diff --git a/.gitattributes b/.gitattributes index 59c6f5f26d9eb5249b073fab1c294f96f46119b9..1472b0e4e9b2b27456139d8ad9eaba71538bc0c6 100644 --- a/.gitattributes +++ b/.gitattributes @@ -491,3 +491,4 @@ videollama2/lib/python3.10/site-packages/cv2/qt/fonts/DejaVuSansCondensed.ttf fi parrot/lib/python3.10/site-packages/xformers/_C.so filter=lfs diff=lfs merge=lfs -text parrot/lib/libasan.so.6 filter=lfs diff=lfs merge=lfs -text parrot/lib/python3.10/site-packages/tiktoken/_tiktoken.cpython-310-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text +mantis_evalkit/lib/python3.10/site-packages/pyarrow/lib.cpython-310-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text diff --git a/mantis_evalkit/lib/python3.10/site-packages/pyarrow/lib.cpython-310-x86_64-linux-gnu.so b/mantis_evalkit/lib/python3.10/site-packages/pyarrow/lib.cpython-310-x86_64-linux-gnu.so new file mode 100644 index 0000000000000000000000000000000000000000..858692214c7894128530aa5fe6af8a1471ebd3af --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/pyarrow/lib.cpython-310-x86_64-linux-gnu.so @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:10e64df432403e0b838dd276ab83637c3e51ff8f1000c677239d621a8d8d492f +size 4854672 diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_async_cpu_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_async_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b86572c7e28bec53883a61bff7a17acbd65d1191 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_async_cpu_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 cpu { + +TORCH_API void _assert_async(const at::Tensor & self); +TORCH_API void _assert_async(const at::Tensor & self, c10::string_view assert_msg); + +} // namespace cpu +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Char_compositeimplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Char_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..65388193206ff3e2c9425335637b62c8f8a0effe --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Char_compositeimplicitautograd_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 compositeimplicitautograd { + +TORCH_API at::Tensor _cast_Char(const at::Tensor & self, bool non_blocking=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_copy_from_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_copy_from_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4471cf73f2b7d1c21d91ca164f8baf7818fa829c --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_copy_from_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 & _copy_from_out(const at::Tensor & self, const at::Tensor & dst, bool non_blocking, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a5cd2aff65e7acbd45dae7c7e5e6e291493d17ce --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_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 _embedding_bag { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, int64_t, bool, const ::std::optional &, bool, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_embedding_bag") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1) -> (Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx); +}; + +struct TORCH_API _embedding_bag_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, int64_t, bool, const ::std::optional &, bool, int64_t, 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::_embedding_bag") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_embedding_bag.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))") + static ::std::tuple call(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r.h new file mode 100644 index 0000000000000000000000000000000000000000..e2ff7ef5514b5a2a3c056bbc44fbb0aa9ad345b8 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r.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::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template ::value>> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r_symint(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template ::value>> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_native.h new file mode 100644 index 0000000000000000000000000000000000000000..725926bbd15c624c81246b9d8aaf26588c986bd9 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_native.h @@ -0,0 +1,25 @@ +#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 ::std::vector foreach_tensor_asin_slow(at::TensorList self); +TORCH_API void _foreach_asin_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_asin_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_asin_cuda(at::TensorList self); +TORCH_API void foreach_tensor_asin_cuda_(at::TensorList self); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6b261fc131cb71b27ac2448fac375de2f33c6c06 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_tanh_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_tanh { + 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_tanh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_tanh(Tensor[] self) -> Tensor[]") + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_tanh_ { + 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_tanh_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_tanh_(Tensor(a!)[] self) -> ()") + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_tanh_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_tanh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_tanh.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/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4d546942f8608e8f91b149cc94fa4590dfc7799 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_gather_sparse_backward_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 _gather_sparse_backward { + using schema = at::Tensor (const at::Tensor &, int64_t, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_gather_sparse_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_gather_sparse_backward(Tensor self, int dim, Tensor index, Tensor grad) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_logcumsumexp_cpu_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_logcumsumexp_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0885d11999d5d3f2c5a627f6e8d82cc2ee9c2ae3 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_logcumsumexp_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 _logcumsumexp(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & _logcumsumexp_out(at::Tensor & out, const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & _logcumsumexp_outf(const at::Tensor & self, int64_t dim, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_mps_convolution_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_mps_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..072af280fde0361be1fce94b87365338f787f9a9 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_mps_convolution_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 _mps_convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_mps_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_mps_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +struct TORCH_API _mps_convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, 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::_mps_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_mps_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_pin_memory.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_pin_memory.h new file mode 100644 index 0000000000000000000000000000000000000000..7fe1d2c08cfaf5bfdf926139ae114a7732687477 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_pin_memory.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::_pin_memory(Tensor self, Device? device=None) -> Tensor +inline at::Tensor _pin_memory(const at::Tensor & self, ::std::optional device=::std::nullopt) { + return at::_ops::_pin_memory::call(self, device); +} + +// aten::_pin_memory.out(Tensor self, Device? device=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _pin_memory_out(at::Tensor & out, const at::Tensor & self, ::std::optional device=::std::nullopt) { + return at::_ops::_pin_memory_out::call(self, device, out); +} +// aten::_pin_memory.out(Tensor self, Device? device=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _pin_memory_outf(const at::Tensor & self, ::std::optional device, at::Tensor & out) { + return at::_ops::_pin_memory_out::call(self, device, out); +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_sobol_engine_draw_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_sobol_engine_draw_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c9e03ba718199a5ee9fd6c1c1a87dc241d62481b --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_sobol_engine_draw_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 _sobol_engine_draw { + using schema = ::std::tuple (const at::Tensor &, int64_t, const at::Tensor &, int64_t, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sobol_engine_draw") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sobol_engine_draw(Tensor quasi, int n, Tensor sobolstate, int dimension, int num_generated, ScalarType? dtype) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & quasi, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated, ::std::optional dtype); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & quasi, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated, ::std::optional dtype); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0a76c27fbf4bbdc0f6a922c556630456d520462e --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile_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 _sparse_semi_structured_tile { + using schema = ::std::tuple (const at::Tensor &, c10::string_view, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_semi_structured_tile") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_semi_structured_tile(Tensor input, str algorithm=\"\", bool use_cutlass=True) -> (Tensor, Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, c10::string_view algorithm, bool use_cutlass); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, c10::string_view algorithm, bool use_cutlass); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_cuda_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e06b2dc1c25f8656c0ef3c69188493c613b65a34 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_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 _thnn_fused_lstm_cell(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & cx, const ::std::optional & input_bias={}, const ::std::optional & hidden_bias={}); + +} // namespace cuda +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr.h new file mode 100644 index 0000000000000000000000000000000000000000..e856b14d91f21d82964311227f485314c03b5288 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr.h @@ -0,0 +1,34 @@ +#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_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_csr_out(at::Tensor & out, const at::Tensor & self, ::std::optional dense_dim=::std::nullopt) { + return at::_ops::_to_sparse_csr_out::call(self, dense_dim, out); +} +// aten::_to_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_csr_outf(const at::Tensor & self, ::std::optional dense_dim, at::Tensor & out) { + return at::_ops::_to_sparse_csr_out::call(self, dense_dim, out); +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_meta_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..98c0c313e8325b3b6bd382470f5e5e39ef552606 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_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_bilinear2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_bilinear2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d.h new file mode 100644 index 0000000000000000000000000000000000000000..b5690c9871cd47c6a9f140778b872615816fb897 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d.h @@ -0,0 +1,113 @@ +#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::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor +inline at::Tensor _upsample_nearest_exact1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::_upsample_nearest_exact1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors); +} +namespace symint { + template ::value>> + at::Tensor _upsample_nearest_exact1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::_upsample_nearest_exact1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors); + } +} + +// aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor +inline at::Tensor _upsample_nearest_exact1d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::_upsample_nearest_exact1d_vec::call(input, output_size, scale_factors); +} +namespace symint { + template ::value>> + at::Tensor _upsample_nearest_exact1d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::_upsample_nearest_exact1d_vec::call(input, output_size, scale_factors); + } +} + +// aten::_upsample_nearest_exact1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_nearest_exact1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); + } +} + +// aten::_upsample_nearest_exact1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_nearest_exact1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); + } +} + +// aten::_upsample_nearest_exact1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, output_size, scales, out); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_nearest_exact1d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, output_size, scales, out); + } +} + +// aten::_upsample_nearest_exact1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, output_size, scales, out); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_nearest_exact1d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, output_size, scales, out); + } +} + +// aten::_upsample_nearest_exact1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor +inline at::Tensor _upsample_nearest_exact1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d::call(self, c10::fromIntArrayRefSlow(output_size), scales); +} +namespace symint { + template ::value>> + at::Tensor _upsample_nearest_exact1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d::call(self, c10::fromIntArrayRefSlow(output_size), scales); + } +} + +// aten::_upsample_nearest_exact1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor +inline at::Tensor _upsample_nearest_exact1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d::call(self, output_size, scales); +} +namespace symint { + template ::value>> + at::Tensor _upsample_nearest_exact1d(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d::call(self, output_size, scales); + } +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_compositeexplicitautogradnonfunctional_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..433d069ede44ebd4964c7379c08cf5e4d27955b3 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_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 _upsample_nearest_exact1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/addcdiv_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/addcdiv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9f1f14aa9fcebe5cbd02646ae697817abb580125 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/addcdiv_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 addcdiv_out { + using schema = at::Tensor & (const 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::addcdiv") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "addcdiv.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); +}; + +struct TORCH_API addcdiv { + using schema = at::Tensor (const 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::addcdiv") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "addcdiv(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); +}; + +struct TORCH_API addcdiv_ { + using schema = at::Tensor & (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::addcdiv_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "addcdiv_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/arccosh_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/arccosh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2e648a299bcdc2f9476bfee79099c46b9487d9be --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/arccosh_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 arccosh(const at::Tensor & self); +TORCH_API at::Tensor & arccosh_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & arccosh_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_copy_compositeexplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..593eeaae71f4c503ffcea493612ba5979ce928e6 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_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 & as_strided_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt); +TORCH_API at::Tensor & as_strided_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset, at::Tensor & out); +TORCH_API 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); +TORCH_API at::Tensor & as_strided_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/binary_cross_entropy_backward.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/binary_cross_entropy_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..39834726f105ead8238100cd8ef00e7ecd2f4cfe --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/binary_cross_entropy_backward.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::binary_cross_entropy_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean) -> Tensor +inline at::Tensor binary_cross_entropy_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::binary_cross_entropy_backward::call(grad_output, self, target, weight, reduction); +} + +// aten::binary_cross_entropy_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & binary_cross_entropy_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::binary_cross_entropy_backward_grad_input::call(grad_output, self, target, weight, reduction, grad_input); +} +// aten::binary_cross_entropy_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & binary_cross_entropy_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input) { + return at::_ops::binary_cross_entropy_backward_grad_input::call(grad_output, self, target, weight, reduction, grad_input); +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/conv_transpose3d_compositeimplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/conv_transpose3d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5a2490e5d71a419e39c96de04de0fb4cbda373a1 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/conv_transpose3d_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 conv_transpose3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, int64_t groups=1, at::IntArrayRef dilation=1); +TORCH_API at::Tensor conv_transpose3d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymInt groups=1, c10::SymIntArrayRef dilation=c10::SymInt(1)); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/corrcoef_compositeimplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/corrcoef_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd3732a5f394acc1dce48683fe76a6d57ea78a2a --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/corrcoef_compositeimplicitautograd_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 compositeimplicitautograd { + +TORCH_API at::Tensor corrcoef(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/corrcoef_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/corrcoef_native.h new file mode 100644 index 0000000000000000000000000000000000000000..20b6127377beb61089a37539b23e1644903ff85f --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/corrcoef_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 corrcoef(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/count_nonzero_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/count_nonzero_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3341e4d98f9a0e2eeb06a537cd74d854cc050051 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/count_nonzero_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 count_nonzero_dim_IntList { + using schema = at::Tensor (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::count_nonzero") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dim_IntList") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "count_nonzero.dim_IntList(Tensor self, int[] dim) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim); +}; + +struct TORCH_API count_nonzero { + using schema = at::Tensor (const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::count_nonzero") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "count_nonzero(Tensor self, int? dim=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, ::std::optional dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dim); +}; + +struct TORCH_API count_nonzero_dim_IntList_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::count_nonzero") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dim_IntList_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); +}; + +struct TORCH_API count_nonzero_out { + using schema = at::Tensor & (const at::Tensor &, ::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::count_nonzero") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, ::std::optional dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_convolution_add_relu.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_convolution_add_relu.h new file mode 100644 index 0000000000000000000000000000000000000000..bdca8ddcd64942021d532163ee301fa92ba3ca5d --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_convolution_add_relu.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::cudnn_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor cudnn_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::cudnn_convolution_add_relu::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template ::value>> + at::Tensor cudnn_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::cudnn_convolution_add_relu::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::cudnn_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor cudnn_convolution_add_relu_symint(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::cudnn_convolution_add_relu::call(self, weight, z, alpha, bias, stride, padding, dilation, groups); +} +namespace symint { + template ::value>> + at::Tensor cudnn_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::cudnn_convolution_add_relu::call(self, weight, z, alpha, bias, stride, padding, dilation, groups); + } +} + +// aten::cudnn_convolution_add_relu.out(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_add_relu_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::cudnn_convolution_add_relu_out::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template ::value>> + at::Tensor & cudnn_convolution_add_relu_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::cudnn_convolution_add_relu_out::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::cudnn_convolution_add_relu.out(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_add_relu_outf(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::cudnn_convolution_add_relu_out::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template ::value>> + at::Tensor & cudnn_convolution_add_relu_outf(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::cudnn_convolution_add_relu_out::call(self, weight, z, alpha, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::cudnn_convolution_add_relu.out(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_add_relu_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::cudnn_convolution_add_relu_out::call(self, weight, z, alpha, bias, stride, padding, dilation, groups, out); +} +namespace symint { + template ::value>> + at::Tensor & cudnn_convolution_add_relu_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::cudnn_convolution_add_relu_out::call(self, weight, z, alpha, bias, stride, padding, dilation, groups, out); + } +} + +// aten::cudnn_convolution_add_relu.out(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_add_relu_symint_outf(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::cudnn_convolution_add_relu_out::call(self, weight, z, alpha, bias, stride, padding, dilation, groups, out); +} +namespace symint { + template ::value>> + at::Tensor & cudnn_convolution_add_relu_outf(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::cudnn_convolution_add_relu_out::call(self, weight, z, alpha, bias, stride, padding, dilation, groups, out); + } +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/deg2rad.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/deg2rad.h new file mode 100644 index 0000000000000000000000000000000000000000..e284f242c36cfcb15af3379845f10a8ba3b77cee --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/deg2rad.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::deg2rad(Tensor self) -> Tensor +inline at::Tensor deg2rad(const at::Tensor & self) { + return at::_ops::deg2rad::call(self); +} + +// aten::deg2rad_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & deg2rad_(at::Tensor & self) { + return at::_ops::deg2rad_::call(self); +} + +// aten::deg2rad.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & deg2rad_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::deg2rad_out::call(self, out); +} +// aten::deg2rad.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & deg2rad_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::deg2rad_out::call(self, out); +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_copy_compositeexplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..46489889de9e731e487078f8ea0742bc58d12a24 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_copy_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API at::Tensor & diagonal_copy_out(at::Tensor & out, const at::Tensor & self, int64_t offset=0, int64_t dim1=0, int64_t dim2=1); +TORCH_API at::Tensor & diagonal_copy_outf(const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/einsum_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/einsum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bf977c9dd59ec4817ff74c2fcdb128f5430b77d8 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/einsum_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 einsum { + using schema = at::Tensor (c10::string_view, at::TensorList, at::OptionalIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::einsum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "einsum(str equation, Tensor[] tensors, *, int[]? path=None) -> Tensor") + static at::Tensor call(c10::string_view equation, at::TensorList tensors, at::OptionalIntArrayRef path); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view equation, at::TensorList tensors, at::OptionalIntArrayRef path); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_dense_backward_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_dense_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..006d55e1c83b386b0901635cdd103063595eef60 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_dense_backward_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 & embedding_dense_backward_out_symint(const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, at::Tensor & out); +TORCH_API at::Tensor embedding_dense_backward_cpu(const at::Tensor & grad_output, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq); +TORCH_API at::Tensor embedding_dense_backward_cuda(const at::Tensor & grad_output, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/erfc_cuda_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/erfc_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7a5524deafac2050bb073a931fa1d0b945415b97 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/erfc_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 erfc(const at::Tensor & self); +TORCH_API at::Tensor & erfc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & erfc_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & erfc_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/expand_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/expand_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4a0b82a7fa315eb6e8bba6fea18731d1c7bc590b --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/expand_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 expand { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::expand") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "expand(Tensor(a) self, SymInt[] size, *, bool implicit=False) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, bool implicit); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, bool implicit); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_backward_compositeimplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..933b0f3b741b2d6ed9f3159b2b2ab2ff64921a6b --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_backward_compositeimplicitautograd_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 compositeimplicitautograd { + +TORCH_API at::Tensor fake_quantize_per_tensor_affine_cachemask_backward(const at::Tensor & grad, const at::Tensor & mask); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fft2.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fft2.h new file mode 100644 index 0000000000000000000000000000000000000000..ac43cc0ca2bb379c08519b3ca933a90dd9cc0d82 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fft2.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::fft_fft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor +inline at::Tensor fft_fft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_fft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_fft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor +inline at::Tensor fft_fft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft2::call(self, s, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_fft2(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft2::call(self, s, dim, norm); + } +} + +// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft2_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft2_out::call(self, s, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_fft2_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft2_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fft2_out::call(self, s, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_fft2_out::call(self, s, dim, norm, out); + } +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/floor.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/floor.h new file mode 100644 index 0000000000000000000000000000000000000000..fc85edd89744f261cac5beb3772479adce61a23c --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/floor.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::floor(Tensor self) -> Tensor +inline at::Tensor floor(const at::Tensor & self) { + return at::_ops::floor::call(self); +} + +// aten::floor_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & floor_(at::Tensor & self) { + return at::_ops::floor_::call(self); +} + +// aten::floor.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & floor_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::floor_out::call(self, out); +} +// aten::floor.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & floor_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::floor_out::call(self, out); +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/fmod_meta.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/fmod_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e57dfa88967bb36f4fec4750c3e6fa9d1e9a5f1c --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/fmod_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_fmod_Tensor : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/glu_backward_jvp_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/glu_backward_jvp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c700e1dd0ce229eee62095a607669df3697a7e3b --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/glu_backward_jvp_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 glu_backward_jvp { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::glu_backward_jvp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "glu_backward_jvp(Tensor grad_x, Tensor grad_glu, Tensor x, Tensor dgrad_glu, Tensor dx, int dim) -> Tensor") + static at::Tensor call(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim); +}; + +struct TORCH_API glu_backward_jvp_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, 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::glu_backward_jvp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "glu_backward_jvp.out(Tensor grad_x, Tensor grad_glu, Tensor x, Tensor dgrad_glu, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/hypot_meta.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/hypot_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..4825a2a111d53ee864a820cfa7b6201a6639c107 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/hypot_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_hypot : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/is_coalesced_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/is_coalesced_native.h new file mode 100644 index 0000000000000000000000000000000000000000..319f5bd5214d820ed7a840538d60d9df735ad870 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/is_coalesced_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 bool is_coalesced_default(const at::Tensor & self); +TORCH_API bool is_coalesced_sparse(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/is_neg_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/is_neg_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4a077f5f85d1536ec5453799882069821fb6cdbf --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/is_neg_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 bool is_neg(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d601b61ad7a29c998b2c6e1a18a99c46af23c8f2 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_native.h @@ -0,0 +1,26 @@ +#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_leaky_relu_out : public at::meta::structured_leaky_relu { +void impl(const at::Tensor & self, const at::Scalar & negative_slope, const at::Tensor & out); +}; +TORCH_API at::Tensor leaky_relu_quantized_cpu(const at::Tensor & self, const at::Scalar & negative_slope=0.01); +TORCH_API at::Tensor & leaky_relu_out_quantized_cpu(const at::Tensor & self, const at::Scalar & negative_slope, at::Tensor & out); +TORCH_API at::Tensor & leaky_relu_quantized_cpu_(at::Tensor & self, const at::Scalar & negative_slope=0.01); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_factor_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_factor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ca856a13fe23a3e381bce9aa16b07a581827a20a --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_factor_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 linalg_lu_factor { + using schema = ::std::tuple (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_lu_factor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_lu_factor(Tensor A, *, bool pivot=True) -> (Tensor LU, Tensor pivots)") + static ::std::tuple call(const at::Tensor & A, bool pivot); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool pivot); +}; + +struct TORCH_API linalg_lu_factor_out { + using schema = ::std::tuple (const at::Tensor &, bool, 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::linalg_lu_factor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_lu_factor.out(Tensor A, *, bool pivot=True, Tensor(a!) LU, Tensor(b!) pivots) -> (Tensor(a!) LU, Tensor(b!) pivots)") + static ::std::tuple call(const at::Tensor & A, bool pivot, at::Tensor & LU, at::Tensor & pivots); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool pivot, at::Tensor & LU, at::Tensor & pivots); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/lstm_mps_backward_compositeexplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/lstm_mps_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..27a000c9bea2ae202910accaf1c1da45edebb7fc --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/lstm_mps_backward_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API void lstm_mps_backward_out(at::Tensor & out0, at::TensorList out1, at::TensorList out2, const ::std::optional & grad_y, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & z_state, const at::Tensor & cell_state_fwd, const at::Tensor & input, const at::Tensor & layersOutputs, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first); +TORCH_API void lstm_mps_backward_outf(const ::std::optional & grad_y, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & z_state, const at::Tensor & cell_state_fwd, const at::Tensor & input, const at::Tensor & layersOutputs, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first, at::Tensor & out0, at::TensorList out1, at::TensorList out2); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/lt_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/lt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dce5c55d8f7891f3aeef763d7b5e78339a82b305 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/lt_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 lt_Scalar_out { + using schema = 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::lt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +struct TORCH_API lt_Scalar { + using schema = 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::lt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt.Scalar(Tensor self, Scalar other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API lt_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const 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::lt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API lt_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt.Tensor(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API lt__Scalar { + using schema = at::Tensor & (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::lt_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API lt__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lt_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/mH_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/mH_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c7920a7e54ca41c26c57db3209673f7d704dab40 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/mH_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 mH { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mH") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mH(Tensor(a) self) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..052723b0529d9f204b4949358525bec3b14fd70e --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_native.h @@ -0,0 +1,26 @@ +#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_max_pool2d_with_indices_backward_out_cpu : public at::meta::structured_max_pool2d_with_indices_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, const at::Tensor & grad_input); +}; +struct TORCH_API structured_max_pool2d_with_indices_backward_out_cuda : public at::meta::structured_max_pool2d_with_indices_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/mean_meta_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/mean_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1e4e7f57b5913a376d7fa89e447a7d22300fbe1c --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/mean_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 mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & mean_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e279b15f6ab6d7d5b66987c1cf5e6077edb0ba2e --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_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 nanmean { + using schema = at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, 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::nanmean") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nanmean(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype); +}; + +struct TORCH_API nanmean_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, ::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::nanmean") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nanmean.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_dropout_backward_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_dropout_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ce2d3a437d3aaa6cce2d0ecb836620be0e531ebf --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_dropout_backward_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 & native_dropout_backward_out(const at::Tensor & grad_output, const at::Tensor & mask, double scale, at::Tensor & out); +TORCH_API at::Tensor native_dropout_backward(const at::Tensor & grad_output, const at::Tensor & mask, double scale); +TORCH_API at::Tensor native_dropout_backward_cuda(const at::Tensor & grad_output, const at::Tensor & mask, double scale); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_dropout_backward_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_dropout_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c9cfb3cc5c074eed5468ea60f3243f86fae77788 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_dropout_backward_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 native_dropout_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::native_dropout_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "native_dropout_backward(Tensor grad_output, Tensor mask, float scale) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & mask, double scale); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & mask, double scale); +}; + +struct TORCH_API native_dropout_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, 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::native_dropout_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "native_dropout_backward.out(Tensor grad_output, Tensor mask, float scale, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & mask, double scale, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & mask, double scale, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_group_norm_backward_compositeexplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_group_norm_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..be0a05ba245c101bcb73e1f9de12c96b2d11c053 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_group_norm_backward_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 ::std::tuple native_group_norm_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, int64_t N, int64_t C, int64_t HxW, int64_t group, ::std::array output_mask); +TORCH_API ::std::tuple native_group_norm_backward_outf(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, int64_t N, int64_t C, int64_t HxW, int64_t group, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple native_group_norm_backward_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, ::std::array output_mask); +TORCH_API ::std::tuple native_group_norm_backward_symint_outf(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_group_norm_compositeexplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_group_norm_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..63b7fd1cef531088104763f3789e140932d3b9be --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/native_group_norm_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API ::std::tuple native_group_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps); +TORCH_API ::std::tuple native_group_norm_symint(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps); +TORCH_API ::std::tuple native_group_norm_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps); +TORCH_API ::std::tuple native_group_norm_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple native_group_norm_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps); +TORCH_API ::std::tuple native_group_norm_symint_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/new_empty_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/new_empty_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0cb922b3f44b7e19b62630cc4c821f82810ed2f2 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/new_empty_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 new_empty_symint(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & new_empty_out_symint(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/q_per_channel_scales_compositeexplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/q_per_channel_scales_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f460708a4d7ca77f65855ad4d665f27c4ea15167 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/q_per_channel_scales_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API at::Tensor & q_per_channel_scales_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & q_per_channel_scales_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/randn_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/randn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3cffc5d3e669918fe4297d9e89a8c04bac852e28 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/randn_ops.h @@ -0,0 +1,105 @@ +#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 randn { + using schema = at::Tensor (c10::SymIntArrayRef, ::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::randn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randn_generator { + using schema = at::Tensor (c10::SymIntArrayRef, ::std::optional, ::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::randn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randn_names { + using schema = at::Tensor (c10::SymIntArrayRef, ::std::optional, ::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::randn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "names") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymIntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randn_generator_with_names { + using schema = at::Tensor (c10::SymIntArrayRef, ::std::optional, ::std::optional, ::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::randn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator_with_names") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API randn_out { + using schema = at::Tensor & (c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::randn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymIntArrayRef size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, at::Tensor & out); +}; + +struct TORCH_API randn_generator_out { + using schema = at::Tensor & (c10::SymIntArrayRef, ::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::randn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API randn_names_out { + using schema = at::Tensor & (c10::SymIntArrayRef, ::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::randn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "names_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymIntArrayRef size, ::std::optional names, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional names, at::Tensor & out); +}; + +struct TORCH_API randn_generator_with_names_out { + using schema = at::Tensor & (c10::SymIntArrayRef, ::std::optional, ::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::randn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator_with_names_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/renorm_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/renorm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f5a4b6fa7cfe4b79767c5c603841799abd572ac8 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/renorm_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 renorm_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, int64_t, 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::renorm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "renorm.out(Tensor self, Scalar p, int dim, Scalar maxnorm, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm, at::Tensor & out); +}; + +struct TORCH_API renorm { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, int64_t, 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::renorm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "renorm(Tensor self, Scalar p, int dim, Scalar maxnorm) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm); +}; + +struct TORCH_API renorm_ { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &, int64_t, 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::renorm_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "renorm_(Tensor(a!) self, Scalar p, int dim, Scalar maxnorm) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_backward.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..4cf3f3b298706c10730a46214011e03c22abc59c --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_backward.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::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); +} +namespace symint { + template ::value>> + at::Tensor & replication_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); + } +} + +// aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); +} +namespace symint { + template ::value>> + at::Tensor & replication_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, c10::fromIntArrayRefSlow(padding), grad_input); + } +} + +// aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, padding, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & replication_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, padding, grad_input); + } +} + +// aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & replication_pad1d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, padding, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & replication_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { + return at::_ops::replication_pad1d_backward_grad_input::call(grad_output, self, padding, grad_input); + } +} + +// aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor +inline at::Tensor replication_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad1d_backward::call(grad_output, self, c10::fromIntArrayRefSlow(padding)); +} +namespace symint { + template ::value>> + at::Tensor replication_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad1d_backward::call(grad_output, self, c10::fromIntArrayRefSlow(padding)); + } +} + +// aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor +inline at::Tensor replication_pad1d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad1d_backward::call(grad_output, self, padding); +} +namespace symint { + template ::value>> + at::Tensor replication_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad1d_backward::call(grad_output, self, padding); + } +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/reshape_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/reshape_native.h new file mode 100644 index 0000000000000000000000000000000000000000..82e656663843a3c1b3de4ab363de5d1027503388 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/reshape_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 reshape_symint(const at::Tensor & self, c10::SymIntArrayRef shape); +TORCH_API at::Tensor reshape_nested_symint(const at::Tensor & self, c10::SymIntArrayRef shape); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/rot90_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/rot90_native.h new file mode 100644 index 0000000000000000000000000000000000000000..66d9d7eb6dbb62781a97c8d378ce8468126d86c9 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/rot90_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 rot90(const at::Tensor & self, int64_t k=1, at::IntArrayRef dims={0,1}); +TORCH_API at::Tensor & rot90_out(const at::Tensor & self, int64_t k, at::IntArrayRef dims, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/row_stack_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/row_stack_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d1940b0a2b3158925e6d632fcb64073009f65d7c --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/row_stack_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 row_stack(at::TensorList tensors); +TORCH_API at::Tensor & row_stack_out(at::TensorList tensors, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/rsqrt_meta.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/rsqrt_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cf91ed832b3a82af8b4a636ba56df72122563792 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/rsqrt_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_rsqrt : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/rsub_compositeexplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/rsub_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8f8be274c37f43d23a995b285ce2607c2273c498 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/rsub_compositeexplicitautograd_dispatch.h @@ -0,0 +1,27 @@ +#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 & rsub_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & rsub_outf(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor rsub(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & rsub_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & rsub_outf(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_compositeexplicitautogradnonfunctional_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c380004c13e6ab26e01caea07ffd2214528af014 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_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 special_chebyshev_polynomial_t(const at::Tensor & x, const at::Tensor & n); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma.h new file mode 100644 index 0000000000000000000000000000000000000000..c4c2bad856134692c93fc0e10e8693ef82aaf924 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma.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::special_digamma(Tensor self) -> Tensor +inline at::Tensor special_digamma(const at::Tensor & self) { + return at::_ops::special_digamma::call(self); +} + +// aten::special_digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_digamma_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_digamma_out::call(self, out); +} +// aten::special_digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_digamma_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_digamma_out::call(self, out); +} + +} diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_erf_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_erf_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c24de7dd216da2c483a8bb819b02f16da2b91fbf --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_erf_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 special_erf(const at::Tensor & self); +TORCH_API at::Tensor & special_erf_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_log_softmax_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_log_softmax_native.h new file mode 100644 index 0000000000000000000000000000000000000000..87e1626cfcac6836dbec1b7c4bccc3b61724b3c8 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/special_log_softmax_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 special_log_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/sqrt_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/sqrt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7be1ba026f21fcd83b33a73e364ec3692408636b --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/sqrt_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 sqrt { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sqrt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sqrt(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API sqrt_ { + using schema = 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::sqrt_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sqrt_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API sqrt_out { + using schema = at::Tensor & (const 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::sqrt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/tensordot_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/tensordot_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..023a1dec6beb2dd53e6e66af495a7247f7fe89ae --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/tensordot_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 tensordot { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::tensordot") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "tensordot(Tensor self, Tensor other, int[] dims_self, int[] dims_other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other); +}; + +struct TORCH_API tensordot_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::tensordot") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "tensordot.out(Tensor self, Tensor other, int[] dims_self, int[] dims_other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0ede026e9553cd66daa88b1d6fc57d0f8375f250 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_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 ::std::vector unbind(const at::Tensor & self, int64_t dim=0); +TORCH_API ::std::vector NestedTensor_unbind(const at::Tensor & self, int64_t dim=0); +TORCH_API ::std::vector unbind(const at::Tensor & self, at::Dimname dim); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_native.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_native.h new file mode 100644 index 0000000000000000000000000000000000000000..788911841b79beeb919586941d98ce0260789494 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_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 ::std::vector unsafe_chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0); +} // namespace native +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeexplicitautogradnonfunctional_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1ffe7c05d8f72f36d0dba85a34c664ee42a2e3d6 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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 upsample_bicubic2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_bicubic2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeimplicitautograd_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c554723846bfe5e9321d68bc3e16297445a291f8 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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 upsample_bilinear2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); +TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cba02f4ef660188d87be3c9e1e0b851db31af365 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_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 upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor upsample_linear1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_complex_copy_ops.h b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_complex_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..088221e2616642108d76586756bd716f68bb1c86 --- /dev/null +++ b/mantis_evalkit/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_complex_copy_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 view_as_complex_copy { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::view_as_complex_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "view_as_complex_copy(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API view_as_complex_copy_out { + using schema = at::Tensor & (const 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::view_as_complex_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops