, dtype, out); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_pinv_compositeimplicitautograd_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_pinv_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9698aeed45b20c7f40b54e6fedcfeb539dc5a33c --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_pinv_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor linalg_pinv(const at::Tensor & self, ::std::optional atol, ::std::optional rtol, bool hermitian=false); +TORCH_API at::Tensor & linalg_pinv_out(at::Tensor & out, const at::Tensor & self, ::std::optional atol, ::std::optional rtol, bool hermitian=false); +TORCH_API at::Tensor & linalg_pinv_outf(const at::Tensor & self, ::std::optional atol, ::std::optional rtol, bool hermitian, at::Tensor & out); +TORCH_API at::Tensor linalg_pinv(const at::Tensor & self, double rcond, bool hermitian=false); +TORCH_API at::Tensor & linalg_pinv_out(at::Tensor & out, const at::Tensor & self, double rcond, bool hermitian=false); +TORCH_API at::Tensor & linalg_pinv_outf(const at::Tensor & self, double rcond, bool hermitian, at::Tensor & out); +TORCH_API at::Tensor linalg_pinv(const at::Tensor & self, const at::Tensor & rcond, bool hermitian=false); +TORCH_API at::Tensor & linalg_pinv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & rcond, bool hermitian=false); +TORCH_API at::Tensor & linalg_pinv_outf(const at::Tensor & self, const at::Tensor & rcond, bool hermitian, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/log_normal_meta_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/log_normal_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cbf5c2c6369303eeb15f610c06e3969b4c9a70e2 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/log_normal_meta_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & log_normal_(at::Tensor & self, double mean=1, double std=2, ::std::optional generator=::std::nullopt); + +} // namespace meta +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/logspace_cuda_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/logspace_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9c9a1134679edc2c02aa0e90c46c9430717ff5da --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/logspace_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & logspace_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, int64_t steps, double base=10.0); +TORCH_API at::Tensor & logspace_outf(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/mul_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/mul_native.h new file mode 100644 index 0000000000000000000000000000000000000000..55939fb8cf3cfe38e23d48235db0244d36f4cd43 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/mul_native.h @@ -0,0 +1,43 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_mul_out : public at::meta::structured_mul_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_mul_Tensor(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & NestedTensor_mul__Tensor(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor mul_sparse(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out_sparse_cpu(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mul_sparse_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out_sparse_cuda(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor mul_sparse_csr(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out_sparse_csr(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mul_sparse_csr_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor mkldnn_mul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mkldnn_mul_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mkldnn_mul_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor mul_zerotensor(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor mul(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & mul_Scalar_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & mul_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor NestedTensor_mul_Scalar(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & NestedTensor_mul__Scalar(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor mul_scalar_sparse_csr(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & mul__scalar_sparse_csr(at::Tensor & self, const at::Scalar & other); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_compositeexplicitautogradnonfunctional_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2d8304d9d1eb9a7a3879a74e39488816971a56d9 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor narrow_copy(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_copy_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss2d.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss2d.h new file mode 100644 index 0000000000000000000000000000000000000000..df4b0792dbb26ace27adeec17f41752d18d0b75b --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss2d.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nll_loss2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, int64_t ignore_index=-100) { + return at::_ops::nll_loss2d_out::call(self, target, weight, reduction, ignore_index, out); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, int64_t ignore_index=-100) { + return at::_ops::nll_loss2d_out::call(self, target, weight, reduction, ignore_index, out); + } +} + +// aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nll_loss2d_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, at::Tensor & out) { + return at::_ops::nll_loss2d_out::call(self, target, weight, reduction, ignore_index, out); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss2d_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, at::Tensor & out) { + return at::_ops::nll_loss2d_out::call(self, target, weight, reduction, ignore_index, out); + } +} + +// aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nll_loss2d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, c10::SymInt ignore_index=-100) { + return at::_ops::nll_loss2d_out::call(self, target, weight, reduction, ignore_index, out); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, c10::SymInt ignore_index=-100) { + return at::_ops::nll_loss2d_out::call(self, target, weight, reduction, ignore_index, out); + } +} + +// aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nll_loss2d_symint_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & out) { + return at::_ops::nll_loss2d_out::call(self, target, weight, reduction, ignore_index, out); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss2d_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & out) { + return at::_ops::nll_loss2d_out::call(self, target, weight, reduction, ignore_index, out); + } +} + +// aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor +inline at::Tensor nll_loss2d(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, int64_t ignore_index=-100) { + return at::_ops::nll_loss2d::call(self, target, weight, reduction, ignore_index); +} +namespace symint { + template ::value>> + at::Tensor nll_loss2d(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, int64_t ignore_index=-100) { + return at::_ops::nll_loss2d::call(self, target, weight, reduction, ignore_index); + } +} + +// aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor +inline at::Tensor nll_loss2d_symint(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, c10::SymInt ignore_index=-100) { + return at::_ops::nll_loss2d::call(self, target, weight, reduction, ignore_index); +} +namespace symint { + template ::value>> + at::Tensor nll_loss2d(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, c10::SymInt ignore_index=-100) { + return at::_ops::nll_loss2d::call(self, target, weight, reduction, ignore_index); + } +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/q_scale.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/q_scale.h new file mode 100644 index 0000000000000000000000000000000000000000..a6fdd8f453cf7ad9f5844fd29f978e976831ae34 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/q_scale.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::q_scale(Tensor self) -> float +inline double q_scale(const at::Tensor & self) { + return at::_ops::q_scale::call(self); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/quantile_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/quantile_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8223a9100e2c03428d3a51be6d43371f407c8d23 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/quantile_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor quantile(const at::Tensor & self, const at::Tensor & q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear"); +TORCH_API at::Tensor & quantile_out(const at::Tensor & self, const at::Tensor & q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); +TORCH_API at::Tensor quantile(const at::Tensor & self, double q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear"); +TORCH_API at::Tensor & quantile_out(const at::Tensor & self, double q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/range_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/range_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..52f793d7a25a95d092256c302d262c49a2decac6 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/range_ops.h @@ -0,0 +1,61 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API range_step { + using schema = at::Tensor (const at::Scalar &, const at::Scalar &, const at::Scalar &, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::range") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "step") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "range.step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API range { + using schema = at::Tensor (const at::Scalar &, const at::Scalar &, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::range") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "range(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(const at::Scalar & start, const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API range_out_ { + using schema = at::Tensor & (const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::range") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "range.out_(Scalar start, Scalar end, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Scalar & start, const at::Scalar & end, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, at::Tensor & out); +}; + +struct TORCH_API range_out { + using schema = at::Tensor & (const at::Scalar &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::range") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "range.out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/select_copy_compositeexplicitautograd_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/select_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..12882704b1313bbac0b9f533ffe6dba754203905 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/select_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & select_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t index); +TORCH_API at::Tensor & select_copy_outf(const at::Tensor & self, int64_t dim, int64_t index, at::Tensor & out); +TORCH_API at::Tensor & select_copy_symint_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt index); +TORCH_API at::Tensor & select_copy_symint_outf(const at::Tensor & self, int64_t dim, c10::SymInt index, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/selu.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/selu.h new file mode 100644 index 0000000000000000000000000000000000000000..1130831c138cb6a3dc42cec44b259b4acf54f1a8 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/selu.h @@ -0,0 +1,35 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::selu(Tensor self) -> Tensor +inline at::Tensor selu(const at::Tensor & self) { + return at::_ops::selu::call(self); +} + +// aten::selu_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & selu_(at::Tensor & self) { + return at::_ops::selu_::call(self); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/slice_scatter_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/slice_scatter_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b2a54e064c65329ffe92c4a5b47295d02bbe1019 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/slice_scatter_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API slice_scatter { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, ::std::optional, ::std::optional, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slice_scatter") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slice_scatter(Tensor self, Tensor src, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & src, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step); +}; + +struct TORCH_API slice_scatter_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, ::std::optional, ::std::optional, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slice_scatter") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slice_scatter.out(Tensor self, Tensor src, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & src, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv3d_forward_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv3d_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..925bf1378adeed7532b2578cfd86dae5ee847dfb --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv3d_forward_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor slow_conv3d_forward_cpu(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor & slow_conv3d_forward_out_cpu(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & output); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/smooth_l1_loss_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/smooth_l1_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bc4116ce924d92f2f588c92939d7b5b5241e73f7 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/smooth_l1_loss_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API smooth_l1_loss_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::smooth_l1_loss") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "smooth_l1_loss.out(Tensor self, Tensor target, int reduction=Mean, float beta=1.0, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & out); +}; + +struct TORCH_API smooth_l1_loss { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::smooth_l1_loss") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "smooth_l1_loss(Tensor self, Tensor target, int reduction=Mean, float beta=1.0) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/softmax.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/softmax.h new file mode 100644 index 0000000000000000000000000000000000000000..a3983f0890046ad99fcc153989f88dc0f4fc7547 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/softmax.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor +inline at::Tensor softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::softmax_int::call(self, dim, dtype); +} + +// aten::softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::softmax_int_out::call(self, dim, dtype, out); +} +// aten::softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & softmax_outf(const at::Tensor & self, int64_t dim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::softmax_int_out::call(self, dim, dtype, out); +} + +// aten::softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor softmax(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::softmax_Dimname::call(self, dim, dtype); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_j1_cpu_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_j1_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ab8120bd229c623244c5ee02841608ef2dfd8dcc --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_j1_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_bessel_j1(const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_j1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_j1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_y1_cuda_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_y1_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1d560c15ae37558b7f2cda7f3d060dfb6f82983d --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_y1_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_bessel_y1(const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/split_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/split_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bf0450777a795e56925f4d0a3df3c21072055353 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/split_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API split_Tensor { + using schema = ::std::vector (const at::Tensor &, c10::SymInt, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::split") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[]") + static ::std::vector call(const at::Tensor & self, c10::SymInt split_size, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim); +}; + +struct TORCH_API split_sizes { + using schema = ::std::vector (const at::Tensor &, c10::SymIntArrayRef, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::split") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "sizes") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[]") + static ::std::vector call(const at::Tensor & self, c10::SymIntArrayRef split_size, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_size, int64_t dim); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/sub_ops.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/sub_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1cf0632494db529e8da505da5b4491c05f83e253 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/sub_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sub_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +}; + +struct TORCH_API sub_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/t_copy.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/t_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..e562aef2b818e8418664c6e06031a3f2f76acf46 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/t_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::t_copy(Tensor self) -> Tensor +inline at::Tensor t_copy(const at::Tensor & self) { + return at::_ops::t_copy::call(self); +} + +// aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & t_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::t_copy_out::call(self, out); +} +// aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & t_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::t_copy_out::call(self, out); +} + +} diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/to_mkldnn_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/to_mkldnn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2d2a595c5c8b4d6f232b0a459fb78f3bb597ad44 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/to_mkldnn_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & to_mkldnn_out(const at::Tensor & self, ::std::optional dtype, at::Tensor & out); +TORCH_API at::Tensor dense_to_mkldnn(const at::Tensor & self, ::std::optional dtype=::std::nullopt); +} // namespace native +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_compositeimplicitautograd_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5e95242aa2af6716eb71736e1bc4211e34276502 --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor trace_backward(const at::Tensor & grad, at::IntArrayRef sizes); +TORCH_API at::Tensor trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_meta_dispatch.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..516c778dc2ae1c517e4e25a58db4b541dfc3ffda --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor upsample_trilinear3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_trilinear3d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_trilinear3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/xor_native.h b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/xor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..73289b3182d5aa422910188268e280c1af4c936f --- /dev/null +++ b/pllava/lib/python3.10/site-packages/torch/include/ATen/ops/xor_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor __xor__(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & __ixor__(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor __xor__(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & __ixor__(at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at