diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..85f0e0f71c0eabf5c60e970ed075cfa158c550e9 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 miopen_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor miopen_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..aa3d7e2b5e2692f011ec14ba05b7ef29e1dc30b3 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & miopen_convolution_out_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); +TORCH_API at::Tensor miopen_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bee78a94be892d967760dfcb280055fc93866e23 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API miopen_convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_convolution"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); +}; + +struct TORCH_API miopen_convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_convolution"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu.h new file mode 100644 index 0000000000000000000000000000000000000000..8c1a8f71d7b1255b2da451bc781b3ac841263106 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu.h @@ -0,0 +1,53 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::miopen_convolution_relu(Tensor self, Tensor weight, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor miopen_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::miopen_convolution_relu::call(self, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + at::Tensor miopen_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::miopen_convolution_relu::call(self, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::miopen_convolution_relu(Tensor self, Tensor weight, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor miopen_convolution_relu_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::miopen_convolution_relu::call(self, weight, bias, stride, padding, dilation, groups); +} +namespace symint { + template >> + at::Tensor miopen_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::miopen_convolution_relu::call(self, weight, bias, stride, padding, dilation, groups); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..94f966170d5e2838e6e5a330ceafce3bf72966b1 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 miopen_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups); +TORCH_API at::Tensor miopen_convolution_relu_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6f6d7c590799d5af144dbc65672043e3a991cdef --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 miopen_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..137eba207341a54439ca3cf1b18f603b1e339626 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_relu_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API miopen_convolution_relu { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_convolution_relu"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "miopen_convolution_relu(Tensor self, Tensor weight, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, SymInt groups) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose.h new file mode 100644 index 0000000000000000000000000000000000000000..0c86a51384622a3da3afd75cbae54291e89565fd --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline at::Tensor miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); +} +namespace symint { + template >> + at::Tensor miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); + } +} + +// aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline at::Tensor miopen_convolution_transpose_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic); +} +namespace symint { + template >> + at::Tensor miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic); + } +} + +// aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_convolution_transpose_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, out); + } +} + +// aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_convolution_transpose_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_convolution_transpose_out::call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a53658477cc7981f85304d42851ff415ba3e055e --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & miopen_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor & miopen_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out); +TORCH_API at::Tensor & miopen_convolution_transpose_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor & miopen_convolution_transpose_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bcb6922d76cfcdfffa50112f8ee81e8cd3cb3896 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor miopen_convolution_transpose_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_native.h new file mode 100644 index 0000000000000000000000000000000000000000..98e7ba311f90d16fa560fb8e4274e133f1c0d200 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & miopen_convolution_transpose_out_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); +TORCH_API at::Tensor miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..893f5ac384b17f4cf02c1de378b3e19e7ad096c6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API miopen_convolution_transpose { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_convolution_transpose"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); +}; + +struct TORCH_API miopen_convolution_transpose_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_convolution_transpose"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution.h new file mode 100644 index 0000000000000000000000000000000000000000..60679cc615dc7eaa9ca88d15272f1a139a339137 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); +} +namespace symint { + template >> + at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); + } +} + +// aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline at::Tensor miopen_depthwise_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic); +} +namespace symint { + template >> + at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic); + } +} + +// aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_depthwise_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_depthwise_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_depthwise_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_depthwise_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_depthwise_convolution_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_depthwise_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); + } +} + +// aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_depthwise_convolution_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_depthwise_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..795da9cadd603895994ce38466334d6dc93ef29a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & miopen_depthwise_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor & miopen_depthwise_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out); +TORCH_API at::Tensor & miopen_depthwise_convolution_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor & miopen_depthwise_convolution_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e5fec9e701c09c7d3f97b092081146c5798c6f46 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor miopen_depthwise_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3938591bfc106f4468e619e71b74de522f50d652 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & miopen_depthwise_convolution_out_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); +TORCH_API at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..988a20d28abd03a4ac514374b5018e5ee490325d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API miopen_depthwise_convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_depthwise_convolution"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); +}; + +struct TORCH_API miopen_depthwise_convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_depthwise_convolution"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn.h new file mode 100644 index 0000000000000000000000000000000000000000..d411127c5291c8831f76b6b7417683b114b3e568 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::miopen_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple miopen_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::miopen_rnn::call(input, weight, weight_stride0, hx, cx, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state); +} + +// aten::miopen_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple miopen_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state) { + return at::_ops::miopen_rnn_out::call(input, weight, weight_stride0, hx, cx, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); +} +// aten::miopen_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple miopen_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::miopen_rnn_out::call(input, weight, weight_stride0, hx, cx, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..bec7b6f6aadaf134805711ec8261ae42065e4c3a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::miopen_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[]) +inline ::std::tuple> miopen_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::miopen_rnn_backward::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); +} + +// aten::miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void miopen_rnn_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::miopen_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); +} +// aten::miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void miopen_rnn_backward_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3) { + return at::_ops::miopen_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0aaa3d21ee5c0f2e3019512d4bbea962e7d24a4a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void miopen_rnn_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +TORCH_API void miopen_rnn_backward_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fc509d4fa1427358e487add4b4babde7760688c8 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple> miopen_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..743e3c879acac00bb8e7acb8c7285027e91b2b66 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 void miopen_rnn_backward_out(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); +TORCH_API ::std::tuple> miopen_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..de51fd2e93a5c688ea8610947af1db66f1360596 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API miopen_rnn_backward { + using schema = ::std::tuple> (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const at::Tensor &, const ::std::optional &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, int64_t, int64_t, int64_t, bool, double, bool, bool, at::IntArrayRef, const ::std::optional &, const at::Tensor &, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_rnn_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "miopen_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[])"; + static ::std::tuple> call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); + static ::std::tuple> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +}; + +struct TORCH_API miopen_rnn_backward_out { + using schema = void (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const at::Tensor &, const ::std::optional &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, int64_t, int64_t, int64_t, bool, double, bool, bool, at::IntArrayRef, const ::std::optional &, const at::Tensor &, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_rnn_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> ()"; + static void call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f497b5b8ca41bc1d7a9d98df441092c025f50630 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple miopen_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +TORCH_API ::std::tuple miopen_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0667b8a763821ee8bb74f996b1161f4480c56b35 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple miopen_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..71905a19c7a936e8b436f8470cfd851bb32ddb90 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 miopen_rnn_out(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +TORCH_API ::std::tuple miopen_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5714fd52fcde4ba1cacd28dd4eae662fe5d43a66 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API miopen_rnn { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const ::std::optional &, int64_t, int64_t, int64_t, bool, double, bool, bool, at::IntArrayRef, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_rnn"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "miopen_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +}; + +struct TORCH_API miopen_rnn_out { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const at::Tensor &, const ::std::optional &, int64_t, int64_t, int64_t, bool, double, bool, bool, at::IntArrayRef, const ::std::optional &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::miopen_rnn"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "miopen_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!))"; + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish.h new file mode 100644 index 0000000000000000000000000000000000000000..488e00aadbd9189eae833ebfddaaf41afbe39cee --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mish(Tensor self) -> Tensor +inline at::Tensor mish(const at::Tensor & self) { + return at::_ops::mish::call(self); +} + +// aten::mish_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & mish_(at::Tensor & self) { + return at::_ops::mish_::call(self); +} + +// aten::mish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mish_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::mish_out::call(self, out); +} +// aten::mish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mish_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::mish_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..dda09adcc7bad582fc6d8ceb414542bfd42d2f72 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward.h @@ -0,0 +1,36 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mish_backward(Tensor grad_output, Tensor self) -> Tensor +inline at::Tensor mish_backward(const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::mish_backward::call(grad_output, self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0a5d456fbaf21dd9d6886907eb89985118b07377 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mish_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6170944efa5616743f739c2330127e992bf999ea --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mish_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..96afe166ed910887a73c1cd34b4f1d4217d92411 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mish_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0ed35c78d273e01fc25cc5619ca2bf6ce9a19df5 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 math_mish_backward(const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor mish_backward(const at::Tensor & grad_output, const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0f44f489103741f17f6354c08d1b31a591a08ab6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_backward_ops.h @@ -0,0 +1,34 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mish_backward { + 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::mish_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mish_backward(Tensor grad_output, Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_compositeexplicitautogradnonfunctional_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4492582613bca0927779c0d4b8e476466597e24b --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mish(const at::Tensor & self); +TORCH_API at::Tensor & mish_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8ea3ca88972b258358fc859c94d64edc6a7fc518 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mish(const at::Tensor & self); +TORCH_API at::Tensor & mish_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & mish_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & mish_(at::Tensor & self); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0a961b78be585cc360d4e2403dfd78fdaf20833f --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mish(const at::Tensor & self); +TORCH_API at::Tensor & mish_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & mish_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & mish_(at::Tensor & self); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_meta.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..be11c29134af79cafd808266d908673db8d7ed4a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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_mish : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_meta_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1fd884449af949c055df01bdb4e458cd34216b14 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mish(const at::Tensor & self); +TORCH_API at::Tensor & mish_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & mish_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & mish_(at::Tensor & self); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1f2562a791183aeeabbac5806694890f34b31f71 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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_mish_out : public at::meta::structured_mish { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c26b77d01d69f07483d02e01ac3312a380d1b4b2 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mish_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mish { + 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::mish"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mish(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 mish_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mish_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mish_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API mish_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::mish"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mish.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 + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d.h new file mode 100644 index 0000000000000000000000000000000000000000..02a8df770629398239a3b0d0b82f9b31aa981e11 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_adaptive_avg_pool2d(Tensor self, int[2] output_size) -> Tensor +inline at::Tensor mkldnn_adaptive_avg_pool2d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::mkldnn_adaptive_avg_pool2d::call(self, output_size); +} + +// aten::mkldnn_adaptive_avg_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_adaptive_avg_pool2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::mkldnn_adaptive_avg_pool2d_out::call(self, output_size, out); +} +// aten::mkldnn_adaptive_avg_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_adaptive_avg_pool2d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::mkldnn_adaptive_avg_pool2d_out::call(self, output_size, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..5d1bee44121dcccfdfb99f701c1a1f57a528b88b --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor +inline at::Tensor mkldnn_adaptive_avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::mkldnn_adaptive_avg_pool2d_backward::call(grad_output, self); +} + +// aten::mkldnn_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_adaptive_avg_pool2d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::mkldnn_adaptive_avg_pool2d_backward_out::call(grad_output, self, out); +} +// aten::mkldnn_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_adaptive_avg_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out) { + return at::_ops::mkldnn_adaptive_avg_pool2d_backward_out::call(grad_output, self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d7ba42fefca9f27c0cc229f827bc7fef805e5aa0 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_adaptive_avg_pool2d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & mkldnn_adaptive_avg_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..360904683ae3b981599885d2d1701e31bc26624d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_adaptive_avg_pool2d_backward_out(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor mkldnn_adaptive_avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3125938f98b5cca430916902a0e7f8fee69c2e26 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_adaptive_avg_pool2d_backward { + 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::mkldnn_adaptive_avg_pool2d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self); +}; + +struct TORCH_API mkldnn_adaptive_avg_pool2d_backward_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::mkldnn_adaptive_avg_pool2d_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..58750e047dca38dd5f9e49bd9b8c7e5f8cc22225 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mkldnn_adaptive_avg_pool2d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor & mkldnn_adaptive_avg_pool2d_out(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4b8399254b2f4ac51ae809f800672a90268a89a7 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_adaptive_avg_pool2d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_adaptive_avg_pool2d { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_adaptive_avg_pool2d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_adaptive_avg_pool2d(Tensor self, int[2] output_size) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef output_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size); +}; + +struct TORCH_API mkldnn_adaptive_avg_pool2d_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_adaptive_avg_pool2d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_adaptive_avg_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution.h new file mode 100644 index 0000000000000000000000000000000000000000..688ade492c4547f0e533df4c7c67fb965559267c --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor mkldnn_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::mkldnn_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template >> + at::Tensor mkldnn_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::mkldnn_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor mkldnn_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::mkldnn_convolution::call(self, weight, bias, padding, stride, dilation, groups); +} +namespace symint { + template >> + at::Tensor mkldnn_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::mkldnn_convolution::call(self, weight, bias, padding, stride, dilation, groups); + } +} + +// aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::mkldnn_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::mkldnn_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::mkldnn_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::mkldnn_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_convolution_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::mkldnn_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::mkldnn_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, out); + } +} + +// aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_convolution_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::mkldnn_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::mkldnn_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..08d88d462c2dff5e042e3681fb82e01c89ec9a08 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution_compositeexplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mkldnn_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups); +TORCH_API at::Tensor mkldnn_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); +TORCH_API at::Tensor & mkldnn_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups); +TORCH_API at::Tensor & mkldnn_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out); +TORCH_API at::Tensor & mkldnn_convolution_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); +TORCH_API at::Tensor & mkldnn_convolution_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d53a2f0c2740b2fbd08fe31e9b5d10583b0082f1 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mkldnn_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups); +TORCH_API at::Tensor & mkldnn_convolution_out_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6b88bf3234f54c58106495a3a96cb4a1c9e1b58d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_convolution_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_convolution"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +struct TORCH_API mkldnn_convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_convolution"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear.h new file mode 100644 index 0000000000000000000000000000000000000000..0b9df83849324ecadfb1a715d0db5acd812aa25b --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_linear(Tensor self, Tensor weight, Tensor? bias=None) -> Tensor +inline at::Tensor mkldnn_linear(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias={}) { + return at::_ops::mkldnn_linear::call(self, weight, bias); +} + +// aten::mkldnn_linear.out(Tensor self, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_linear_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias={}) { + return at::_ops::mkldnn_linear_out::call(self, weight, bias, out); +} +// aten::mkldnn_linear.out(Tensor self, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_linear_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::Tensor & out) { + return at::_ops::mkldnn_linear_out::call(self, weight, bias, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..9a39203a72e625a6c2100150b075d421a4bb2117 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_linear_backward(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple mkldnn_linear_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask) { + return at::_ops::mkldnn_linear_backward::call(self, grad_output, weight, output_mask); +} + +// aten::mkldnn_linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple mkldnn_linear_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask) { + return at::_ops::mkldnn_linear_backward_out::call(self, grad_output, weight, output_mask, out0, out1, out2); +} +// aten::mkldnn_linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple mkldnn_linear_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::mkldnn_linear_backward_out::call(self, grad_output, weight, output_mask, out0, out1, out2); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..43692a36a86148e10995afc829081f92b77daf17 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple mkldnn_linear_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask); +TORCH_API ::std::tuple mkldnn_linear_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input.h new file mode 100644 index 0000000000000000000000000000000000000000..1615eec302a1754d94da02d1925b6933070a0bcf --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_linear_backward_input(int[] input_size, Tensor grad_output, Tensor weight) -> Tensor +inline at::Tensor mkldnn_linear_backward_input(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight) { + return at::_ops::mkldnn_linear_backward_input::call(input_size, grad_output, weight); +} + +// aten::mkldnn_linear_backward_input.out(int[] input_size, Tensor grad_output, Tensor weight, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_linear_backward_input_out(at::Tensor & out, at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight) { + return at::_ops::mkldnn_linear_backward_input_out::call(input_size, grad_output, weight, out); +} +// aten::mkldnn_linear_backward_input.out(int[] input_size, Tensor grad_output, Tensor weight, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_linear_backward_input_outf(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight, at::Tensor & out) { + return at::_ops::mkldnn_linear_backward_input_out::call(input_size, grad_output, weight, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..269016db55201189a42b30f1a587042cf57a7c36 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_linear_backward_input_out(at::Tensor & out, at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight); +TORCH_API at::Tensor & mkldnn_linear_backward_input_outf(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_native.h new file mode 100644 index 0000000000000000000000000000000000000000..15c32557261103be1fbaf1264f6e496671486fc9 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_linear_backward_input_out(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight, at::Tensor & out); +TORCH_API at::Tensor mkldnn_linear_backward_input(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dd1a498a4d656d890fa693eccd226b4d191dc218 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_input_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_linear_backward_input { + using schema = at::Tensor (at::IntArrayRef, 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::mkldnn_linear_backward_input"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_linear_backward_input(int[] input_size, Tensor grad_output, Tensor weight) -> Tensor"; + static at::Tensor call(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight); +}; + +struct TORCH_API mkldnn_linear_backward_input_out { + using schema = at::Tensor & (at::IntArrayRef, 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::mkldnn_linear_backward_input"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_linear_backward_input.out(int[] input_size, Tensor grad_output, Tensor weight, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8ea87e99aab7de64f265d51c9e89ed45c0eb0424 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mkldnn_linear_backward_out(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple mkldnn_linear_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..300c4b9b288980e58a6b5fbb3ad4d107027b98bc --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_linear_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_linear_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_linear_backward(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask); +}; + +struct TORCH_API mkldnn_linear_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_linear_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights.h new file mode 100644 index 0000000000000000000000000000000000000000..ca183b58f8bee439911855a302823bbfea12c013 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_linear_backward_weights(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined) -> (Tensor, Tensor) +inline ::std::tuple mkldnn_linear_backward_weights(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined) { + return at::_ops::mkldnn_linear_backward_weights::call(grad_output, input, weight, bias_defined); +} + +// aten::mkldnn_linear_backward_weights.out(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple mkldnn_linear_backward_weights_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined) { + return at::_ops::mkldnn_linear_backward_weights_out::call(grad_output, input, weight, bias_defined, out0, out1); +} +// aten::mkldnn_linear_backward_weights.out(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple mkldnn_linear_backward_weights_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::mkldnn_linear_backward_weights_out::call(grad_output, input, weight, bias_defined, out0, out1); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a3bfff834f132f17a0eb9426c07226f5d378c6e0 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple mkldnn_linear_backward_weights_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined); +TORCH_API ::std::tuple mkldnn_linear_backward_weights_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_native.h new file mode 100644 index 0000000000000000000000000000000000000000..82da2f2a9952d37e9d3e4a3981b7e360a4645135 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mkldnn_linear_backward_weights_out(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple mkldnn_linear_backward_weights(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..03c3edd97883cd006e056170086004cd92f4e6d0 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_linear_backward_weights { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_linear_backward_weights"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_linear_backward_weights(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined); +}; + +struct TORCH_API mkldnn_linear_backward_weights_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_linear_backward_weights"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_linear_backward_weights.out(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..70703049873b969a065f99357038b97fa20e2833 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_linear_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias={}); +TORCH_API at::Tensor & mkldnn_linear_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_native.h new file mode 100644 index 0000000000000000000000000000000000000000..54be98ce0e107aa3855441263486286e3c22568a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_linear_out(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::Tensor & out); +TORCH_API at::Tensor mkldnn_linear(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias={}); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..830f05a33c6b9f2e85f1a6e4949e6bd6ef6ce0de --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_linear { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_linear"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_linear(Tensor self, Tensor weight, Tensor? bias=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias); +}; + +struct TORCH_API mkldnn_linear_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_linear"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_linear.out(Tensor self, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d.h new file mode 100644 index 0000000000000000000000000000000000000000..3ee800032fce67d78136224a1c4d922e14ddfa27 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor +inline at::Tensor mkldnn_max_pool2d(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_pool2d::call(self, kernel_size, stride, padding, dilation, ceil_mode); +} + +// aten::mkldnn_max_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_max_pool2d_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_pool2d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} +// aten::mkldnn_max_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_max_pool2d_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_pool2d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..9e9a52ce480ade8339bbfda728b433533097a703 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor +inline at::Tensor mkldnn_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::mkldnn_max_pool2d_backward::call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode); +} + +// aten::mkldnn_max_pool2d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_max_pool2d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::mkldnn_max_pool2d_backward_out::call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); +} +// aten::mkldnn_max_pool2d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out) { + return at::_ops::mkldnn_max_pool2d_backward_out::call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..87a7ef2f54f5abf1d74b4d185c700d5a3ada5d59 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_max_pool2d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +TORCH_API at::Tensor & mkldnn_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..55ba9a65851936d4fd7855811a69319256148996 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_max_pool2d_backward_out(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +TORCH_API at::Tensor mkldnn_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e4c54beddb7ed55558ce850267f3e3e993c18b08 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_max_pool2d_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool2d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +struct TORCH_API mkldnn_max_pool2d_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool2d_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_max_pool2d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..02db28ffabadc35bdf8248a9776237a87c6fbaf5 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_max_pool2d_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); +TORCH_API at::Tensor & mkldnn_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e77e795a1ada06ed4b9a94d4d3904f18d2c8474c --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_max_pool2d_out(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +TORCH_API at::Tensor mkldnn_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..63ae3c6a89bda783e0c0ce1635e08b084e98e5a9 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool2d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_max_pool2d { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool2d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +struct TORCH_API mkldnn_max_pool2d_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool2d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_max_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d.h new file mode 100644 index 0000000000000000000000000000000000000000..693ba1dd09628d4cfda3f1b46faa177abdd7dd24 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#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); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..18ac262369ad4ed789641b1662f12efa8e699c14 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_max_pool3d_backward(Tensor grad_output, Tensor output, Tensor input, 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_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, 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_backward::call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode); +} + +// aten::mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, 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_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, 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_backward_out::call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); +} +// aten::mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, 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_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, 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_backward_out::call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..91fa08b5632f8c67e338ae712a30832b221091f6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_max_pool3d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +TORCH_API at::Tensor & mkldnn_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..577df3f8f2992b65caaf8daf19fb14a49037c2ea --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_max_pool3d_backward_out(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +TORCH_API at::Tensor mkldnn_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..20f223a3dfeb8b3bb1b7565191176ee8b2bd2798 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_max_pool3d_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool3d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_max_pool3d_backward(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +struct TORCH_API mkldnn_max_pool3d_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool3d_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..55aeaaafe117e612ee33e7c50b272757208e9db5 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & 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); +TORCH_API 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); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5e7ca6ae78706d6ed4a3115c8beac5af98a05403 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_max_pool3d_out(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +TORCH_API 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); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..48332e7965b4983282411a1b7bfed3a228d89619 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_max_pool3d { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "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"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +struct TORCH_API mkldnn_max_pool3d_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool3d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "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!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..b89a389c74bc14787a0634b51319d2c919b9cc6e --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_reorder_conv2d_weight(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None) -> Tensor +inline at::Tensor mkldnn_reorder_conv2d_weight(const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv2d_weight::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt); +} +namespace symint { + template >> + at::Tensor mkldnn_reorder_conv2d_weight(const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv2d_weight::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt); + } +} + +// aten::mkldnn_reorder_conv2d_weight(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None) -> Tensor +inline at::Tensor mkldnn_reorder_conv2d_weight_symint(const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv2d_weight::call(self, padding, stride, dilation, groups, input_size); +} +namespace symint { + template >> + at::Tensor mkldnn_reorder_conv2d_weight(const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv2d_weight::call(self, padding, stride, dilation, groups, input_size); + } +} + +// aten::mkldnn_reorder_conv2d_weight.out(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_reorder_conv2d_weight_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv2d_weight_out::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_reorder_conv2d_weight_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv2d_weight_out::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt, out); + } +} + +// aten::mkldnn_reorder_conv2d_weight.out(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_reorder_conv2d_weight_outf(const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::OptionalIntArrayRef input_size, at::Tensor & out) { + return at::_ops::mkldnn_reorder_conv2d_weight_out::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_reorder_conv2d_weight_outf(const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::OptionalIntArrayRef input_size, at::Tensor & out) { + return at::_ops::mkldnn_reorder_conv2d_weight_out::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt, out); + } +} + +// aten::mkldnn_reorder_conv2d_weight.out(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_reorder_conv2d_weight_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv2d_weight_out::call(self, padding, stride, dilation, groups, input_size, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_reorder_conv2d_weight_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv2d_weight_out::call(self, padding, stride, dilation, groups, input_size, out); + } +} + +// aten::mkldnn_reorder_conv2d_weight.out(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_reorder_conv2d_weight_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out) { + return at::_ops::mkldnn_reorder_conv2d_weight_out::call(self, padding, stride, dilation, groups, input_size, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_reorder_conv2d_weight_outf(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out) { + return at::_ops::mkldnn_reorder_conv2d_weight_out::call(self, padding, stride, dilation, groups, input_size, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b8f7d2b3f7f7e7786992c065c292da43355e35cf --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_reorder_conv2d_weight_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt); +TORCH_API at::Tensor & mkldnn_reorder_conv2d_weight_outf(const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::OptionalIntArrayRef input_size, at::Tensor & out); +TORCH_API at::Tensor & mkldnn_reorder_conv2d_weight_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt); +TORCH_API at::Tensor & mkldnn_reorder_conv2d_weight_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bfea7df0f2c3d8004eeaea211782dcc5e1652e54 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_reorder_conv2d_weight_out_symint(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); +TORCH_API at::Tensor mkldnn_reorder_conv2d_weight(const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..79b58393ab7175c637ab3f22808e59d2edbd8c99 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv2d_weight_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_reorder_conv2d_weight { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::OptionalSymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_reorder_conv2d_weight"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_reorder_conv2d_weight(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size); +}; + +struct TORCH_API mkldnn_reorder_conv2d_weight_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::OptionalSymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_reorder_conv2d_weight"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_reorder_conv2d_weight.out(Tensor self, SymInt[2] padding=0, SymInt[2] stride=1, SymInt[2] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..a99274afc925dd73a67ed0a0cae58026f2fdc899 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_reorder_conv3d_weight(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None) -> Tensor +inline at::Tensor mkldnn_reorder_conv3d_weight(const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv3d_weight::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt); +} +namespace symint { + template >> + at::Tensor mkldnn_reorder_conv3d_weight(const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv3d_weight::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt); + } +} + +// aten::mkldnn_reorder_conv3d_weight(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None) -> Tensor +inline at::Tensor mkldnn_reorder_conv3d_weight_symint(const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv3d_weight::call(self, padding, stride, dilation, groups, input_size); +} +namespace symint { + template >> + at::Tensor mkldnn_reorder_conv3d_weight(const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv3d_weight::call(self, padding, stride, dilation, groups, input_size); + } +} + +// aten::mkldnn_reorder_conv3d_weight.out(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_reorder_conv3d_weight_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv3d_weight_out::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_reorder_conv3d_weight_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv3d_weight_out::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt, out); + } +} + +// aten::mkldnn_reorder_conv3d_weight.out(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_reorder_conv3d_weight_outf(const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::OptionalIntArrayRef input_size, at::Tensor & out) { + return at::_ops::mkldnn_reorder_conv3d_weight_out::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_reorder_conv3d_weight_outf(const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::OptionalIntArrayRef input_size, at::Tensor & out) { + return at::_ops::mkldnn_reorder_conv3d_weight_out::call(self, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, input_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*input_size)) : ::std::nullopt, out); + } +} + +// aten::mkldnn_reorder_conv3d_weight.out(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_reorder_conv3d_weight_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv3d_weight_out::call(self, padding, stride, dilation, groups, input_size, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_reorder_conv3d_weight_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt) { + return at::_ops::mkldnn_reorder_conv3d_weight_out::call(self, padding, stride, dilation, groups, input_size, out); + } +} + +// aten::mkldnn_reorder_conv3d_weight.out(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mkldnn_reorder_conv3d_weight_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out) { + return at::_ops::mkldnn_reorder_conv3d_weight_out::call(self, padding, stride, dilation, groups, input_size, out); +} +namespace symint { + template >> + at::Tensor & mkldnn_reorder_conv3d_weight_outf(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out) { + return at::_ops::mkldnn_reorder_conv3d_weight_out::call(self, padding, stride, dilation, groups, input_size, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ce5444b2d5452a6e756d8b712a7a7cfc09ba4853 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_reorder_conv3d_weight_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt); +TORCH_API at::Tensor & mkldnn_reorder_conv3d_weight_outf(const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::OptionalIntArrayRef input_size, at::Tensor & out); +TORCH_API at::Tensor & mkldnn_reorder_conv3d_weight_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1, at::OptionalSymIntArrayRef input_size=::std::nullopt); +TORCH_API at::Tensor & mkldnn_reorder_conv3d_weight_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5e10f311c4b101e842e990eae80eb89bdb0b917d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mkldnn_reorder_conv3d_weight_out_symint(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); +TORCH_API at::Tensor mkldnn_reorder_conv3d_weight(const at::Tensor & self, at::IntArrayRef padding=0, at::IntArrayRef stride=1, at::IntArrayRef dilation=1, int64_t groups=1, at::OptionalIntArrayRef input_size=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..490b4aebe5d36301afc8dee8c139ba764e691b6a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_reorder_conv3d_weight_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_reorder_conv3d_weight { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::OptionalSymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_reorder_conv3d_weight"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_reorder_conv3d_weight(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size); +}; + +struct TORCH_API mkldnn_reorder_conv3d_weight_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::OptionalSymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_reorder_conv3d_weight"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_reorder_conv3d_weight.out(Tensor self, SymInt[3] padding=0, SymInt[3] stride=1, SymInt[3] dilation=1, SymInt groups=1, SymInt[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::OptionalSymIntArrayRef input_size, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer.h new file mode 100644 index 0000000000000000000000000000000000000000..ecb2d540d1c030c6746fa8b71f2b4a5a17c78d16 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple mkldnn_rnn_layer(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) { + return at::_ops::mkldnn_rnn_layer::call(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); +} + +// aten::mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple mkldnn_rnn_layer_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) { + return at::_ops::mkldnn_rnn_layer_out::call(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train, out0, out1, out2, out3); +} +// aten::mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple mkldnn_rnn_layer_outf(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { + return at::_ops::mkldnn_rnn_layer_out::call(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train, out0, out1, out2, out3); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..feafd52a1e50d73c5c61b9d5c6d2c04f3419605a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_rnn_layer_backward(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple mkldnn_rnn_layer_backward(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace) { + return at::_ops::mkldnn_rnn_layer_backward::call(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace); +} + +// aten::mkldnn_rnn_layer_backward.out(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5, Tensor(g!) out6) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!)) +inline ::std::tuple mkldnn_rnn_layer_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6, const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace) { + return at::_ops::mkldnn_rnn_layer_backward_out::call(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace, out0, out1, out2, out3, out4, out5, out6); +} +// aten::mkldnn_rnn_layer_backward.out(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5, Tensor(g!) out6) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!)) +inline ::std::tuple mkldnn_rnn_layer_backward_outf(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6) { + return at::_ops::mkldnn_rnn_layer_backward_out::call(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace, out0, out1, out2, out3, out4, out5, out6); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0a260ef75e648b60e06cecf430c505145020cbb8 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple mkldnn_rnn_layer_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6, const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace); +TORCH_API ::std::tuple mkldnn_rnn_layer_backward_outf(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9aeb950a1f85e19e2c43dd704b65bbc74571683e --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 ::std::tuple mkldnn_rnn_layer_backward(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7ede1d4c708b777eb14d24c140cee895561a1086 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mkldnn_rnn_layer_backward_out(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6); +TORCH_API ::std::tuple mkldnn_rnn_layer_backward(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..45ad23606d18b737458fb80a5551a4cf8aae34aa --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_rnn_layer_backward { + using schema = ::std::tuple (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 ::std::optional &, const ::std::optional &, const ::std::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_rnn_layer_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_rnn_layer_backward(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace); +}; + +struct TORCH_API mkldnn_rnn_layer_backward_out { + using schema = ::std::tuple (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 ::std::optional &, const ::std::optional &, const ::std::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_rnn_layer_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_rnn_layer_backward.out(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5, Tensor(g!) out6) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!))"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a1c3a84ce44995fc51407f21bbec4db490110def --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple mkldnn_rnn_layer_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); +TORCH_API ::std::tuple mkldnn_rnn_layer_outf(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..af6fbc1496bbb98e3793648609bf906ca346abeb --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 ::std::tuple mkldnn_rnn_layer(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2bdf476ca68306eec522f19792fd67fd658cb77a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mkldnn_rnn_layer_out(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +TORCH_API ::std::tuple mkldnn_rnn_layer(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7effedfa59ce8f261d665cb7c7668a8db8de05d9 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mkldnn_rnn_layer { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_rnn_layer"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); +}; + +struct TORCH_API mkldnn_rnn_layer_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_rnn_layer"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm.h new file mode 100644 index 0000000000000000000000000000000000000000..7454f0d6d04e1da322db8368ee58d3062291d1c5 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mm(Tensor self, Tensor mat2) -> Tensor +inline at::Tensor mm(const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::mm::call(self, mat2); +} + +// aten::mm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::mm_out::call(self, mat2, out); +} +// aten::mm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out) { + return at::_ops::mm_out::call(self, mat2, out); +} + +// aten::mm.dtype(Tensor self, Tensor mat2, ScalarType out_dtype) -> Tensor +inline at::Tensor mm(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype) { + return at::_ops::mm_dtype::call(self, mat2, out_dtype); +} + +// aten::mm.dtype_out(Tensor self, Tensor mat2, ScalarType out_dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype) { + return at::_ops::mm_dtype_out::call(self, mat2, out_dtype, out); +} +// aten::mm.dtype_out(Tensor self, Tensor mat2, ScalarType out_dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out) { + return at::_ops::mm_dtype_out::call(self, mat2, out_dtype, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_compositeexplicitautogradnonfunctional_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d3f22da667c649c22f2d2469a53666c4df36663f --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mm(const at::Tensor & self, const at::Tensor & mat2); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6a157f36ff12025a5fff065548f84c11d588ae16 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aa484a8c2807542af1d168ed3b129440cfb9f722 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor mm(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); +TORCH_API at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); +TORCH_API at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_meta.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..056a3ee5f88e1237642785d85e977629d833ba75 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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_mm : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, const at::Tensor & mat2); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_meta_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f4ce90f439875bdd0d81665b2e944603b477b077 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1f864d3baea0792ac7a2b636b1a2f8c80835424a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_native.h @@ -0,0 +1,37 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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_mm_out_cpu : public at::meta::structured_mm { +void impl(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & out); +}; +struct TORCH_API structured_mm_out_cuda : public at::meta::structured_mm { +void impl(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & out); +}; +TORCH_API at::Tensor _sparse_mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _sparse_mm_out(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor _sparse_csr_mm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & _sparse_csr_mm_out(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +TORCH_API at::Tensor _mm_dtype_cuda(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); +TORCH_API at::Tensor & _mm_dtype_out_cuda(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..15dbd2b998da562d987abe092c6d80823a8cc164 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mm_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mm { + 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::mm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mm(Tensor self, Tensor mat2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2); +}; + +struct TORCH_API mm_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::mm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +}; + +struct TORCH_API mm_dtype { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mm"; + static constexpr const char* overload_name = "dtype"; + static constexpr const char* schema_str = "mm.dtype(Tensor self, Tensor mat2, ScalarType out_dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype); +}; + +struct TORCH_API mm_dtype_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mm"; + static constexpr const char* overload_name = "dtype_out"; + static constexpr const char* schema_str = "mm.dtype_out(Tensor self, Tensor mat2, ScalarType out_dtype, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::ScalarType out_dtype, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode.h new file mode 100644 index 0000000000000000000000000000000000000000..6e647a4c64a302d13358eca7bc7fc80e4e3abbb3 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false) { + return at::_ops::mode::call(self, dim, keepdim); +} + +// aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple mode_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim=-1, bool keepdim=false) { + return at::_ops::mode_values::call(self, dim, keepdim, values, indices); +} +// aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple mode_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::mode_values::call(self, dim, keepdim, values, indices); +} + +// aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple mode(const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::mode_dimname::call(self, dim, keepdim); +} + +// aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple mode_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::mode_dimname_out::call(self, dim, keepdim, values, indices); +} +// aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple mode_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::mode_dimname_out::call(self, dim, keepdim, values, indices); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..db2bb16b0209a025411b9f9545634b74e34d459f --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple mode_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim=-1, bool keepdim=false); +TORCH_API ::std::tuple mode_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7747614a9331d7ae96eff54f71406f561e3ec752 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mode(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple mode_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple mode_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9318abaaa1170606354fccd44b4f1384c3f8e5b1 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 ::std::tuple mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f7456dd2b16ca70de364ac102a53371b9b06ffd1 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_native.h new file mode 100644 index 0000000000000000000000000000000000000000..74169f11d519a492c2479553524d6f021415a3df --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mode_out(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false); +TORCH_API ::std::tuple mode(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple mode_out(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1a47cb43a92765af5e404736dd0ef3b1fd07c41a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mode_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mode { + using schema = ::std::tuple (const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mode"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices)"; + static ::std::tuple call(const at::Tensor & self, int64_t dim, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim); +}; + +struct TORCH_API mode_values { + using schema = ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mode"; + static constexpr const char* overload_name = "values"; + static constexpr const char* schema_str = "mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)"; + static ::std::tuple call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +}; + +struct TORCH_API mode_dimname { + using schema = ::std::tuple (const at::Tensor &, at::Dimname, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mode"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)"; + static ::std::tuple call(const at::Tensor & self, at::Dimname dim, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim); +}; + +struct TORCH_API mode_dimname_out { + using schema = ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mode"; + static constexpr const char* overload_name = "dimname_out"; + static constexpr const char* schema_str = "mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)"; + static ::std::tuple call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis.h new file mode 100644 index 0000000000000000000000000000000000000000..b5b06d803bb8541acae9ce8bb7114f3a3d6a649a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::moveaxis.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a) +inline at::Tensor moveaxis(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination) { + return at::_ops::moveaxis_intlist::call(self, source, destination); +} + +// aten::moveaxis.int(Tensor(a) self, int source, int destination) -> Tensor(a) +inline at::Tensor moveaxis(const at::Tensor & self, int64_t source, int64_t destination) { + return at::_ops::moveaxis_int::call(self, source, destination); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..39d5366ad61f8df25b505890d1added2d230a7cc --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 moveaxis(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); +TORCH_API at::Tensor moveaxis(const at::Tensor & self, int64_t source, int64_t destination); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ea51c3df31edf9fda82a013c2242a6dc185ebc4d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 moveaxis(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); +TORCH_API at::Tensor moveaxis(const at::Tensor & self, int64_t source, int64_t destination); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0d620442ca9e6797f63a0972e96f132d2209e475 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API moveaxis_intlist { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::moveaxis"; + static constexpr const char* overload_name = "intlist"; + static constexpr const char* schema_str = "moveaxis.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); +}; + +struct TORCH_API moveaxis_int { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::moveaxis"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "moveaxis.int(Tensor(a) self, int source, int destination) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t source, int64_t destination); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t source, int64_t destination); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim.h new file mode 100644 index 0000000000000000000000000000000000000000..225df56de6d4072982924a2d92b4c3d851aa818e --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim.h @@ -0,0 +1,41 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::movedim.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a) +inline at::Tensor movedim(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination) { + return at::_ops::movedim_intlist::call(self, source, destination); +} + +// aten::movedim.int(Tensor(a) self, int source, int destination) -> Tensor(a) +inline at::Tensor movedim(const at::Tensor & self, int64_t source, int64_t destination) { + return at::_ops::movedim_int::call(self, source, destination); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2aa4cec02bfbde390c98ca27eac256c5bb5dfc4d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 movedim(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); +TORCH_API at::Tensor movedim(const at::Tensor & self, int64_t source, int64_t destination); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a38afdbf1346bb4b061fe99d838509d08cd6be0d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 movedim(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); +TORCH_API at::Tensor movedim(const at::Tensor & self, int64_t source, int64_t destination); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3c8e01ba87c61d58bc26cdb5d54571965bdd36f5 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/movedim_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API movedim_intlist { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::movedim"; + static constexpr const char* overload_name = "intlist"; + static constexpr const char* schema_str = "movedim.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); +}; + +struct TORCH_API movedim_int { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::movedim"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "movedim.int(Tensor(a) self, int source, int destination) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t source, int64_t destination); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t source, int64_t destination); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..efe853603a519aae7974ef68cd3e25f4f747127a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mps_convolution_backward(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple mps_convolution_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask) { + return at::_ops::mps_convolution_backward::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask); +} +namespace symint { + template >> + ::std::tuple mps_convolution_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask) { + return at::_ops::mps_convolution_backward::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask); + } +} + +// aten::mps_convolution_backward(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple mps_convolution_backward_symint(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::mps_convolution_backward::call(self, grad_output, weight, padding, stride, dilation, groups, output_mask); +} +namespace symint { + template >> + ::std::tuple mps_convolution_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::mps_convolution_backward::call(self, grad_output, weight, padding, stride, dilation, groups, output_mask); + } +} + +// aten::mps_convolution_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple mps_convolution_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask) { + return at::_ops::mps_convolution_backward_out::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple mps_convolution_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask) { + return at::_ops::mps_convolution_backward_out::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask, out0, out1, out2); + } +} + +// aten::mps_convolution_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple mps_convolution_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::mps_convolution_backward_out::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple mps_convolution_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::mps_convolution_backward_out::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask, out0, out1, out2); + } +} + +// aten::mps_convolution_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple mps_convolution_backward_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::mps_convolution_backward_out::call(self, grad_output, weight, padding, stride, dilation, groups, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple mps_convolution_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::mps_convolution_backward_out::call(self, grad_output, weight, padding, stride, dilation, groups, output_mask, out0, out1, out2); + } +} + +// aten::mps_convolution_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple mps_convolution_backward_symint_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::mps_convolution_backward_out::call(self, grad_output, weight, padding, stride, dilation, groups, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple mps_convolution_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::mps_convolution_backward_out::call(self, grad_output, weight, padding, stride, dilation, groups, output_mask, out0, out1, out2); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c10510d0153f19bd7629bbf2db70737f3f8e985b --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple mps_convolution_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask); +TORCH_API ::std::tuple mps_convolution_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple mps_convolution_backward_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask); +TORCH_API ::std::tuple mps_convolution_backward_symint_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d80d3117cfdaf23eac8c9a3c71303b3904914545 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mps_convolution_backward_out_symint(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..73708f0367fd696ace228d684c46484965e4a881 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mps_convolution_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mps_convolution_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mps_convolution_backward(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask); +}; + +struct TORCH_API mps_convolution_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mps_convolution_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mps_convolution_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..8f381405549ffe7c87d8d919391bd4c7f9dadfb0 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mps_convolution_transpose_backward(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[2] output_mask) -> (Tensor, Tensor) +inline ::std::tuple mps_convolution_transpose_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask) { + return at::_ops::mps_convolution_transpose_backward::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask); +} +namespace symint { + template >> + ::std::tuple mps_convolution_transpose_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask) { + return at::_ops::mps_convolution_transpose_backward::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask); + } +} + +// aten::mps_convolution_transpose_backward(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[2] output_mask) -> (Tensor, Tensor) +inline ::std::tuple mps_convolution_transpose_backward_symint(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::mps_convolution_transpose_backward::call(self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask); +} +namespace symint { + template >> + ::std::tuple mps_convolution_transpose_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::mps_convolution_transpose_backward::call(self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask); + } +} + +// aten::mps_convolution_transpose_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple mps_convolution_transpose_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask) { + return at::_ops::mps_convolution_transpose_backward_out::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask, out0, out1); +} +namespace symint { + template >> + ::std::tuple mps_convolution_transpose_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask) { + return at::_ops::mps_convolution_transpose_backward_out::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask, out0, out1); + } +} + +// aten::mps_convolution_transpose_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple mps_convolution_transpose_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::mps_convolution_transpose_backward_out::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask, out0, out1); +} +namespace symint { + template >> + ::std::tuple mps_convolution_transpose_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::mps_convolution_transpose_backward_out::call(self, grad_output, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, output_mask, out0, out1); + } +} + +// aten::mps_convolution_transpose_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple mps_convolution_transpose_backward_symint_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::mps_convolution_transpose_backward_out::call(self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask, out0, out1); +} +namespace symint { + template >> + ::std::tuple mps_convolution_transpose_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::mps_convolution_transpose_backward_out::call(self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask, out0, out1); + } +} + +// aten::mps_convolution_transpose_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple mps_convolution_transpose_backward_symint_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::mps_convolution_transpose_backward_out::call(self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask, out0, out1); +} +namespace symint { + template >> + ::std::tuple mps_convolution_transpose_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::mps_convolution_transpose_backward_out::call(self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask, out0, out1); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b3050924da988526abc7236b2fb9cacf9ffc792c --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple mps_convolution_transpose_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask); +TORCH_API ::std::tuple mps_convolution_transpose_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple mps_convolution_transpose_backward_symint_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask); +TORCH_API ::std::tuple mps_convolution_transpose_backward_symint_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0f2860569a561e95875cdd8a62ac606b60514c8a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward_native.h @@ -0,0 +1,26 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mps_convolution_transpose_backward_out_symint(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..64179d97ac3a2b3d9d43791fd26574ab1a99d8c8 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mps_convolution_transpose_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mps_convolution_transpose_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mps_convolution_transpose_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mps_convolution_transpose_backward(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[2] output_mask) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask); +}; + +struct TORCH_API mps_convolution_transpose_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, ::std::array, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mps_convolution_transpose_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mps_convolution_transpose_backward.out(Tensor self, Tensor grad_output, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..6b8a5ccdaca5f653aafc446384d4b670c9aa1249 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mse_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mse_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean) { + return at::_ops::mse_loss_out::call(self, target, reduction, out); +} +// aten::mse_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mse_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out) { + return at::_ops::mse_loss_out::call(self, target, reduction, out); +} + +// aten::mse_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor +inline at::Tensor mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean) { + return at::_ops::mse_loss::call(self, target, reduction); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..836dd16d8f57ef8b5a78f98826a5bc0264eb69d0 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mse_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & mse_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { + return at::_ops::mse_loss_backward_grad_input::call(grad_output, self, target, reduction, grad_input); +} +// aten::mse_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & mse_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input) { + return at::_ops::mse_loss_backward_grad_input::call(grad_output, self, target, reduction, grad_input); +} + +// aten::mse_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor +inline at::Tensor mse_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { + return at::_ops::mse_loss_backward::call(grad_output, self, target, reduction); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4584bebc8d8ebf26a13517f8a623badb42bf9ae0 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mse_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API at::Tensor & mse_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API at::Tensor & mse_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f9856cf26e8a926b628df7fac2163d441b8d97e9 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mse_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API at::Tensor & mse_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API at::Tensor & mse_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..98974d69e234cd57a541975f362b3ce78a6e10c2 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mse_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API at::Tensor & mse_loss_backward_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..157a604c9105496abf64600c8520aba8b09aceb6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mse_loss_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mse_loss_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "mse_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); +}; + +struct TORCH_API mse_loss_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mse_loss_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mse_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_compositeexplicitautogradnonfunctional_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bbea2594c3138d3b1a4b22a98d9ae14c04529d59 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9ca90b822f06ef50c53bf657bae743ac0f923c89 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8ad9badc888d519161e1d25c4168278d7b25ec31 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_meta.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..d1ac11224ac580d337b8e356e2fdf8ca22390cb6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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_mse_loss : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & target, int64_t reduction); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_meta_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ba6277dc3fee943e6d3efc9ae6e862c0e6299fd8 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_meta_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c21f17eaee5c12646779c857df5137098ec8b6dc --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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_mse_loss_out : public at::meta::structured_mse_loss { +void impl(const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & out); +}; +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8fd3e3282629b466e2e57f4e430a393675f422cf --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mse_loss_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mse_loss"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mse_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); +}; + +struct TORCH_API mse_loss { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mse_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mse_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort.h new file mode 100644 index 0000000000000000000000000000000000000000..eace61d6dd1beee028495928932e3fa4be4dc3e6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::msort.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & msort_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::msort_out::call(self, out); +} +// aten::msort.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & msort_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::msort_out::call(self, out); +} + +// aten::msort(Tensor self) -> Tensor +inline at::Tensor msort(const at::Tensor & self) { + return at::_ops::msort::call(self); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8ac51a9dfd305d228b53642866b5b5ca39a70f11 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 msort(const at::Tensor & self); +TORCH_API at::Tensor & msort_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & msort_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9e1139bd9acad7d084e0ef8bf21d3ade91393c0d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 msort(const at::Tensor & self); +TORCH_API at::Tensor & msort_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b5102ac2548d9e8a1c1e8ab2e4e8d4d10c08d0d6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/msort_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API msort_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::msort"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "msort.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); +}; + +struct TORCH_API msort { + 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::msort"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "msort(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 + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul.h new file mode 100644 index 0000000000000000000000000000000000000000..ac9bc62896e25355a0d213c9980d0ed0baad960a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mul.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor mul(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::mul_Tensor::call(self, other); +} + +// aten::mul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::mul_out::call(self, other, out); +} +// aten::mul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::mul_out::call(self, other, out); +} + +// aten::mul.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor mul(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::mul_Scalar::call(self, other); +} + +// aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mul_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::mul_Scalar_out::call(self, other, out); +} +// aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mul_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::mul_Scalar_out::call(self, other, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..39bcc708671a34b5c60d2905ec4b43c07e9b7067 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_compositeexplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mul(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & mul_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & mul_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & mul_(at::Tensor & self, const at::Scalar & other); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_compositeexplicitautogradnonfunctional_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1b16ca6dac0728f480a218870aafb34ed205ee85 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4b4ee757e60ec639052293c168d7ce5c23180bb5 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_cpu_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mul_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d71f895cad118aafef71d4000485eae1656fdc71 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_cuda_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mul_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_meta.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..2971724d39035abe4547ab8721dfa3ee690db214 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_meta.h @@ -0,0 +1,32 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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_mul_Tensor : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_meta_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ad2bd16ab27e79c1a41e4868fc8260a4acd94282 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_meta_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mul_(at::Tensor & self, const at::Tensor & other); + +} // namespace meta +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d82c5a403c066e504b0ce51ceba223ef58092374 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_native.h @@ -0,0 +1,48 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_mul_out : public at::meta::structured_mul_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_mul_Tensor(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & NestedTensor_mul__Tensor(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor mul_sparse(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out_sparse_cpu(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mul_sparse_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out_sparse_cuda(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor mul_sparse_csr(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out_sparse_csr(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mul_sparse_csr_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor mkldnn_mul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mkldnn_mul_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mkldnn_mul_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor mul_zerotensor(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor mul(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & mul_Scalar_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & mul_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor NestedTensor_mul_Scalar(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & NestedTensor_mul__Scalar(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor mul_scalar_sparse_csr(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & mul__scalar_sparse_csr(at::Tensor & self, const at::Scalar & other); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..881ca1495c6cbae618af8d75f76a866ea668d4be --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mul_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mul_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "mul.Tensor(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API mul__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "mul_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API mul_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::mul"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mul.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 mul_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "mul.Scalar(Tensor self, Scalar other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API mul__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "mul_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API mul_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mul"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..266f7f1e257054b994d4bb2d95684cf0c7be16c7 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multi_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multi_margin_loss_out::call(self, target, p, margin, weight, reduction, out); +} +// aten::multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multi_margin_loss_outf(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out) { + return at::_ops::multi_margin_loss_out::call(self, target, p, margin, weight, reduction, out); +} + +// aten::multi_margin_loss(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean) -> Tensor +inline at::Tensor multi_margin_loss(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multi_margin_loss::call(self, target, p, margin, weight, reduction); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..c515146f92675968c4c6272bca87e267bfaf6b8f --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::multi_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & multi_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multi_margin_loss_backward_grad_input::call(grad_output, self, target, p, margin, weight, reduction, grad_input); +} +// aten::multi_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & multi_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input) { + return at::_ops::multi_margin_loss_backward_grad_input::call(grad_output, self, target, p, margin, weight, reduction, grad_input); +} + +// aten::multi_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean) -> Tensor +inline at::Tensor multi_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multi_margin_loss_backward::call(grad_output, self, target, p, margin, weight, reduction); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f8de779e2f3f204ed611e8d9625a39f0b8f6d77a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multi_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..692041f01a3efc40e9fc2f2412f73c08c2bab20c --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multi_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..91cf225143af27034a4347b4a47e9d7b564580f4 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multi_margin_loss_cpu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_cpu_backward_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); +TORCH_API at::Tensor multi_margin_loss_cuda_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_cuda_backward_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a600ab57c880e21d5fd5fed42b20fc7c6d672bdc --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API multi_margin_loss_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const ::std::optional &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multi_margin_loss_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "multi_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); +}; + +struct TORCH_API multi_margin_loss_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const ::std::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multi_margin_loss_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "multi_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..869b70582b327e1fb25ce2fda473148b1e79ddc3 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multi_margin_loss(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_outf(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f0bac3f431f456748ab6493e89358294a8e97245 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multi_margin_loss(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_outf(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ffe5dfce2f10924e5aef740f4beece18c9ce5990 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multi_margin_loss_cpu(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_cpu_out(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out); +TORCH_API at::Tensor multi_margin_loss_cuda(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_cuda_out(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..569dbe7a9092b4533a08e55777c29fb4855bb8e3 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API multi_margin_loss_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const ::std::optional &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multi_margin_loss"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & out); +}; + +struct TORCH_API multi_margin_loss { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const ::std::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multi_margin_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "multi_margin_loss(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..da742dc7361eb02bd1e4af802dd098e15df45439 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::multilabel_margin_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multilabel_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multilabel_margin_loss_out::call(self, target, reduction, out); +} +// aten::multilabel_margin_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multilabel_margin_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out) { + return at::_ops::multilabel_margin_loss_out::call(self, target, reduction, out); +} + +// aten::multilabel_margin_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor +inline at::Tensor multilabel_margin_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multilabel_margin_loss::call(self, target, reduction); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..2f17b3eb5501545d10314cd59f8df7765a253e76 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::multilabel_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & multilabel_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target) { + return at::_ops::multilabel_margin_loss_backward_grad_input::call(grad_output, self, target, reduction, is_target, grad_input); +} +// aten::multilabel_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & multilabel_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input) { + return at::_ops::multilabel_margin_loss_backward_grad_input::call(grad_output, self, target, reduction, is_target, grad_input); +} + +// aten::multilabel_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target) -> Tensor +inline at::Tensor multilabel_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target) { + return at::_ops::multilabel_margin_loss_backward::call(grad_output, self, target, reduction, is_target); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a69230573be1432b645a84633b568748d1b88c5 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multilabel_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a903e11f66b5159099f50633fb789810ef92d31c --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multilabel_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d7b529bfc429e671893cf43c8e2f905305b4299e --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multilabel_margin_loss_backward_cpu(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_cpu_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input); +TORCH_API at::Tensor multilabel_margin_loss_backward_cuda(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +TORCH_API at::Tensor & multilabel_margin_loss_backward_cuda_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f6b0f8b00312a37eafec43fa52e342217f522408 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API multilabel_margin_loss_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multilabel_margin_loss_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "multilabel_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input); +}; + +struct TORCH_API multilabel_margin_loss_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multilabel_margin_loss_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "multilabel_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f4f1cfa39b9d0afdd5bcf4dd96a6365ebfafd8e2 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multilabel_margin_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multilabel_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multilabel_margin_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..884eb169c97ab87165feeb01c38da32562316260 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::multilabel_margin_loss_forward.output(Tensor self, Tensor target, int reduction, *, Tensor(a!) output, Tensor(b!) is_target) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple multilabel_margin_loss_forward_out(at::Tensor & output, at::Tensor & is_target, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { + return at::_ops::multilabel_margin_loss_forward_output::call(self, target, reduction, output, is_target); +} +// aten::multilabel_margin_loss_forward.output(Tensor self, Tensor target, int reduction, *, Tensor(a!) output, Tensor(b!) is_target) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple multilabel_margin_loss_forward_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target) { + return at::_ops::multilabel_margin_loss_forward_output::call(self, target, reduction, output, is_target); +} + +// aten::multilabel_margin_loss_forward(Tensor self, Tensor target, int reduction) -> (Tensor output, Tensor is_target) +inline ::std::tuple multilabel_margin_loss_forward(const at::Tensor & self, const at::Tensor & target, int64_t reduction) { + return at::_ops::multilabel_margin_loss_forward::call(self, target, reduction); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c05f570d1b1559a92b5d752727eb4edf995515ca --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 ::std::tuple multilabel_margin_loss_forward(const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API ::std::tuple multilabel_margin_loss_forward_out(at::Tensor & output, at::Tensor & is_target, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API ::std::tuple multilabel_margin_loss_forward_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f8ea471e64993337958e3d2fe9bc89982b8084ad --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple multilabel_margin_loss_forward(const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API ::std::tuple multilabel_margin_loss_forward_out(at::Tensor & output, at::Tensor & is_target, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API ::std::tuple multilabel_margin_loss_forward_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4ff8510c59f20a52fb6f9629619dc41efe26d184 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multilabel_margin_loss_forward_cpu(const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API ::std::tuple multilabel_margin_loss_forward_out_cpu(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); +TORCH_API ::std::tuple multilabel_margin_loss_forward_cuda(const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API ::std::tuple multilabel_margin_loss_forward_out_cuda(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f078659e6e14f28d7b9891c78d386465d8ce1dc3 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API multilabel_margin_loss_forward_output { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multilabel_margin_loss_forward"; + static constexpr const char* overload_name = "output"; + static constexpr const char* schema_str = "multilabel_margin_loss_forward.output(Tensor self, Tensor target, int reduction, *, Tensor(a!) output, Tensor(b!) is_target) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); +}; + +struct TORCH_API multilabel_margin_loss_forward { + using schema = ::std::tuple (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::multilabel_margin_loss_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "multilabel_margin_loss_forward(Tensor self, Tensor target, int reduction) -> (Tensor output, Tensor is_target)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & target, int64_t reduction); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3c05671f8293de308be4b3305363f971d6a4000d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multilabel_margin_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multilabel_margin_loss_out(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6e37cc4124b51ef299d9d773a28c503f77d77f00 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API multilabel_margin_loss_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multilabel_margin_loss"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "multilabel_margin_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); +}; + +struct TORCH_API multilabel_margin_loss { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multilabel_margin_loss"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "multilabel_margin_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial.h new file mode 100644 index 0000000000000000000000000000000000000000..284e3847e820507edd42dc47a0e46458c6508607 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::multinomial.out(Tensor self, SymInt num_samples, bool replacement=False, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt) { + return at::_ops::multinomial_out::call(self, num_samples, replacement, generator, out); +} +namespace symint { + template >> + at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt) { + return at::_ops::multinomial_out::call(self, num_samples, replacement, generator, out); + } +} + +// aten::multinomial.out(Tensor self, SymInt num_samples, bool replacement=False, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multinomial_outf(const at::Tensor & self, int64_t num_samples, bool replacement, ::std::optional generator, at::Tensor & out) { + return at::_ops::multinomial_out::call(self, num_samples, replacement, generator, out); +} +namespace symint { + template >> + at::Tensor & multinomial_outf(const at::Tensor & self, int64_t num_samples, bool replacement, ::std::optional generator, at::Tensor & out) { + return at::_ops::multinomial_out::call(self, num_samples, replacement, generator, out); + } +} + +// aten::multinomial.out(Tensor self, SymInt num_samples, bool replacement=False, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multinomial_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt num_samples, bool replacement=false, ::std::optional generator=::std::nullopt) { + return at::_ops::multinomial_out::call(self, num_samples, replacement, generator, out); +} +namespace symint { + template >> + at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, c10::SymInt num_samples, bool replacement=false, ::std::optional generator=::std::nullopt) { + return at::_ops::multinomial_out::call(self, num_samples, replacement, generator, out); + } +} + +// aten::multinomial.out(Tensor self, SymInt num_samples, bool replacement=False, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multinomial_symint_outf(const at::Tensor & self, c10::SymInt num_samples, bool replacement, ::std::optional generator, at::Tensor & out) { + return at::_ops::multinomial_out::call(self, num_samples, replacement, generator, out); +} +namespace symint { + template >> + at::Tensor & multinomial_outf(const at::Tensor & self, c10::SymInt num_samples, bool replacement, ::std::optional generator, at::Tensor & out) { + return at::_ops::multinomial_out::call(self, num_samples, replacement, generator, out); + } +} + +// aten::multinomial(Tensor self, SymInt num_samples, bool replacement=False, *, Generator? generator=None) -> Tensor +inline at::Tensor multinomial(const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt) { + return at::_ops::multinomial::call(self, num_samples, replacement, generator); +} +namespace symint { + template >> + at::Tensor multinomial(const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt) { + return at::_ops::multinomial::call(self, num_samples, replacement, generator); + } +} + +// aten::multinomial(Tensor self, SymInt num_samples, bool replacement=False, *, Generator? generator=None) -> Tensor +inline at::Tensor multinomial_symint(const at::Tensor & self, c10::SymInt num_samples, bool replacement=false, ::std::optional generator=::std::nullopt) { + return at::_ops::multinomial::call(self, num_samples, replacement, generator); +} +namespace symint { + template >> + at::Tensor multinomial(const at::Tensor & self, c10::SymInt num_samples, bool replacement=false, ::std::optional generator=::std::nullopt) { + return at::_ops::multinomial::call(self, num_samples, replacement, generator); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..72a87fbd77e1209ce026d44394810c3ae3b71166 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multinomial(const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor multinomial_symint(const at::Tensor & self, c10::SymInt num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_outf(const at::Tensor & self, int64_t num_samples, bool replacement, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & multinomial_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_symint_outf(const at::Tensor & self, c10::SymInt num_samples, bool replacement, ::std::optional generator, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc96880eb1b33356f1981244400ac6867cf73371 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cuda_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multinomial(const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor multinomial_symint(const at::Tensor & self, c10::SymInt num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_outf(const at::Tensor & self, int64_t num_samples, bool replacement, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & multinomial_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_symint_outf(const at::Tensor & self, c10::SymInt num_samples, bool replacement, ::std::optional generator, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_native.h new file mode 100644 index 0000000000000000000000000000000000000000..54c5d03bc989809d2120c8e9494a348110372ea3 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multinomial(const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_out(const at::Tensor & self, int64_t num_samples, bool replacement, ::std::optional generator, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c178a8bdecdc17df37ffb07176a2cc0b3084a312 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API multinomial_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymInt, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multinomial"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "multinomial.out(Tensor self, SymInt num_samples, bool replacement=False, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymInt num_samples, bool replacement, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt num_samples, bool replacement, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API multinomial { + using schema = at::Tensor (const at::Tensor &, c10::SymInt, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multinomial"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "multinomial(Tensor self, SymInt num_samples, bool replacement=False, *, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymInt num_samples, bool replacement, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt num_samples, bool replacement, ::std::optional generator); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply.h new file mode 100644 index 0000000000000000000000000000000000000000..bce7fc9c91152e2619f39abb9630e18fcc08c8a1 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::multiply.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor multiply(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::multiply_Tensor::call(self, other); +} + +// aten::multiply.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multiply_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::multiply_out::call(self, other, out); +} +// aten::multiply.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multiply_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::multiply_out::call(self, other, out); +} + +// aten::multiply.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor multiply(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::multiply_Scalar::call(self, other); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0087787309235f217b5388508e16678b339858a1 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply_compositeimplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multiply(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & multiply_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & multiply_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & multiply_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor multiply(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & multiply_(at::Tensor & self, const at::Scalar & other); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply_native.h new file mode 100644 index 0000000000000000000000000000000000000000..82775810c09aa3e8051265f0b839141b399fffb7 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 multiply(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & multiply_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & multiply_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor multiply(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & multiply_(at::Tensor & self, const at::Scalar & other); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..76ecb8d9b221cc79455583eae32c7532e14f24f2 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/multiply_ops.h @@ -0,0 +1,78 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API multiply_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multiply"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "multiply.Tensor(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API multiply__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multiply_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "multiply_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API multiply_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::multiply"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "multiply.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 multiply_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multiply"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "multiply.Scalar(Tensor self, Scalar other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API multiply__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::multiply_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "multiply_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv.h new file mode 100644 index 0000000000000000000000000000000000000000..a900dfe28762ea310019ddab024ce0e3537e032f --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mv(Tensor self, Tensor vec) -> Tensor +inline at::Tensor mv(const at::Tensor & self, const at::Tensor & vec) { + return at::_ops::mv::call(self, vec); +} + +// aten::mv.out(Tensor self, Tensor vec, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec) { + return at::_ops::mv_out::call(self, vec, out); +} +// aten::mv.out(Tensor self, Tensor vec, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mv_outf(const at::Tensor & self, const at::Tensor & vec, at::Tensor & out) { + return at::_ops::mv_out::call(self, vec, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a255757cfb649e333990fdde2f39285c7d93eb3 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mv(const at::Tensor & self, const at::Tensor & vec); +TORCH_API at::Tensor & mv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec); +TORCH_API at::Tensor & mv_outf(const at::Tensor & self, const at::Tensor & vec, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f00252f9936e024cc522af58e73371ee24e75b08 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mv(const at::Tensor & self, const at::Tensor & vec); +TORCH_API at::Tensor & mv_out(const at::Tensor & self, const at::Tensor & vec, at::Tensor & out); +TORCH_API at::Tensor mv_sparse(const at::Tensor & self, const at::Tensor & vec); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f2b07981ff04d40599f153ebfae717a55b30171e --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mv_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mv { + 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::mv"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mv(Tensor self, Tensor vec) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & vec); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec); +}; + +struct TORCH_API mv_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::mv"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mv.out(Tensor self, Tensor vec, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & vec, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma.h new file mode 100644 index 0000000000000000000000000000000000000000..00842718285183dae24ea9b51661ee1006ab6e56 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mvlgamma.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mvlgamma_out(at::Tensor & out, const at::Tensor & self, int64_t p) { + return at::_ops::mvlgamma_out::call(self, p, out); +} +// aten::mvlgamma.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mvlgamma_outf(const at::Tensor & self, int64_t p, at::Tensor & out) { + return at::_ops::mvlgamma_out::call(self, p, out); +} + +// aten::mvlgamma(Tensor self, int p) -> Tensor +inline at::Tensor mvlgamma(const at::Tensor & self, int64_t p) { + return at::_ops::mvlgamma::call(self, p); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..abf5fb97e00d2acba1a4220cdd3196f10e97a15d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mvlgamma(const at::Tensor & self, int64_t p); +TORCH_API at::Tensor & mvlgamma_(at::Tensor & self, int64_t p); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..172129aa3dff863188358c79c550f760f279fa20 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mvlgamma_out(at::Tensor & out, const at::Tensor & self, int64_t p); +TORCH_API at::Tensor & mvlgamma_outf(const at::Tensor & self, int64_t p, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..632e2d27322b50735d1585f548a70de09e3349e6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & mvlgamma_out(at::Tensor & out, const at::Tensor & self, int64_t p); +TORCH_API at::Tensor & mvlgamma_outf(const at::Tensor & self, int64_t p, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b9c6ef27fe6bd312836fcc317ef427e505464ba5 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 mvlgamma(const at::Tensor & self, int64_t p); +TORCH_API at::Tensor & mvlgamma_(at::Tensor & self, int64_t p); +TORCH_API at::Tensor & mvlgamma_out(const at::Tensor & self, int64_t p, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..be4e2c4f036737c633e5ee4c17e5256428c1f2ea --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/mvlgamma_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API mvlgamma_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mvlgamma"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mvlgamma.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p, at::Tensor & out); +}; + +struct TORCH_API mvlgamma { + using schema = 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::mvlgamma"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mvlgamma(Tensor self, int p) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p); +}; + +struct TORCH_API mvlgamma_ { + using schema = at::Tensor & (at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mvlgamma_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mvlgamma_(Tensor(a!) self, int p) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t p); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t p); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num.h new file mode 100644 index 0000000000000000000000000000000000000000..2287e7b576b9a27649e7a2f514048be209ccdfdf --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num.h @@ -0,0 +1,50 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::nan_to_num(Tensor self, float? nan=None, float? posinf=None, float? neginf=None) -> Tensor +inline at::Tensor nan_to_num(const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt) { + return at::_ops::nan_to_num::call(self, nan, posinf, neginf); +} + +// aten::nan_to_num_(Tensor(a!) self, float? nan=None, float? posinf=None, float? neginf=None) -> Tensor(a!) +inline at::Tensor & nan_to_num_(at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt) { + return at::_ops::nan_to_num_::call(self, nan, posinf, neginf); +} + +// aten::nan_to_num.out(Tensor self, float? nan=None, float? posinf=None, float? neginf=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nan_to_num_out(at::Tensor & out, const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt) { + return at::_ops::nan_to_num_out::call(self, nan, posinf, neginf, out); +} +// aten::nan_to_num.out(Tensor self, float? nan=None, float? posinf=None, float? neginf=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nan_to_num_outf(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out) { + return at::_ops::nan_to_num_out::call(self, nan, posinf, neginf, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ff79b532251d375f5ad83ffde4d2d012e7287c2c --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nan_to_num(const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); +TORCH_API at::Tensor & nan_to_num_(at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4dbf0615aceefd20383114e0f03ac9130cb87cca --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_cpu_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & nan_to_num_out(at::Tensor & out, const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); +TORCH_API at::Tensor & nan_to_num_outf(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f9138eb842b6cfb380143fff9ee40b9a4a5f28d5 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_cuda_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & nan_to_num_out(at::Tensor & out, const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); +TORCH_API at::Tensor & nan_to_num_outf(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_native.h new file mode 100644 index 0000000000000000000000000000000000000000..39df604c7dc3cbefe4ad9df7aed1a0e6f8c21fa9 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_native.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nan_to_num(const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); +TORCH_API at::Tensor & nan_to_num_(at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); +TORCH_API at::Tensor & nan_to_num_out(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out); +TORCH_API at::Tensor nan_to_num_sparse(const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); +TORCH_API at::Tensor & nan_to_num_sparse_out(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out); +TORCH_API at::Tensor & nan_to_num_sparse_(at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5bfc74f721f87cbb270f280e1f830c6a958e0266 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nan_to_num_ops.h @@ -0,0 +1,56 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API nan_to_num { + using schema = at::Tensor (const at::Tensor &, ::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::nan_to_num"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nan_to_num(Tensor self, float? nan=None, float? posinf=None, float? neginf=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf); +}; + +struct TORCH_API nan_to_num_ { + using schema = at::Tensor & (at::Tensor &, ::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::nan_to_num_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nan_to_num_(Tensor(a!) self, float? nan=None, float? posinf=None, float? neginf=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf); +}; + +struct TORCH_API nan_to_num_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nan_to_num"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "nan_to_num.out(Tensor self, float? nan=None, float? posinf=None, float? neginf=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean.h new file mode 100644 index 0000000000000000000000000000000000000000..696990710201725771fcf0d97eb02a3c3952b14c --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::nanmean(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor nanmean(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::nanmean::call(self, dim, keepdim, dtype); +} + +// aten::nanmean.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanmean_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::nanmean_out::call(self, dim, keepdim, dtype, out); +} +// aten::nanmean.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanmean_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::nanmean_out::call(self, dim, keepdim, dtype, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d462705129f912b3f5b0f85fe61dcde72386f3cf --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nanmean(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & nanmean_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & nanmean_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_native.h new file mode 100644 index 0000000000000000000000000000000000000000..11f1533bf4ce267861e0ca3523c32ce19b7855d6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nanmean(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & nanmean_out(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7dc8113adcbd5ec14f3e6ce43f2525d26ffc4b2d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API nanmean { + using schema = at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanmean"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nanmean(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype); +}; + +struct TORCH_API nanmean_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanmean"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "nanmean.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian.h new file mode 100644 index 0000000000000000000000000000000000000000..da9a08795a529fa4d4fded483e1f98c3f812aecc --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian.h @@ -0,0 +1,73 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::nanmedian(Tensor self) -> Tensor +inline at::Tensor nanmedian(const at::Tensor & self) { + return at::_ops::nanmedian::call(self); +} + +// aten::nanmedian.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple nanmedian(const at::Tensor & self, int64_t dim, bool keepdim=false) { + return at::_ops::nanmedian_dim::call(self, dim, keepdim); +} + +// aten::nanmedian.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple nanmedian_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false) { + return at::_ops::nanmedian_dim_values::call(self, dim, keepdim, values, indices); +} +// aten::nanmedian.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple nanmedian_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::nanmedian_dim_values::call(self, dim, keepdim, values, indices); +} + +// aten::nanmedian.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) +inline ::std::tuple nanmedian(const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::nanmedian_names_dim::call(self, dim, keepdim); +} + +// aten::nanmedian.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple nanmedian_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false) { + return at::_ops::nanmedian_names_dim_values::call(self, dim, keepdim, values, indices); +} +// aten::nanmedian.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple nanmedian_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::nanmedian_names_dim_values::call(self, dim, keepdim, values, indices); +} + +// aten::nanmedian.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanmedian_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::nanmedian_out::call(self, out); +} +// aten::nanmedian.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanmedian_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::nanmedian_out::call(self, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..df46da1a8602410befb5547795818d36716dcc61 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & nanmedian_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & nanmedian_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API ::std::tuple nanmedian(const at::Tensor & self, int64_t dim, bool keepdim=false); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4babc373c8a0c147b4d6adfcaaf7cd1ea578fa43 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nanmedian(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple nanmedian_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple nanmedian_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fd99f8c69a1388383fde288d2b2f7a3b0339f2d6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nanmedian(const at::Tensor & self); +TORCH_API ::std::tuple nanmedian_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple nanmedian_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9673189424e823d4dd09ab4f39e33d1f235c14ee --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nanmedian(const at::Tensor & self); +TORCH_API ::std::tuple nanmedian_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple nanmedian_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f7cb2ce3d1c575b8bef504de71f66a016bda3f86 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_native.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 & nanmedian_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor nanmedian_cpu(const at::Tensor & self); +TORCH_API at::Tensor nanmedian_cuda(const at::Tensor & self); +TORCH_API ::std::tuple nanmedian(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple nanmedian_out_cpu(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple nanmedian_out_cuda(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple nanmedian(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API ::std::tuple nanmedian_out(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bb03c3a86c7c8351dc45ad81879af7d7b6bc4203 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanmedian_ops.h @@ -0,0 +1,89 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API nanmedian { + 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::nanmedian"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nanmedian(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 nanmedian_dim { + using schema = ::std::tuple (const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanmedian"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "nanmedian.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices)"; + static ::std::tuple call(const at::Tensor & self, int64_t dim, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim); +}; + +struct TORCH_API nanmedian_dim_values { + using schema = ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanmedian"; + static constexpr const char* overload_name = "dim_values"; + static constexpr const char* schema_str = "nanmedian.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)"; + static ::std::tuple call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +}; + +struct TORCH_API nanmedian_names_dim { + using schema = ::std::tuple (const at::Tensor &, at::Dimname, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanmedian"; + static constexpr const char* overload_name = "names_dim"; + static constexpr const char* schema_str = "nanmedian.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)"; + static ::std::tuple call(const at::Tensor & self, at::Dimname dim, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim); +}; + +struct TORCH_API nanmedian_names_dim_values { + using schema = ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanmedian"; + static constexpr const char* overload_name = "names_dim_values"; + static constexpr const char* schema_str = "nanmedian.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)"; + static ::std::tuple call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices); +}; + +struct TORCH_API nanmedian_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::nanmedian"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "nanmedian.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 + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile.h new file mode 100644 index 0000000000000000000000000000000000000000..7b8eeea30d9166267595936ad8068d60c17467a2 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile.h @@ -0,0 +1,59 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor +inline at::Tensor nanquantile(const at::Tensor & self, const at::Tensor & q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear") { + return at::_ops::nanquantile::call(self, q, dim, keepdim, interpolation); +} + +// aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanquantile_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear") { + return at::_ops::nanquantile_out::call(self, q, dim, keepdim, interpolation, out); +} +// aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanquantile_outf(const at::Tensor & self, const at::Tensor & q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out) { + return at::_ops::nanquantile_out::call(self, q, dim, keepdim, interpolation, out); +} + +// aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor +inline at::Tensor nanquantile(const at::Tensor & self, double q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear") { + return at::_ops::nanquantile_scalar::call(self, q, dim, keepdim, interpolation); +} + +// aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanquantile_out(at::Tensor & out, const at::Tensor & self, double q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear") { + return at::_ops::nanquantile_scalar_out::call(self, q, dim, keepdim, interpolation, out); +} +// aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanquantile_outf(const at::Tensor & self, double q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out) { + return at::_ops::nanquantile_scalar_out::call(self, q, dim, keepdim, interpolation, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9def889cf9a42be7e654cb314b550939381ef9f9 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile_compositeimplicitautograd_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nanquantile(const at::Tensor & self, const at::Tensor & q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear"); +TORCH_API at::Tensor & nanquantile_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear"); +TORCH_API at::Tensor & nanquantile_outf(const at::Tensor & self, const at::Tensor & q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); +TORCH_API at::Tensor nanquantile(const at::Tensor & self, double q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear"); +TORCH_API at::Tensor & nanquantile_out(at::Tensor & out, const at::Tensor & self, double q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear"); +TORCH_API at::Tensor & nanquantile_outf(const at::Tensor & self, double q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile_native.h new file mode 100644 index 0000000000000000000000000000000000000000..aaf19c0cf2b8fa8e2fa87404d187900a291a8769 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nanquantile(const at::Tensor & self, const at::Tensor & q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear"); +TORCH_API at::Tensor & nanquantile_out(const at::Tensor & self, const at::Tensor & q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); +TORCH_API at::Tensor nanquantile(const at::Tensor & self, double q, ::std::optional dim=::std::nullopt, bool keepdim=false, c10::string_view interpolation="linear"); +TORCH_API at::Tensor & nanquantile_out(const at::Tensor & self, double q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3910aa82bc6cc0959092cd0c131065ddf1bdb962 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nanquantile_ops.h @@ -0,0 +1,67 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API nanquantile { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional, bool, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanquantile"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & q, ::std::optional dim, bool keepdim, c10::string_view interpolation); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & q, ::std::optional dim, bool keepdim, c10::string_view interpolation); +}; + +struct TORCH_API nanquantile_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, ::std::optional, bool, c10::string_view, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanquantile"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); +}; + +struct TORCH_API nanquantile_scalar { + using schema = at::Tensor (const at::Tensor &, double, ::std::optional, bool, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanquantile"; + static constexpr const char* overload_name = "scalar"; + static constexpr const char* schema_str = "nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor"; + static at::Tensor call(const at::Tensor & self, double q, ::std::optional dim, bool keepdim, c10::string_view interpolation); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double q, ::std::optional dim, bool keepdim, c10::string_view interpolation); +}; + +struct TORCH_API nanquantile_scalar_out { + using schema = at::Tensor & (const at::Tensor &, double, ::std::optional, bool, c10::string_view, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nanquantile"; + static constexpr const char* overload_name = "scalar_out"; + static constexpr const char* schema_str = "nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, double q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double q, ::std::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum.h new file mode 100644 index 0000000000000000000000000000000000000000..899f24cc1bb55429941782889bc8ca07ff36dc5d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::nansum(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor nansum(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::nansum::call(self, dim, keepdim, dtype); +} + +// aten::nansum.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nansum_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::nansum_out::call(self, dim, keepdim, dtype, out); +} +// aten::nansum.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nansum_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::nansum_out::call(self, dim, keepdim, dtype, out); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e4873dd71df73b8cb90e4bbebbb44670fb1337ad --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nansum(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & nansum_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & nansum_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..06b3d9cfc6257bb45d0bda88185bf62502eaf6e1 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nansum(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & nansum_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & nansum_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8fd5454de55fd56b8d3dcc3f39cf5ea379543e83 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_native.h @@ -0,0 +1,27 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 nansum(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & nansum_out(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a4ec056cd29ba0f5400bfc00b3719cfbcd0e7fa6 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/nansum_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API nansum { + using schema = at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nansum"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nansum(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype); +}; + +struct TORCH_API nansum_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nansum"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "nansum.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow.h new file mode 100644 index 0000000000000000000000000000000000000000..8946a97975a1f657da5d9a52783280ebb029de15 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow.h @@ -0,0 +1,75 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) +inline at::Tensor narrow(const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow(const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow::call(self, dim, start, length); + } +} + +// aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) +inline at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow::call(self, dim, start, length); + } +} + +// aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) +inline at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, int64_t length) { + return at::_ops::narrow_Tensor::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, int64_t length) { + return at::_ops::narrow_Tensor::call(self, dim, start, length); + } +} + +// aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) +inline at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length) { + return at::_ops::narrow_Tensor::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length) { + return at::_ops::narrow_Tensor::call(self, dim, start, length); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bf6f660379ea8fa2cd49da52ad642f425cd83bfe --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h @@ -0,0 +1,31 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..7e9e4f4df60d5b8e748897094422364f1d7efe56 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy.h @@ -0,0 +1,97 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::narrow_copy(Tensor self, int dim, SymInt start, SymInt length) -> Tensor +inline at::Tensor narrow_copy(const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow_copy::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow_copy(const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow_copy::call(self, dim, start, length); + } +} + +// aten::narrow_copy(Tensor self, int dim, SymInt start, SymInt length) -> Tensor +inline at::Tensor narrow_copy_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow_copy::call(self, dim, start, length); +} +namespace symint { + template >> + at::Tensor narrow_copy(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow_copy::call(self, dim, start, length); + } +} + +// aten::narrow_copy.out(Tensor self, int dim, SymInt start, SymInt length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & narrow_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); +} +namespace symint { + template >> + at::Tensor & narrow_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); + } +} + +// aten::narrow_copy.out(Tensor self, int dim, SymInt start, SymInt length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & narrow_copy_outf(const at::Tensor & self, int64_t dim, int64_t start, int64_t length, at::Tensor & out) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); +} +namespace symint { + template >> + at::Tensor & narrow_copy_outf(const at::Tensor & self, int64_t dim, int64_t start, int64_t length, at::Tensor & out) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); + } +} + +// aten::narrow_copy.out(Tensor self, int dim, SymInt start, SymInt length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & narrow_copy_symint_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); +} +namespace symint { + template >> + at::Tensor & narrow_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); + } +} + +// aten::narrow_copy.out(Tensor self, int dim, SymInt start, SymInt length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & narrow_copy_symint_outf(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length, at::Tensor & out) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); +} +namespace symint { + template >> + at::Tensor & narrow_copy_outf(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length, at::Tensor & out) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_compositeexplicitautogradnonfunctional_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..15016503419733bcdab287895a6eaa0ab08d9725 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor narrow_copy(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_copy_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f0ae17e4cdf3bf8508278ec7fe685ecbc34c9572 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_cpu_dispatch.h @@ -0,0 +1,33 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 narrow_copy(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_copy_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor & narrow_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor & narrow_copy_outf(const at::Tensor & self, int64_t dim, int64_t start, int64_t length, at::Tensor & out); +TORCH_API at::Tensor & narrow_copy_symint_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor & narrow_copy_symint_outf(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length, at::Tensor & out); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d4e3273485581aed6bfd2cebb71b711395112129 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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_copy_dense_cpu(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor & narrow_copy_dense_cpu_out(const at::Tensor & self, int64_t dim, int64_t start, int64_t length, at::Tensor & out); +TORCH_API at::Tensor narrow_copy_sparse(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_copy_dense_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2b570ae75a2edeb57b015585befd97123fdabb7d --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API narrow_copy { + using schema = at::Tensor (const at::Tensor &, int64_t, c10::SymInt, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::narrow_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "narrow_copy(Tensor self, int dim, SymInt start, SymInt length) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +}; + +struct TORCH_API narrow_copy_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, c10::SymInt, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::narrow_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "narrow_copy.out(Tensor self, int dim, SymInt start, SymInt length, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length, at::Tensor & out); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_native.h new file mode 100644 index 0000000000000000000000000000000000000000..46d567c63671d87d24ca2b8c00a21bdb0da2f34a --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_native.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..29fc0a495ac6e4ac7e672fa20938de718fae0c71 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API narrow { + using schema = at::Tensor (const at::Tensor &, int64_t, c10::SymInt, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::narrow"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +}; + +struct TORCH_API narrow_Tensor { + using schema = at::Tensor (const at::Tensor &, int64_t, const at::Tensor &, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::narrow"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..5c59ecc7e50e042c1f74c91d3254d57f41dd3956 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) +inline ::std::tuple native_batch_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps) { + return at::_ops::native_batch_norm::call(input, weight, bias, running_mean, running_var, training, momentum, eps); +} + +// aten::native_batch_norm.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_batch_norm_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps) { + return at::_ops::native_batch_norm_out::call(input, weight, bias, running_mean, running_var, training, momentum, eps, out, save_mean, save_invstd); +} +// aten::native_batch_norm.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_batch_norm_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd) { + return at::_ops::native_batch_norm_out::call(input, weight, bias, running_mean, running_var, training, momentum, eps, out, save_mean, save_invstd); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..b1c68ac0dd67fd664193dc12977f67959ed9ea33 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::native_batch_norm_backward(Tensor grad_out, Tensor input, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, float eps, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple native_batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask) { + return at::_ops::native_batch_norm_backward::call(grad_out, input, weight, running_mean, running_var, save_mean, save_invstd, train, eps, output_mask); +} + +// aten::native_batch_norm_backward.out(Tensor grad_out, Tensor input, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, float eps, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_batch_norm_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask) { + return at::_ops::native_batch_norm_backward_out::call(grad_out, input, weight, running_mean, running_var, save_mean, save_invstd, train, eps, output_mask, out0, out1, out2); +} +// aten::native_batch_norm_backward.out(Tensor grad_out, Tensor input, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, float eps, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_batch_norm_backward_outf(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_batch_norm_backward_out::call(grad_out, input, weight, running_mean, running_var, save_mean, save_invstd, train, eps, output_mask, out0, out1, out2); +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_compositeexplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dc96649fbcfe7e87a159f7168a062eec2b7594ed --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple native_batch_norm_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); +TORCH_API ::std::tuple native_batch_norm_backward_outf(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + +} // namespace compositeexplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fbb064726cc38b64e0547ef51525f555cc9ca732 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 ::std::tuple native_batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a64c03d85e02f3a345540f14983ce480bf669853 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple native_batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..02cfd1137e238fd13e8118da59486fbb7d3d1e88 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_native.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 native_batch_norm_backward_out(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple batch_norm_backward_cpu(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); +TORCH_API ::std::tuple batch_norm_backward_cuda(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); +TORCH_API ::std::tuple mkldnn_batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4c4eba1796d42d5f145f35f5eaa644e29ed8b5fa --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_backward_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API native_batch_norm_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_batch_norm_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "native_batch_norm_backward(Tensor grad_out, Tensor input, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, float eps, bool[3] output_mask) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); +}; + +struct TORCH_API native_batch_norm_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_batch_norm_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "native_batch_norm_backward.out(Tensor grad_out, Tensor input, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_invstd, bool train, float eps, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_cpu_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc0a4395d1799186f4af12ff02815ea5256570a4 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_cpu_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 ::std::tuple native_batch_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple native_batch_norm_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple native_batch_norm_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); + +} // namespace cpu +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_cuda_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d8e6d25a0280a7a0f7c6e11c5f1459f017f4e579 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_cuda_dispatch.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple native_batch_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple native_batch_norm_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple native_batch_norm_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); + +} // namespace cuda +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_native.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3ef8d14993195d62343e81b86f01d5a70447012c --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_native.h @@ -0,0 +1,30 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 batch_norm_cpu(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple batch_norm_cpu_out(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); +TORCH_API ::std::tuple batch_norm_cuda(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple batch_norm_cuda_out(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); +TORCH_API ::std::tuple mkldnn_batch_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +} // namespace native +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_ops.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4bc3acec8a1850c83124f2d15aaa71499e81c61 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_ops.h @@ -0,0 +1,45 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#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 _ops { + + +struct TORCH_API native_batch_norm { + using schema = ::std::tuple (const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_batch_norm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +}; + +struct TORCH_API native_batch_norm_out { + using schema = ::std::tuple (const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_batch_norm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "native_batch_norm.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); +}; + +}} // namespace at::_ops + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_channel_shuffle.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_channel_shuffle.h new file mode 100644 index 0000000000000000000000000000000000000000..9c1c4311ddbfa43a7f271fe5d8b136f3edf3ca90 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_channel_shuffle.h @@ -0,0 +1,53 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::native_channel_shuffle(Tensor self, SymInt groups) -> Tensor +inline at::Tensor native_channel_shuffle(const at::Tensor & self, int64_t groups) { + return at::_ops::native_channel_shuffle::call(self, groups); +} +namespace symint { + template >> + at::Tensor native_channel_shuffle(const at::Tensor & self, int64_t groups) { + return at::_ops::native_channel_shuffle::call(self, groups); + } +} + +// aten::native_channel_shuffle(Tensor self, SymInt groups) -> Tensor +inline at::Tensor native_channel_shuffle_symint(const at::Tensor & self, c10::SymInt groups) { + return at::_ops::native_channel_shuffle::call(self, groups); +} +namespace symint { + template >> + at::Tensor native_channel_shuffle(const at::Tensor & self, c10::SymInt groups) { + return at::_ops::native_channel_shuffle::call(self, groups); + } +} + +} + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) diff --git a/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_channel_shuffle_compositeimplicitautograd_dispatch.h b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_channel_shuffle_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..272c077601f5ce9b50ebdb398ae76bab6f1d9077 --- /dev/null +++ b/miniconda3/envs/ladir/lib/python3.10/site-packages/torch/include/ATen/ops/native_channel_shuffle_compositeimplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) +#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 native_channel_shuffle(const at::Tensor & self, int64_t groups); +TORCH_API at::Tensor native_channel_shuffle_symint(const at::Tensor & self, c10::SymInt groups); + +} // namespace compositeimplicitautograd +} // namespace at + +#else +#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." +#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION)