diff --git a/.gitattributes b/.gitattributes index f42a27912befd60ec3d96f2188909cacba28a059..c18e1fc33cd4dff3a670cfe43dc33cd825f579c7 100644 --- a/.gitattributes +++ b/.gitattributes @@ -179,3 +179,5 @@ lib/python3.10/site-packages/babel/locale-data/lt.dat filter=lfs diff=lfs merge= lib/python3.10/site-packages/babel/locale-data/lb.dat filter=lfs diff=lfs merge=lfs -text lib/python3.10/site-packages/babel/locale-data/am.dat filter=lfs diff=lfs merge=lfs -text lib/python3.10/site-packages/babel/locale-data/yue_Hans.dat filter=lfs diff=lfs merge=lfs -text +lib/python3.10/site-packages/babel/locale-data/da.dat filter=lfs diff=lfs merge=lfs -text +lib/python3.10/site-packages/babel/locale-data/de.dat filter=lfs diff=lfs merge=lfs -text diff --git a/lib/python3.10/site-packages/babel/locale-data/da.dat b/lib/python3.10/site-packages/babel/locale-data/da.dat new file mode 100644 index 0000000000000000000000000000000000000000..cd659eb34b3a928682a6fa63fbefe13bda6c7caa --- /dev/null +++ b/lib/python3.10/site-packages/babel/locale-data/da.dat @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5545713658e2b9bbe3ddefcf86299e30b05566502dd464f66c07e7c98bbaef51 +size 171756 diff --git a/lib/python3.10/site-packages/babel/locale-data/de.dat b/lib/python3.10/site-packages/babel/locale-data/de.dat new file mode 100644 index 0000000000000000000000000000000000000000..a44a3a1a7a73b8054040612b3bc4163c464027fd --- /dev/null +++ b/lib/python3.10/site-packages/babel/locale-data/de.dat @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:97a001560db35cf5fd5acf60dbe59ebded394b8ea28b48676ee095892ea6b660 +size 178630 diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward_cpu_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..387a8e8cb37fb586967283c5c25abb1cce196369 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward_cpu_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 cpu { + +TORCH_API at::Tensor _cdist_forward(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesce_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesce_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80a25a656974f695a117618e57a4f1af8242aa4a --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesce_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 _coalesce { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_coalesce"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_coalesce(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 _coalesce_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 const char* name = "aten::_coalesce"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_coalesce.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/lib/python3.10/site-packages/torch/include/ATen/ops/_convert_indices_from_csr_to_coo_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_convert_indices_from_csr_to_coo_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aea44eb401030c72612c72c5685d06ff4448d26c --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_convert_indices_from_csr_to_coo_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 _convert_indices_from_csr_to_coo(const at::Tensor & crow_indices, const at::Tensor & col_indices, bool out_int32=false, bool transpose=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c9777ba08c6b58118fedd264c721656db753d8f4 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_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 _cslt_sparse_mm_search { + using schema = int64_t (const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, ::std::optional, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cslt_sparse_mm_search"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cslt_sparse_mm_search(Tensor compressed_A, Tensor dense_B, Tensor? bias=None, Tensor? alpha=None, ScalarType? out_dtype=None, bool transpose_result=False) -> int"; + static int64_t call(const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias, const ::std::optional & alpha, ::std::optional out_dtype, bool transpose_result); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias, const ::std::optional & alpha, ::std::optional out_dtype, bool transpose_result); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_meta_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..158c62e49306875f9294eaf125066593b8c02336 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_efficientzerotensor_meta_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 meta { + +TORCH_API at::Tensor _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace meta +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h new file mode 100644 index 0000000000000000000000000000000000000000..75c2ef2590f5af7a01e04aaf9057d4a56b231d95 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_affine_quantized.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::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory, scale, zero_point, memory_format); +} +namespace symint { + template >> + at::Tensor _empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory, scale, zero_point, memory_format); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized_symint(c10::SymIntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template >> + at::Tensor _empty_affine_quantized(c10::SymIntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(size, dtype, layout, device, pin_memory, scale, zero_point, memory_format); +} +namespace symint { + template >> + at::Tensor _empty_affine_quantized(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(size, dtype, layout, device, pin_memory, scale, zero_point, memory_format); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_outf(at::IntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_affine_quantized_outf(at::IntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_symint_out(at::Tensor & out, c10::SymIntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_affine_quantized_out(at::Tensor & out, c10::SymIntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_symint_outf(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); +} +namespace symint { + template >> + at::Tensor & _empty_affine_quantized_outf(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); + } +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..65ddcff310c5838c0ae908b471e4cbbbbaffb868 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_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 _empty_per_channel_affine_quantized { + using schema = at::Tensor (c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, int64_t, ::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 const char* name = "aten::_empty_per_channel_affine_quantized"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_empty_per_channel_affine_quantized(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor"; + static at::Tensor call(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +}; + +struct TORCH_API _empty_per_channel_affine_quantized_out { + using schema = at::Tensor & (c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, int64_t, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_empty_per_channel_affine_quantized"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_empty_per_channel_affine_quantized.out(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7b82288d3309966ba842d96ffc33c3c69de0df17 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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 _fake_quantize_learnable_per_channel_affine_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, int64_t, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fake_quantize_learnable_per_channel_affine_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fake_quantize_learnable_per_channel_affine_backward(Tensor grad, Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_cuda_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7f38bcbca12f570f7fbfe04179eb3ef57d75782f --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_cuda_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 cuda { + +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4b8da4688b73398675676179e26de258fddbb84a --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_clamp_min_native.h @@ -0,0 +1,35 @@ +#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_clamp_min_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_min_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_clamp_min_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_min_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_clamp_min_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_clamp_min_list_kernel_slow(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_min_List_out(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void foreach_tensor_clamp_min_list_kernel_slow_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_min_list_kernel_cuda(at::TensorList self, at::TensorList other); +TORCH_API void foreach_tensor_clamp_min_list_kernel_cuda_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_clamp_min_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_min_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_clamp_min_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_clamp_min_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_clamp_min_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_cuda_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e88579040af34e53524b8c83a5f698841f8e4054 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erfc_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_erfc(at::TensorList self); +TORCH_API void _foreach_erfc_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_masked_softmax_compositeexplicitautograd_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_masked_softmax_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bb1ff99fb31cb0e310624141dd7115c617fd305 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_masked_softmax_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 & _masked_softmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, ::std::optional dim=::std::nullopt, ::std::optional mask_type=::std::nullopt); +TORCH_API at::Tensor & _masked_softmax_outf(const at::Tensor & self, const at::Tensor & mask, ::std::optional dim, ::std::optional mask_type, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..47b6623644e4d2558342707f6388c6835814f4a4 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_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 _nnpack_spatial_convolution(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride=1); +TORCH_API at::Tensor & _nnpack_spatial_convolution_out_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_slow_conv2d_backward_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_slow_conv2d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7851f9fb467b83461abbc4f06e95fcbb0c5dfbdd --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_slow_conv2d_backward_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::tuple slow_conv2d_backward_out_cpu(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias); +TORCH_API ::std::tuple slow_conv2d_backward_out_cuda(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias); +TORCH_API ::std::tuple _slow_conv2d_backward_output_mask_out_symint(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple slow_conv2d_backward_cpu(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, ::std::array output_mask); +TORCH_API ::std::tuple slow_conv2d_backward_cuda(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, ::std::array output_mask); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_backward_data.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_backward_data.h new file mode 100644 index 0000000000000000000000000000000000000000..ea9f9340dd0a60733d062ee871b71d1ed1f44ddb --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_backward_data.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::_softmax_backward_data(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype) -> Tensor +inline at::Tensor _softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype) { + return at::_ops::_softmax_backward_data::call(grad_output, output, dim, input_dtype); +} + +// aten::_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _softmax_backward_data_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype) { + return at::_ops::_softmax_backward_data_out::call(grad_output, output, dim, input_dtype, grad_input); +} +// aten::_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, at::Tensor & grad_input) { + return at::_ops::_softmax_backward_data_out::call(grad_output, output, dim, input_dtype, grad_input); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm.h new file mode 100644 index 0000000000000000000000000000000000000000..e825a080a64d4127541dcf51e590b7218545e00c --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_semi_structured_addmm(Tensor input, Tensor mat1, Tensor mat1_meta, Tensor mat2, *, Scalar alpha=1, Scalar beta=1, ScalarType? out_dtype=None) -> Tensor +inline at::Tensor _sparse_semi_structured_addmm(const at::Tensor & input, const at::Tensor & mat1, const at::Tensor & mat1_meta, const at::Tensor & mat2, const at::Scalar & alpha=1, const at::Scalar & beta=1, ::std::optional out_dtype=::std::nullopt) { + return at::_ops::_sparse_semi_structured_addmm::call(input, mat1, mat1_meta, mat2, alpha, beta, out_dtype); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_unique_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_unique_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a85e9f6228e72c145573059ea367cf4408abbe0d --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_unique_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::tuple _unique_out(const at::Tensor & self, bool sorted, bool return_inverse, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple _unique_cpu(const at::Tensor & self, bool sorted=true, bool return_inverse=false); +TORCH_API ::std::tuple _unique_cuda(const at::Tensor & self, bool sorted=true, bool return_inverse=false); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_meta_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..660435a04a499f03aee7b9e9e6f78fff4704eab8 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_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_bicubic2d_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_bicubic2d_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_bicubic2d_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_bicubic2d_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_bicubic2d_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_bicubic2d_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/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bc988555d4df387f3c54e96f577e88c87f38ac0 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_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 adaptive_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_cuda_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d2464ca09e1416b25cd3beec54c4533c7d3451d5 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor adaptive_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/addr.h b/lib/python3.10/site-packages/torch/include/ATen/ops/addr.h new file mode 100644 index 0000000000000000000000000000000000000000..35bb9d2bc3cf87116081ad9366c0a7264b2637e6 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/addr.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::addr(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1) -> Tensor +inline at::Tensor addr(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::addr::call(self, vec1, vec2, beta, alpha); +} + +// aten::addr.out(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & addr_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::addr_out::call(self, vec1, vec2, beta, alpha, out); +} +// aten::addr.out(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & addr_outf(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { + return at::_ops::addr_out::call(self, vec1, vec2, beta, alpha, out); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/amin_cuda_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/amin_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4fa55718355377e7d15a2f762de3c9b6968d9cf7 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/amin_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor amin(const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); +TORCH_API at::Tensor & amin_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); +TORCH_API at::Tensor & amin_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/atan.h b/lib/python3.10/site-packages/torch/include/ATen/ops/atan.h new file mode 100644 index 0000000000000000000000000000000000000000..2af744ea516f39d0917ef39cbe2841095d6002a7 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/atan.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::atan(Tensor self) -> Tensor +inline at::Tensor atan(const at::Tensor & self) { + return at::_ops::atan::call(self); +} + +// aten::atan_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & atan_(at::Tensor & self) { + return at::_ops::atan_::call(self); +} + +// aten::atan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atan_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::atan_out::call(self, out); +} +// aten::atan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atan_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::atan_out::call(self, out); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_elemt.h b/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_elemt.h new file mode 100644 index 0000000000000000000000000000000000000000..cf56886fd447b413adf1bac09d67e75c6a24bff2 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_elemt.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::batch_norm_elemt(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps) -> Tensor +inline at::Tensor batch_norm_elemt(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps) { + return at::_ops::batch_norm_elemt::call(input, weight, bias, mean, invstd, eps); +} + +// aten::batch_norm_elemt.out(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & batch_norm_elemt_out(at::Tensor & out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps) { + return at::_ops::batch_norm_elemt_out::call(input, weight, bias, mean, invstd, eps, out); +} +// aten::batch_norm_elemt.out(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & batch_norm_elemt_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps, at::Tensor & out) { + return at::_ops::batch_norm_elemt_out::call(input, weight, bias, mean, invstd, eps, out); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/blackman_window_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/blackman_window_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d4ad0fa31d7c4af251daccd989728d7254abb4d6 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/blackman_window_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor blackman_window(int64_t window_length, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & blackman_window_out(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor blackman_window(int64_t window_length, bool periodic, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & blackman_window_periodic_out(int64_t window_length, bool periodic, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/bmm.h b/lib/python3.10/site-packages/torch/include/ATen/ops/bmm.h new file mode 100644 index 0000000000000000000000000000000000000000..6dfc9612702cacdfef410cf0aedc90809051f482 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/bmm.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::bmm(Tensor self, Tensor mat2) -> Tensor +inline at::Tensor bmm(const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::bmm::call(self, mat2); +} + +// aten::bmm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::bmm_out::call(self, mat2, out); +} +// aten::bmm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bmm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out) { + return at::_ops::bmm_out::call(self, mat2, out); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/broadcast_tensors_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/broadcast_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d14102e8c615187f0229a94b537ac37bdf020189 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/broadcast_tensors_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API broadcast_tensors { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::broadcast_tensors"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "broadcast_tensors(Tensor[] tensors) -> Tensor[]"; + static ::std::vector call(at::TensorList tensors); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/ccol_indices_copy_compositeexplicitautograd_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/ccol_indices_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..639cbb5e134beb0826719fec7932496c7d5af524 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/ccol_indices_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 & ccol_indices_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & ccol_indices_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/channel_shuffle.h b/lib/python3.10/site-packages/torch/include/ATen/ops/channel_shuffle.h new file mode 100644 index 0000000000000000000000000000000000000000..233ad23ee208b6f20d1c8e2f5efd459bd480980d --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/channel_shuffle.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::channel_shuffle(Tensor self, SymInt groups) -> Tensor +inline at::Tensor channel_shuffle(const at::Tensor & self, int64_t groups) { + return at::_ops::channel_shuffle::call(self, groups); +} +namespace symint { + template >> + at::Tensor channel_shuffle(const at::Tensor & self, int64_t groups) { + return at::_ops::channel_shuffle::call(self, groups); + } +} + +// aten::channel_shuffle(Tensor self, SymInt groups) -> Tensor +inline at::Tensor channel_shuffle_symint(const at::Tensor & self, c10::SymInt groups) { + return at::_ops::channel_shuffle::call(self, groups); +} +namespace symint { + template >> + at::Tensor channel_shuffle(const at::Tensor & self, c10::SymInt groups) { + return at::_ops::channel_shuffle::call(self, groups); + } +} + +// aten::channel_shuffle.out(Tensor self, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & channel_shuffle_out(at::Tensor & out, const at::Tensor & self, int64_t groups) { + return at::_ops::channel_shuffle_out::call(self, groups, out); +} +namespace symint { + template >> + at::Tensor & channel_shuffle_out(at::Tensor & out, const at::Tensor & self, int64_t groups) { + return at::_ops::channel_shuffle_out::call(self, groups, out); + } +} + +// aten::channel_shuffle.out(Tensor self, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & channel_shuffle_outf(const at::Tensor & self, int64_t groups, at::Tensor & out) { + return at::_ops::channel_shuffle_out::call(self, groups, out); +} +namespace symint { + template >> + at::Tensor & channel_shuffle_outf(const at::Tensor & self, int64_t groups, at::Tensor & out) { + return at::_ops::channel_shuffle_out::call(self, groups, out); + } +} + +// aten::channel_shuffle.out(Tensor self, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & channel_shuffle_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt groups) { + return at::_ops::channel_shuffle_out::call(self, groups, out); +} +namespace symint { + template >> + at::Tensor & channel_shuffle_out(at::Tensor & out, const at::Tensor & self, c10::SymInt groups) { + return at::_ops::channel_shuffle_out::call(self, groups, out); + } +} + +// aten::channel_shuffle.out(Tensor self, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & channel_shuffle_symint_outf(const at::Tensor & self, c10::SymInt groups, at::Tensor & out) { + return at::_ops::channel_shuffle_out::call(self, groups, out); +} +namespace symint { + template >> + at::Tensor & channel_shuffle_outf(const at::Tensor & self, c10::SymInt groups, at::Tensor & out) { + return at::_ops::channel_shuffle_out::call(self, groups, out); + } +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/clamp_meta.h b/lib/python3.10/site-packages/torch/include/ATen/ops/clamp_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..3bf885133ddeedd66312ecc1a542f51b4a3091da --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/clamp_meta.h @@ -0,0 +1,32 @@ +#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_clamp : public TensorIteratorBase { + + + void meta(const at::Tensor & self, at::OptionalScalarRef min, at::OptionalScalarRef max); +}; +struct TORCH_API structured_clamp_Tensor : public TensorIteratorBase { + + + void meta(const at::Tensor & self, at::OptionalTensorRef min, at::OptionalTensorRef max); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/complex_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/complex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4709deada6f71bc5fe1faef8164f66ff11e849b5 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/complex_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 complex(const at::Tensor & real, const at::Tensor & imag); +TORCH_API at::Tensor & complex_out(const at::Tensor & real, const at::Tensor & imag, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfftn_compositeimplicitautograd_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfftn_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fb298b2b45b243de9f1e6fb02f03d57b51143f22 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfftn_compositeimplicitautograd_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 compositeimplicitautograd { + +TORCH_API at::Tensor fft_hfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor fft_hfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API const at::Tensor & fft_hfftn_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API const at::Tensor & fft_hfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out); +TORCH_API const at::Tensor & fft_hfftn_symint_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API const at::Tensor & fft_hfftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/flipud_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/flipud_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e887daab391a3a1b4946f203502101379559ed33 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/flipud_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 flipud { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::flipud"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "flipud(Tensor self) -> Tensor"; + 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/lib/python3.10/site-packages/torch/include/ATen/ops/frobenius_norm.h b/lib/python3.10/site-packages/torch/include/ATen/ops/frobenius_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..655034eebc5761d1d9bff2ddbdadb82dd829a623 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/frobenius_norm.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::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor +inline at::Tensor frobenius_norm(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false) { + return at::_ops::frobenius_norm_dim::call(self, dim, keepdim); +} + +// aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & frobenius_norm_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false) { + return at::_ops::frobenius_norm_out::call(self, dim, keepdim, out); +} +// aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & frobenius_norm_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { + return at::_ops::frobenius_norm_out::call(self, dim, keepdim, out); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/glu_meta_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/glu_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dadf8681c1931693a99c1c95ef8be95981a724d5 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/glu_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 glu(const at::Tensor & self, int64_t dim=-1); +TORCH_API at::Tensor & glu_out(at::Tensor & out, const at::Tensor & self, int64_t dim=-1); +TORCH_API at::Tensor & glu_outf(const at::Tensor & self, int64_t dim, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward.h b/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..1b079531ac1bf3d8550743047e2d4e36d3bb07e4 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_3d_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::grid_sampler_3d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor) +inline ::std::tuple grid_sampler_3d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask) { + return at::_ops::grid_sampler_3d_backward::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask); +} + +// aten::grid_sampler_3d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple grid_sampler_3d_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask) { + return at::_ops::grid_sampler_3d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1); +} +// aten::grid_sampler_3d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple grid_sampler_3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::grid_sampler_3d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/histogramdd_compositeimplicitautograd_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/histogramdd_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0557c7ab3977d764c45f4bcee65472ac9969101b --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/histogramdd_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple> histogramdd(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple> histogramdd(const at::Tensor & self, int64_t bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple> histogramdd(const at::Tensor & self, at::TensorList bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/imag_compositeimplicitautograd_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/imag_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3ed78d4b3036eda7306082c445c405e7b846461a --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/imag_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 imag(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/is_leaf_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/is_leaf_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fe540d99ddb30049061435630867619755bf6a21 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/is_leaf_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_leaf(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky.h b/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky.h new file mode 100644 index 0000000000000000000000000000000000000000..980a1214670c303be32d9b30bd7f52477f15e7e0 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky.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::linalg_cholesky(Tensor self, *, bool upper=False) -> Tensor +inline at::Tensor linalg_cholesky(const at::Tensor & self, bool upper=false) { + return at::_ops::linalg_cholesky::call(self, upper); +} + +// aten::linalg_cholesky.out(Tensor self, *, bool upper=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cholesky_out(at::Tensor & out, const at::Tensor & self, bool upper=false) { + return at::_ops::linalg_cholesky_out::call(self, upper, out); +} +// aten::linalg_cholesky.out(Tensor self, *, bool upper=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cholesky_outf(const at::Tensor & self, bool upper, at::Tensor & out) { + return at::_ops::linalg_cholesky_out::call(self, upper, out); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_diagonal_compositeimplicitautograd_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_diagonal_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..76359b305432ecaa7e027b8dad0ad15b0aa61194 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_diagonal_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 linalg_diagonal(const at::Tensor & A, int64_t offset=0, int64_t dim1=-2, int64_t dim2=-1); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_factor_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_factor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a9d4c00ddfc2bab89c3bd0caf0b727f9857034e7 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_factor_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 ::std::tuple linalg_ldl_factor(const at::Tensor & self, bool hermitian=false); +TORCH_API ::std::tuple linalg_ldl_factor_out(const at::Tensor & self, bool hermitian, at::Tensor & LD, at::Tensor & pivots); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_solve_ex.h b/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_solve_ex.h new file mode 100644 index 0000000000000000000000000000000000000000..239a5b8f5f6d9b3b68b7d262c5728b82728c85ef --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_solve_ex.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::linalg_solve_ex(Tensor A, Tensor B, *, bool left=True, bool check_errors=False) -> (Tensor result, Tensor info) +inline ::std::tuple linalg_solve_ex(const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false) { + return at::_ops::linalg_solve_ex::call(A, B, left, check_errors); +} + +// aten::linalg_solve_ex.out(Tensor A, Tensor B, *, bool left=True, bool check_errors=False, Tensor(a!) result, Tensor(b!) info) -> (Tensor(a!) result, Tensor(b!) info) +inline ::std::tuple linalg_solve_ex_out(at::Tensor & result, at::Tensor & info, const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false) { + return at::_ops::linalg_solve_ex_out::call(A, B, left, check_errors, result, info); +} +// aten::linalg_solve_ex.out(Tensor A, Tensor B, *, bool left=True, bool check_errors=False, Tensor(a!) result, Tensor(b!) info) -> (Tensor(a!) result, Tensor(b!) info) +inline ::std::tuple linalg_solve_ex_outf(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, at::Tensor & result, at::Tensor & info) { + return at::_ops::linalg_solve_ex_out::call(A, B, left, check_errors, result, info); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ecf57adf7a6ee88ce14dbb2909a5b6a4d2db8a8 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/log2_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 log2(const at::Tensor & self); +TORCH_API at::Tensor & log2_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & log2_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & log2_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/mH_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/mH_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f4f269f761c2958968692799612e774d937a5236 --- /dev/null +++ b/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 const char* name = "aten::mH"; + static constexpr const char* overload_name = ""; + static constexpr const char* 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/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d.h b/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d.h new file mode 100644 index 0000000000000000000000000000000000000000..1e141b810572483c96b7390d0644c89008a9edce --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d.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::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor +inline at::Tensor mkldnn_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::mkldnn_max_pool3d::call(self, kernel_size, stride, padding, dilation, ceil_mode); +} + +// aten::mkldnn_max_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_max_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::mkldnn_max_pool3d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} +// aten::mkldnn_max_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out) { + return at::_ops::mkldnn_max_pool3d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..780cef22d8a893fbddc59ba98278afd7d9db45ae --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_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 compositeimplicitautograd { + +TORCH_API at::Tensor narrow(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, int64_t length); +TORCH_API at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7bb2ec0e46bd8a918454306952f85352293fbde7 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_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 narrow_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor narrow_nested_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor narrow_tensor_symint(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/neg_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/neg_native.h new file mode 100644 index 0000000000000000000000000000000000000000..832e14f803673162a2050ace0c8caf13c24a3671 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/neg_native.h @@ -0,0 +1,31 @@ +#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_neg_out : public at::meta::structured_neg { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_neg(const at::Tensor & self); +TORCH_API at::Tensor & NestedTensor_neg_(at::Tensor & self); +TORCH_API at::Tensor neg_sparse(const at::Tensor & self); +TORCH_API at::Tensor & neg_out_sparse(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & neg_sparse_(at::Tensor & self); +TORCH_API at::Tensor neg_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & neg_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & neg_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_forward_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b6ccb1a656042c840fe0c216b1ab49dcd44ab650 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_forward_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_nll_loss_forward_out_cpu : public at::meta::structured_nll_loss_forward { +void impl(const at::Tensor & self, const at::Tensor & target, at::OptionalTensorRef weight, int64_t reduction, int64_t ignore_index, const at::Tensor & output, const at::Tensor & total_weight); +}; +struct TORCH_API structured_nll_loss_forward_out_cuda : public at::meta::structured_nll_loss_forward { +void impl(const at::Tensor & self, const at::Tensor & target, at::OptionalTensorRef weight, int64_t reduction, int64_t ignore_index, const at::Tensor & output, const at::Tensor & total_weight); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_nd_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_nd_native.h new file mode 100644 index 0000000000000000000000000000000000000000..eab10f0a87f07799947ecd12abdc5ffc14abb7e8 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_nd_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 nll_loss_nd_symint(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean, c10::SymInt ignore_index=-100); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_gru_cell_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_gru_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f21bf5affbb1d009cec2fb90a4e869ff3e9cb590 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_gru_cell_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 quantized_gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2331e8a2bceb170871d04d62de1b21aca7cbb76b --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell_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 quantized_rnn_tanh_cell { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::quantized_rnn_tanh_cell"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "quantized_rnn_tanh_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor b_ih, Tensor b_hh, Tensor packed_ih, Tensor packed_hh, Tensor col_offsets_ih, Tensor col_offsets_hh, Scalar scale_ih, Scalar scale_hh, Scalar zero_point_ih, Scalar zero_point_hh) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/refine_names_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/refine_names_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c871989879c7030486a3b6935a3f435d45460294 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/refine_names_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 refine_names(const at::Tensor & self, at::DimnameList names); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/repeat_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/repeat_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3fa706538c859232d15d95d34ef35e33a4507e37 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/repeat_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 repeat(const at::Tensor & self, at::IntArrayRef repeats); +TORCH_API at::Tensor & repeat_out_symint(const at::Tensor & self, c10::SymIntArrayRef repeats, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/resize_as_sparse_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/resize_as_sparse_native.h new file mode 100644 index 0000000000000000000000000000000000000000..15237dd3d6290f342184548e7b1c73eeec67e421 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/resize_as_sparse_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor resize_as_sparse(const at::Tensor & self, const at::Tensor & the_template); +TORCH_API const at::Tensor & resize_as_sparse_out(const at::Tensor & self, const at::Tensor & the_template, const at::Tensor & out); +TORCH_API const at::Tensor & resize_as_sparse_(const at::Tensor & self, const at::Tensor & the_template); +TORCH_API const at::Tensor & resize_as_sparse_compressed_(const at::Tensor & self, const at::Tensor & the_template); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/set.h b/lib/python3.10/site-packages/torch/include/ATen/ops/set.h new file mode 100644 index 0000000000000000000000000000000000000000..67ae799adf237276f33f9efc361e474f670a7b40 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/set.h @@ -0,0 +1,161 @@ +#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 { + + +namespace symint { + template >> + at::Tensor & set_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}) { + return at::_ops::set__source_Storage_storage_offset::call(self, source, storage_offset, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride)); + } +} + +namespace symint { + template >> + at::Tensor & set_(at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}) { + return at::_ops::set__source_Storage_storage_offset::call(self, source, storage_offset, size, stride); + } +} + +namespace symint { + template >> + at::Tensor & set_(at::Tensor & self, const at::Tensor & source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}) { + return at::_ops::set__source_Tensor_storage_offset::call(self, source, storage_offset, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride)); + } +} + +namespace symint { + template >> + at::Tensor & set_(at::Tensor & self, const at::Tensor & source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}) { + return at::_ops::set__source_Tensor_storage_offset::call(self, source, storage_offset, size, stride); + } +} + +// aten::set.source_Storage_out(Tensor self, Storage source, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_out(at::Tensor & out, const at::Tensor & self, at::Storage source) { + return at::_ops::set_source_Storage_out::call(self, source, out); +} +// aten::set.source_Storage_out(Tensor self, Storage source, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_outf(const at::Tensor & self, at::Storage source, at::Tensor & out) { + return at::_ops::set_source_Storage_out::call(self, source, out); +} + +// aten::set.source_Storage(Tensor self, Storage source) -> Tensor +inline at::Tensor set(const at::Tensor & self, at::Storage source) { + return at::_ops::set_source_Storage::call(self, source); +} + +// aten::set.source_Storage_storage_offset_out(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[], *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_out(at::Tensor & out, const at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}) { + return at::_ops::set_source_Storage_storage_offset_out::call(self, source, storage_offset, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template >> + at::Tensor & set_out(at::Tensor & out, const at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}) { + return at::_ops::set_source_Storage_storage_offset_out::call(self, source, storage_offset, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::set.source_Storage_storage_offset_out(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[], *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_outf(const at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::set_source_Storage_storage_offset_out::call(self, source, storage_offset, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template >> + at::Tensor & set_outf(const at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::set_source_Storage_storage_offset_out::call(self, source, storage_offset, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::set.source_Storage_storage_offset_out(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[], *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_symint_out(at::Tensor & out, const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}) { + return at::_ops::set_source_Storage_storage_offset_out::call(self, source, storage_offset, size, stride, out); +} +namespace symint { + template >> + at::Tensor & set_out(at::Tensor & out, const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}) { + return at::_ops::set_source_Storage_storage_offset_out::call(self, source, storage_offset, size, stride, out); + } +} + +// aten::set.source_Storage_storage_offset_out(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[], *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_symint_outf(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::set_source_Storage_storage_offset_out::call(self, source, storage_offset, size, stride, out); +} +namespace symint { + template >> + at::Tensor & set_outf(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::set_source_Storage_storage_offset_out::call(self, source, storage_offset, size, stride, out); + } +} + +// aten::set.source_Storage_storage_offset(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor +inline at::Tensor set(const at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}) { + return at::_ops::set_source_Storage_storage_offset::call(self, source, storage_offset, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride)); +} +namespace symint { + template >> + at::Tensor set(const at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}) { + return at::_ops::set_source_Storage_storage_offset::call(self, source, storage_offset, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride)); + } +} + +// aten::set.source_Storage_storage_offset(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor +inline at::Tensor set_symint(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}) { + return at::_ops::set_source_Storage_storage_offset::call(self, source, storage_offset, size, stride); +} +namespace symint { + template >> + at::Tensor set(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}) { + return at::_ops::set_source_Storage_storage_offset::call(self, source, storage_offset, size, stride); + } +} + +// aten::set.source_Tensor_out(Tensor self, Tensor source, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & source) { + return at::_ops::set_source_Tensor_out::call(self, source, out); +} +// aten::set.source_Tensor_out(Tensor self, Tensor source, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_outf(const at::Tensor & self, const at::Tensor & source, at::Tensor & out) { + return at::_ops::set_source_Tensor_out::call(self, source, out); +} + +// aten::set.source_Tensor(Tensor self, Tensor source) -> Tensor +inline at::Tensor set(const at::Tensor & self, const at::Tensor & source) { + return at::_ops::set_source_Tensor::call(self, source); +} + +// aten::set.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::set_out::call(self, out); +} +// aten::set.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & set_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::set_out::call(self, out); +} + +// aten::set(Tensor self) -> Tensor +inline at::Tensor set(const at::Tensor & self) { + return at::_ops::set::call(self); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/set_cuda_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/set_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb7daf678380c9f3efa3a3c1e3b7b938fbbf2e2d --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/set_cuda_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 cuda { + +TORCH_API at::Tensor & set_(at::Tensor & self, at::Storage source); +TORCH_API at::Tensor & set_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor & set__symint(at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor & set_(at::Tensor & self, const at::Tensor & source); +TORCH_API at::Tensor & set_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/sinh_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/sinh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..023577cb69bbe1c962addcad04632b479432e579 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/sinh_native.h @@ -0,0 +1,29 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_sinh_out : public at::meta::structured_sinh { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor sinh_sparse(const at::Tensor & self); +TORCH_API at::Tensor & sinh_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinh_sparse_(at::Tensor & self); +TORCH_API at::Tensor sinh_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & sinh_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinh_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/size_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b3983b69b2f890613bfd40aac1c750185aa4166d --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/size_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 size_int { + using schema = int64_t (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::size"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "size.int(Tensor self, int dim) -> int"; + static int64_t call(const at::Tensor & self, int64_t dim); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +struct TORCH_API size_Dimname { + using schema = int64_t (const at::Tensor &, at::Dimname); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::size"; + static constexpr const char* overload_name = "Dimname"; + static constexpr const char* schema_str = "size.Dimname(Tensor self, Dimname dim) -> int"; + static int64_t call(const at::Tensor & self, at::Dimname dim); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_resize_meta_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_resize_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fbdaa39b990e2d4aecadda81a29656cb32032394 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_resize_meta_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API const at::Tensor & sparse_resize_(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); + +} // namespace meta +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/special_gammaincc_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/special_gammaincc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..964573c907f0cd1d7b8f022606e5c66fb7efb8d6 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/special_gammaincc_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 special_gammaincc_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 const char* name = "aten::special_gammaincc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_gammaincc.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 special_gammaincc { + 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 const char* name = "aten::special_gammaincc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_gammaincc(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); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_cuda_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e40ed94c353a457eedcfcc5cc2b77ecc87cfbf19 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_scaled_modified_bessel_k1(const at::Tensor & x); +TORCH_API at::Tensor & special_scaled_modified_bessel_k1_out(at::Tensor & out, const at::Tensor & x); +TORCH_API at::Tensor & special_scaled_modified_bessel_k1_outf(const at::Tensor & x, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/sub_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/sub_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f4cefe3391ab62e6b83f937fcccfb90e421ad9f5 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/sub_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sub_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sub"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "sub.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +}; + +struct TORCH_API sub_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sub"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "sub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sub_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "sub_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sub"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "sub.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sub_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "sub_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sub"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "sub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/take_along_dim.h b/lib/python3.10/site-packages/torch/include/ATen/ops/take_along_dim.h new file mode 100644 index 0000000000000000000000000000000000000000..1d1437349dfb4f16bfde9db4578dc13ccd363d9a --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/take_along_dim.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::take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & take_along_dim_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, ::std::optional dim=::std::nullopt) { + return at::_ops::take_along_dim_out::call(self, indices, dim, out); +} +// aten::take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & take_along_dim_outf(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim, at::Tensor & out) { + return at::_ops::take_along_dim_out::call(self, indices, dim, out); +} + +// aten::take_along_dim(Tensor self, Tensor indices, int? dim=None) -> Tensor +inline at::Tensor take_along_dim(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim=::std::nullopt) { + return at::_ops::take_along_dim::call(self, indices, dim); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/take_along_dim_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/take_along_dim_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..622a9474fa4da394944a61600bcb0b17a9f67350 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/take_along_dim_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 take_along_dim_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::take_along_dim"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, ::std::optional dim, at::Tensor & out); +}; + +struct TORCH_API take_along_dim { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::take_along_dim"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "take_along_dim(Tensor self, Tensor indices, int? dim=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & indices, ::std::optional dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, ::std::optional dim); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/tensor_split_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/tensor_split_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9e1c56e7cecd7bd27c857e8dd71e24dd1e1f9db3 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/tensor_split_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 tensor_split_sections { + using schema = ::std::vector (const at::Tensor &, c10::SymInt, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::tensor_split"; + static constexpr const char* overload_name = "sections"; + static constexpr const char* schema_str = "tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[]"; + static ::std::vector call(const at::Tensor & self, c10::SymInt sections, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt sections, int64_t dim); +}; + +struct TORCH_API tensor_split_indices { + using schema = ::std::vector (const at::Tensor &, c10::SymIntArrayRef, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::tensor_split"; + static constexpr const char* overload_name = "indices"; + static constexpr const char* schema_str = "tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[]"; + static ::std::vector call(const at::Tensor & self, c10::SymIntArrayRef indices, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef indices, int64_t dim); +}; + +struct TORCH_API tensor_split_tensor_indices_or_sections { + using schema = ::std::vector (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::tensor_split"; + static constexpr const char* overload_name = "tensor_indices_or_sections"; + static constexpr const char* schema_str = "tensor_split.tensor_indices_or_sections(Tensor(a -> *) self, Tensor tensor_indices_or_sections, int dim=0) -> Tensor(a)[]"; + static ::std::vector call(const at::Tensor & self, const at::Tensor & tensor_indices_or_sections, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor_indices_or_sections, int64_t dim); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/to_ops.h b/lib/python3.10/site-packages/torch/include/ATen/ops/to_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8022f194f6f1d49f523f5134ee61b5e2d8bdc12c --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/to_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 to_dtype_layout { + using schema = at::Tensor (const at::Tensor &, ::std::optional, ::std::optional, ::std::optional, ::std::optional, bool, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to"; + static constexpr const char* overload_name = "dtype_layout"; + static constexpr const char* schema_str = "to.dtype_layout(Tensor(a) self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, bool non_blocking=False, bool copy=False, MemoryFormat? memory_format=None) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, bool non_blocking, bool copy, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, bool non_blocking, bool copy, ::std::optional memory_format); +}; + +struct TORCH_API to_device { + using schema = at::Tensor (const at::Tensor &, at::Device, at::ScalarType, bool, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to"; + static constexpr const char* overload_name = "device"; + static constexpr const char* schema_str = "to.device(Tensor(a) self, Device device, ScalarType dtype, bool non_blocking=False, bool copy=False, MemoryFormat? memory_format=None) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::Device device, at::ScalarType dtype, bool non_blocking, bool copy, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Device device, at::ScalarType dtype, bool non_blocking, bool copy, ::std::optional memory_format); +}; + +struct TORCH_API to_dtype { + using schema = at::Tensor (const at::Tensor &, at::ScalarType, bool, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to"; + static constexpr const char* overload_name = "dtype"; + static constexpr const char* schema_str = "to.dtype(Tensor(a) self, ScalarType dtype, bool non_blocking=False, bool copy=False, MemoryFormat? memory_format=None) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::ScalarType dtype, bool non_blocking, bool copy, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ScalarType dtype, bool non_blocking, bool copy, ::std::optional memory_format); +}; + +struct TORCH_API to_other { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::to"; + static constexpr const char* overload_name = "other"; + static constexpr const char* schema_str = "to.other(Tensor(a) self, Tensor other, bool non_blocking=False, bool copy=False, MemoryFormat? memory_format=None) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, bool non_blocking, bool copy, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, bool non_blocking, bool copy, ::std::optional memory_format); +}; + +}} // namespace at::_ops diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..484d95c32872e5d10ead57b5aea9ed548c53c272 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/topk_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 ::std::tuple topk(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true); +TORCH_API ::std::tuple topk_symint(const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true); +TORCH_API ::std::tuple topk_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true); +TORCH_API ::std::tuple topk_outf(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple topk_symint_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true); +TORCH_API ::std::tuple topk_symint_outf(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices); + +} // namespace meta +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/trace.h b/lib/python3.10/site-packages/torch/include/ATen/ops/trace.h new file mode 100644 index 0000000000000000000000000000000000000000..07ba52f86ead41ea07032dc0968b1cf649e30f36 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/trace.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::trace(Tensor self) -> Tensor +inline at::Tensor trace(const at::Tensor & self) { + return at::_ops::trace::call(self); +} + +// aten::trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & trace_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::trace_out::call(self, out); +} +// aten::trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & trace_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::trace_out::call(self, out); +} + +} diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_cpu_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aedc8efc7e51b841a7ed0630efd72e353da1e0e4 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_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 at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f2d831295d7ca7babdc51a8b918284605b832410 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor uniform(const at::Tensor & self, double from=0, double to=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & uniform_out(const at::Tensor & self, double from, double to, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & uniform_(at::Tensor & self, double from=0, double to=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & uniform_meta_(at::Tensor & self, double from=0, double to=1, ::std::optional generator=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/var_mean_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/var_mean_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cdd0a1da3a5964fe796589f33802fe810b711bce --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/var_mean_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 + + +namespace at { +namespace native { +TORCH_API ::std::tuple var_mean(const at::Tensor & self, bool unbiased=true); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased=true, bool keepdim=false); +TORCH_API ::std::tuple var_mean_correction_out(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::DimnameList dim, bool unbiased=true, bool keepdim=false); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_native.h b/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ef17f706383898f30d381b839b4a7a1e80fed378 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_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 & vdot_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor vdot(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor vdot_cuda(const at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at diff --git a/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_real_copy_compositeexplicitautograd_dispatch.h b/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_real_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9054bc9e2eeb9cbabe83cd443455ad272907d533 --- /dev/null +++ b/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_real_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 & view_as_real_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & view_as_real_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at