diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Int_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Int_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9efc821dba9a76be10add00499ad55bb92e4de4f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Int_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _cast_Int(const at::Tensor & self, bool non_blocking=false); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..7ac3b1dc4f199095ee91985301209d121b3194e3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cdist_forward(Tensor x1, Tensor x2, float p, int? compute_mode) -> Tensor +inline at::Tensor _cdist_forward(const at::Tensor & x1, const at::Tensor & x2, double p, c10::optional compute_mode) { + return at::_ops::_cdist_forward::call(x1, x2, p, compute_mode); +} + +// aten::_cdist_forward.out(Tensor x1, Tensor x2, float p, int? compute_mode, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cdist_forward_out(at::Tensor & out, const at::Tensor & x1, const at::Tensor & x2, double p, c10::optional compute_mode) { + return at::_ops::_cdist_forward_out::call(x1, x2, p, compute_mode, out); +} +// aten::_cdist_forward.out(Tensor x1, Tensor x2, float p, int? compute_mode, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cdist_forward_outf(const at::Tensor & x1, const at::Tensor & x2, double p, c10::optional compute_mode, at::Tensor & out) { + return at::_ops::_cdist_forward_out::call(x1, x2, p, compute_mode, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d3b91715ae1613a7335b7cc8c0c98ad19d8319db --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _embedding_bag_forward_only(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_native.h new file mode 100644 index 0000000000000000000000000000000000000000..09dc3340dc3c8b0cd749549571185229830a3fd2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _embedding_bag_out(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +TORCH_API ::std::tuple _embedding_bag_cpu(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +TORCH_API ::std::tuple _embedding_bag_cuda(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4c71fc0db5e7fa774082d403935db77998db18de --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_ceil_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::vector _foreach_ceil(at::TensorList self); +TORCH_API void _foreach_ceil_(at::TensorList self); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9b81a69870a4a9c05f8e07445de08c69686107c4 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_erf(at::TensorList self); +TORCH_API void _foreach_erf_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c51274a7ae94d01774f3997df525d8c9a5399f41 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lerp_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_lerp_List { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_lerp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "List") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[]") + static ::std::vector call(at::TensorList self, at::TensorList tensors1, at::TensorList weights); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights); +}; + +struct TORCH_API _foreach_lerp__List { + using schema = void (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_lerp_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "List") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> ()") + static void call(at::TensorList self, at::TensorList tensors1, at::TensorList weights); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights); +}; + +struct TORCH_API _foreach_lerp_Scalar { + using schema = ::std::vector (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_lerp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[]") + static ::std::vector call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +}; + +struct TORCH_API _foreach_lerp__Scalar { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_lerp_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> ()") + static void call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +}; + +struct TORCH_API _foreach_lerp_List_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_lerp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "List_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out); +}; + +struct TORCH_API _foreach_lerp_Scalar_out { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_lerp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2.h new file mode 100644 index 0000000000000000000000000000000000000000..113685a9a88a01206dae1adbc0ffbb3669fb2466 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_log2(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_log2(at::TensorList self) { + return at::_ops::_foreach_log2::call(self); +} + +// aten::_foreach_log2_(Tensor(a!)[] self) -> () +inline void _foreach_log2_(at::TensorList self) { + return at::_ops::_foreach_log2_::call(self); +} + +// aten::_foreach_log2.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log2_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_log2_out::call(self, out); +} +// aten::_foreach_log2.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_log2_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_log2_out::call(self, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3b95be26cbc56a50b4414f495b0df5b74c9cfcc3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_log2 { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_log2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_log2(Tensor[] self) -> Tensor[]") + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log2_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_log2_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_log2_(Tensor(a!)[] self) -> ()") + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log2_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_log2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_log2.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..844c715350b05f6abef9257f2ed9b5b132f2cc01 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _histogramdd_from_bin_tensors_out(at::Tensor & out, const at::Tensor & self, at::TensorList bins, const c10::optional & weight={}, bool density=false); +TORCH_API at::Tensor & _histogramdd_from_bin_tensors_outf(const at::Tensor & self, at::TensorList bins, const c10::optional & weight, bool density, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_lazy_clone.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_lazy_clone.h new file mode 100644 index 0000000000000000000000000000000000000000..9e7bfdb9465e98cfe17d3d26b17bf63844f90433 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_lazy_clone.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_lazy_clone(Tensor self) -> Tensor +inline at::Tensor _lazy_clone(const at::Tensor & self) { + return at::_ops::_lazy_clone::call(self); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_eigvals_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_eigvals_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a606d520c0f6f6b442eba284268e394e9918b65d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_eigvals_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _linalg_eigvals { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_linalg_eigvals") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_linalg_eigvals(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..798a338c61a818a572afff1148d2c83a013adb42 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _mps_convolution_transpose { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_mps_convolution_transpose") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_mps_convolution_transpose(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_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, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +struct TORCH_API _mps_convolution_transpose_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_mps_convolution_transpose") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_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, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_size_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3c504a0f1708fd668b2f6366accb9817a75e36e9 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_size_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _nested_tensor_size { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_nested_tensor_size") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_nested_tensor_size(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 _nested_tensor_size_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_nested_tensor_size") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_nested_tensor_size.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_pdist_forward_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_pdist_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a6e98ecfa642f3790c5f84eb12fcff650ca56976 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_pdist_forward_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _pdist_forward(const at::Tensor & self, double p=2); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_remove_batch_dim_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_remove_batch_dim_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4c38a770adb6a2c7ee6104d280b277118ff1bb31 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_remove_batch_dim_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _remove_batch_dim { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_remove_batch_dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_remove_batch_dim(Tensor self, int level, int batch_size, int out_dim) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t level, int64_t batch_size, int64_t out_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t level, int64_t batch_size, int64_t out_dim); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_backward_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44978625a1b921083fb33ff2b9040afa77de0f14 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_backward_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _scaled_dot_product_flash_attention_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, c10::optional scale=c10::nullopt); +TORCH_API ::std::tuple _scaled_dot_product_flash_attention_backward_symint(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, c10::optional scale=c10::nullopt); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..156e618d581416743636150a9d44c665f20ccaea --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _softmax(const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_outf(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_semi_structured_linear_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_semi_structured_linear_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a0d2338522ae94318cab315b73a578e7454140eb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_semi_structured_linear_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_semi_structured_linear { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_semi_structured_linear") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_semi_structured_linear(Tensor input, Tensor weight, Tensor meta, *, Tensor? bias=None, str? activation=None, ScalarType? out_dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & meta, const c10::optional & bias, c10::optional activation, c10::optional out_dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & meta, const c10::optional & bias, c10::optional activation, c10::optional out_dtype); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..9402b831cd2c6003b4562d7b10b0f9c5dea7ac8f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_test_autograd_multiple_dispatch_view_copy(Tensor self) -> Tensor +inline at::Tensor _test_autograd_multiple_dispatch_view_copy(const at::Tensor & self) { + return at::_ops::_test_autograd_multiple_dispatch_view_copy::call(self); +} + +// aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_autograd_multiple_dispatch_view_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::_test_autograd_multiple_dispatch_view_copy_out::call(self, out); +} +// aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_autograd_multiple_dispatch_view_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::_test_autograd_multiple_dispatch_view_copy_out::call(self, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_optional_intlist_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_optional_intlist_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f3ed4f5b973c1456d314a72d2ef2e758d8cad526 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_optional_intlist_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _test_optional_intlist { + using schema = at::Tensor (const at::Tensor &, at::OptionalIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_test_optional_intlist") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_optional_intlist(Tensor values, int[]? addends) -> Tensor") + static at::Tensor call(const at::Tensor & values, at::OptionalIntArrayRef addends); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & values, at::OptionalIntArrayRef addends); +}; + +struct TORCH_API _test_optional_intlist_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_test_optional_intlist") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & values, at::OptionalIntArrayRef addends, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & values, at::OptionalIntArrayRef addends, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..79c95544305e7ab8e7a85695dc8b812192a467ed --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _thnn_fused_gru_cell_out(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const c10::optional & input_bias, const c10::optional & hidden_bias, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple _thnn_fused_gru_cell_cuda(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const c10::optional & input_bias={}, const c10::optional & hidden_bias={}); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_trilinear_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_trilinear_native.h new file mode 100644 index 0000000000000000000000000000000000000000..23a407c86f1aa25039392eba4288aa348f856471 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_trilinear_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _trilinear_out(const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim, at::Tensor & out); +TORCH_API at::Tensor _trilinear(const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim=1); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..6e29f62e42bfd3a2cc7421ffbad6474a8c8efcf4 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bilinear2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bilinear2d_aa_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bilinear2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bilinear2d_aa_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bilinear2d_aa_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bilinear2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bilinear2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bilinear2d_aa_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor _upsample_bilinear2d_aa_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w); + } +} + +// aten::_upsample_bilinear2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bilinear2d_aa_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor _upsample_bilinear2d_aa_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_bilinear2d_aa_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/abs_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/abs_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..00e5a7b1c264ce43bca5e01ecbe88a563d14c8e0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/abs_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & abs_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & abs_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d.h new file mode 100644 index 0000000000000000000000000000000000000000..623d81a9c4b678943c071f52545cd263740a62d1 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & adaptive_avg_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_avg_pool3d_out::call(self, c10::fromIntArrayRefSlow(output_size), out); +} +namespace symint { + template ::value>> + at::Tensor & adaptive_avg_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_avg_pool3d_out::call(self, c10::fromIntArrayRefSlow(output_size), out); + } +} + +// aten::adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & adaptive_avg_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::adaptive_avg_pool3d_out::call(self, c10::fromIntArrayRefSlow(output_size), out); +} +namespace symint { + template ::value>> + at::Tensor & adaptive_avg_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::adaptive_avg_pool3d_out::call(self, c10::fromIntArrayRefSlow(output_size), out); + } +} + +// aten::adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & adaptive_avg_pool3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size) { + return at::_ops::adaptive_avg_pool3d_out::call(self, output_size, out); +} +namespace symint { + template ::value>> + at::Tensor & adaptive_avg_pool3d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size) { + return at::_ops::adaptive_avg_pool3d_out::call(self, output_size, out); + } +} + +// aten::adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & adaptive_avg_pool3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out) { + return at::_ops::adaptive_avg_pool3d_out::call(self, output_size, out); +} +namespace symint { + template ::value>> + at::Tensor & adaptive_avg_pool3d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out) { + return at::_ops::adaptive_avg_pool3d_out::call(self, output_size, out); + } +} + +// aten::adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor +inline at::Tensor adaptive_avg_pool3d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_avg_pool3d::call(self, c10::fromIntArrayRefSlow(output_size)); +} +namespace symint { + template ::value>> + at::Tensor adaptive_avg_pool3d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_avg_pool3d::call(self, c10::fromIntArrayRefSlow(output_size)); + } +} + +// aten::adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor +inline at::Tensor adaptive_avg_pool3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size) { + return at::_ops::adaptive_avg_pool3d::call(self, output_size); +} +namespace symint { + template ::value>> + at::Tensor adaptive_avg_pool3d(const at::Tensor & self, c10::SymIntArrayRef output_size) { + return at::_ops::adaptive_avg_pool3d::call(self, output_size); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/align_tensors_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/align_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b039c5f6beb132596ff1d5ae9c302878ab95ac59 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/align_tensors_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API align_tensors { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::align_tensors") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "align_tensors(Tensor[] tensors) -> Tensor[]") + static ::std::vector call(at::TensorList tensors); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/arctanh_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/arctanh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e9ebf625bfcc28afe01efe49f9316a397788d07a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/arctanh_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor arctanh(const at::Tensor & self); +TORCH_API at::Tensor & arctanh_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & arctanh_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b9a2552964dc7619b45e3da676fa591658588c90 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API batch_norm_gather_stats_with_counts { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, double, double, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::batch_norm_gather_stats_with_counts") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "batch_norm_gather_stats_with_counts(Tensor input, Tensor mean, Tensor invstd, Tensor? running_mean, Tensor? running_var, float momentum, float eps, Tensor counts) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & running_mean, const c10::optional & running_var, double momentum, double eps, const at::Tensor & counts); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & running_mean, const c10::optional & running_var, double momentum, double eps, const at::Tensor & counts); +}; + +struct TORCH_API batch_norm_gather_stats_with_counts_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, double, double, const at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::batch_norm_gather_stats_with_counts") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "batch_norm_gather_stats_with_counts.out(Tensor input, Tensor mean, Tensor invstd, Tensor? running_mean, Tensor? running_var, float momentum, float eps, Tensor counts, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & running_mean, const c10::optional & running_var, double momentum, double eps, const at::Tensor & counts, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & running_mean, const c10::optional & running_var, double momentum, double eps, const at::Tensor & counts, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_not_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_not_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5d78bf5906c610635664f99c8ec8e9c94c6c0811 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_not_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor bitwise_not(const at::Tensor & self); +TORCH_API at::Tensor & bitwise_not_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & bitwise_not_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & bitwise_not_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/contiguous_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/contiguous_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4f554ad217d17f3b7af13cf884f810f0fc5a220 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/contiguous_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API contiguous { + using schema = at::Tensor (const at::Tensor &, at::MemoryFormat); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::contiguous") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "contiguous(Tensor(a) self, *, MemoryFormat memory_format=contiguous_format) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self, at::MemoryFormat memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::MemoryFormat memory_format); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/convolution_backward_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/convolution_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7c5609ee0b65d4f88fe959497685a9e653de8def --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/convolution_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API convolution_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::OptionalSymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, c10::SymIntArrayRef, c10::SymInt, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::convolution_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); +}; + +struct TORCH_API convolution_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::OptionalSymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, 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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::convolution_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, 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 & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, 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 & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/copysign.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/copysign.h new file mode 100644 index 0000000000000000000000000000000000000000..123bf6536931902a4be16fdb4e081b2eb3777e02 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/copysign.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::copysign.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copysign_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::copysign_out::call(self, other, out); +} +// aten::copysign.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copysign_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::copysign_out::call(self, other, out); +} + +// aten::copysign.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor copysign(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::copysign_Tensor::call(self, other); +} + +// aten::copysign.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor copysign(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::copysign_Scalar::call(self, other); +} + +// aten::copysign.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copysign_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::copysign_Scalar_out::call(self, other, out); +} +// aten::copysign.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copysign_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::copysign_Scalar_out::call(self, other, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/count_nonzero.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/count_nonzero.h new file mode 100644 index 0000000000000000000000000000000000000000..a145693fcb08dc08ce09122f78eef07c3f06c910 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/count_nonzero.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::count_nonzero.dim_IntList(Tensor self, int[] dim) -> Tensor +inline at::Tensor count_nonzero(const at::Tensor & self, at::IntArrayRef dim) { + return at::_ops::count_nonzero_dim_IntList::call(self, dim); +} + +// aten::count_nonzero(Tensor self, int? dim=None) -> Tensor +inline at::Tensor count_nonzero(const at::Tensor & self, c10::optional dim=c10::nullopt) { + return at::_ops::count_nonzero::call(self, dim); +} + +// aten::count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & count_nonzero_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim) { + return at::_ops::count_nonzero_dim_IntList_out::call(self, dim, out); +} +// aten::count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & count_nonzero_outf(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out) { + return at::_ops::count_nonzero_dim_IntList_out::call(self, dim, out); +} + +// aten::count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & count_nonzero_out(at::Tensor & out, const at::Tensor & self, c10::optional dim=c10::nullopt) { + return at::_ops::count_nonzero_out::call(self, dim, out); +} +// aten::count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & count_nonzero_outf(const at::Tensor & self, c10::optional dim, at::Tensor & out) { + return at::_ops::count_nonzero_out::call(self, dim, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..6344507093cc8f2b70a9b8df9be939f5951b9abb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::cudnn_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple cudnn_batch_norm(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon) { + return at::_ops::cudnn_batch_norm::call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); +} + +// aten::cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple cudnn_batch_norm_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon) { + return at::_ops::cudnn_batch_norm_out::call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon, out0, out1, out2, out3); +} +// aten::cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple cudnn_batch_norm_outf(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { + return at::_ops::cudnn_batch_norm_out::call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon, out0, out1, out2, out3); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/data_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/data_native.h new file mode 100644 index 0000000000000000000000000000000000000000..02c8430efe7bc377cf72c3ebff92d7dcb3456929 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/data_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor data(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/div_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/div_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4f283c7ac8b7f15010b48ad60a6a0749cfc30baf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/div_cuda_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/div_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/div_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f7073fba5f517aa072decc244ff5bf4abd9519d6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/div_native.h @@ -0,0 +1,41 @@ +#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_div_out : public at::meta::structured_div_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_div_Tensor(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor div_sparse(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_out_sparse_zerodim(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & div_sparse_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor div_zerotensor(const at::Tensor & self, const at::Tensor & other); +struct TORCH_API structured_div_out_mode : public at::meta::structured_div_Tensor_mode { +void impl(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode, const at::Tensor & out); +}; +TORCH_API at::Tensor div_sparse(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode); +TORCH_API at::Tensor & div_out_sparse_zerodim(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode, at::Tensor & out); +TORCH_API at::Tensor & div_sparse_(at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode); +TORCH_API at::Tensor div(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & div_Scalar_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor NestedTensor_div_Scalar(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor div(const at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode); +TORCH_API at::Tensor & div_Scalar_mode_out(const at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfft2_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfft2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d13601d25caf076199907e7f50db97e8a1e7c0d3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfft2_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fft_rfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_rfft2_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/kthvalue_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/kthvalue_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..45b01801bf0d1523a53e1b7dd92f8537f629d224 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/kthvalue_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple kthvalue(const at::Tensor & self, int64_t k, int64_t dim=-1, bool keepdim=false); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eccb9154c1ecc07d439ef5f66d6e1fbc511c6631 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor linalg_ldl_solve(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian=false); +TORCH_API at::Tensor & linalg_ldl_solve_out(at::Tensor & out, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian=false); +TORCH_API at::Tensor & linalg_ldl_solve_outf(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_tensorsolve_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_tensorsolve_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fa5ae0902298786ca7f4b0f5edf367c6943f0b30 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_tensorsolve_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_tensorsolve { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::OptionalIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_tensorsolve") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_tensorsolve(Tensor self, Tensor other, int[]? dims=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims); +}; + +struct TORCH_API linalg_tensorsolve_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_tensorsolve") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_tensorsolve.out(Tensor self, Tensor other, int[]? dims=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vander_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vander_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bdaab51aa96d4300f4594bf3051569af5dfa6fe8 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vander_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor linalg_vander_symint(const at::Tensor & x, c10::optional N=c10::nullopt); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..805d3f08065d145b31b43b340f49575b3f68f0eb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API logaddexp_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::logaddexp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logaddexp.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 logaddexp { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::logaddexp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logaddexp(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logical_and_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logical_and_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cbba19f9530a4d070f824315fa02bfafc8ba1123 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logical_and_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & logical_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mean_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mean_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9aab4991fb2641ffef0b4e3f37218bbc77a20107 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mean_ops.h @@ -0,0 +1,72 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API mean { + using schema = at::Tensor (const at::Tensor &, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mean") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mean(Tensor self, *, ScalarType? dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional dtype); +}; + +struct TORCH_API mean_dim { + using schema = at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mean") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mean.dim(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional dtype); +}; + +struct TORCH_API mean_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mean") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mean.out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional dtype, at::Tensor & out); +}; + +struct TORCH_API mean_names_dim { + using schema = at::Tensor (const at::Tensor &, at::DimnameList, bool, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mean") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "names_dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mean.names_dim(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::DimnameList dim, bool keepdim, c10::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool keepdim, c10::optional dtype); +}; + +struct TORCH_API mean_names_out { + using schema = at::Tensor & (const at::Tensor &, at::DimnameList, bool, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mean") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "names_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mean.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::DimnameList dim, bool keepdim, c10::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool keepdim, c10::optional dtype, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b38b58ff23c0742acf3145df7ec4d90493c38f06 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & 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 diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/native_group_norm_backward_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/native_group_norm_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e872feb2f5331a38acda9dfd5600e3ae3b414053 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/native_group_norm_backward_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple native_group_norm_backward_out_symint(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional & weight, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple native_group_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional & weight, int64_t N, int64_t C, int64_t HxW, int64_t group, ::std::array output_mask); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/native_layer_norm_backward_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/native_layer_norm_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aa75c67f2734a9773c180cc84616a3cadc6f9ba3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/native_layer_norm_backward_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple native_layer_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional & weight, const c10::optional & bias, ::std::array output_mask); +TORCH_API ::std::tuple native_layer_norm_backward_symint(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional & weight, const c10::optional & bias, ::std::array output_mask); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_backward_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aab4644c12203a70748210e129585b393ab14244 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight); +TORCH_API at::Tensor nll_loss_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/pairwise_distance_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/pairwise_distance_native.h new file mode 100644 index 0000000000000000000000000000000000000000..750f65e5d62312c5e399327c02371ef466389e79 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/pairwise_distance_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor pairwise_distance(const at::Tensor & x1, const at::Tensor & x2, double p=2, double eps=1e-06, bool keepdim=false); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/polygamma_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/polygamma_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cfebbce4430fc83898b60719b9107f4458f74642 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/polygamma_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_polygamma : public TensorIteratorBase { + + + void meta(int64_t n, const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/put_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/put_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b94ab7225958dd622e2b2e41bf8e04ff232c0a0e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/put_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & put_(at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rad2deg_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rad2deg_native.h new file mode 100644 index 0000000000000000000000000000000000000000..99a7f0ab43bc1105c9eb6a61bda1fcd6eff979e3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rad2deg_native.h @@ -0,0 +1,29 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor rad2deg(const at::Tensor & self); +TORCH_API at::Tensor & rad2deg_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & rad2deg_(at::Tensor & self); +TORCH_API at::Tensor rad2deg_sparse(const at::Tensor & self); +TORCH_API at::Tensor & rad2deg_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & rad2deg_sparse_(at::Tensor & self); +TORCH_API at::Tensor rad2deg_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & rad2deg_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & rad2deg_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rand_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rand_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7330c5fe351fb660425366c5b95c58cb1f9bae31 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rand_compositeimplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, c10::optional generator); +TORCH_API at::Tensor & rand_outf(at::IntArrayRef size, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, c10::optional generator); +TORCH_API at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, c10::optional generator, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/randperm_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/randperm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9e05664557314917366f0a048f647dbd4be01652 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/randperm_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor randperm(int64_t n, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & randperm_out(int64_t n, at::Tensor & out); +TORCH_API at::Tensor randperm(int64_t n, c10::optional generator, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & randperm_out_cpu(int64_t n, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor & randperm_out_cuda(int64_t n, c10::optional generator, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad1d_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad1d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..00228f75958c9f5c739e52fbb7b91d4c15a9769e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad1d_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor reflection_pad1d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & reflection_pad1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/renorm_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/renorm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..271484811cc132499731622794f08814d6e51b3f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/renorm_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_renorm_out : public at::meta::structured_renorm { +void impl(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad2d_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0c1f60f5abe016b699355e08f4c1f142c660f156 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad2d_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API replication_pad2d_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::replication_pad2d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "replication_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); +}; + +struct TORCH_API replication_pad2d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::replication_pad2d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "replication_pad2d(Tensor self, SymInt[4] padding) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/smooth_l1_loss_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/smooth_l1_loss_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8c6fdde84b89dcb823d2780e454327577281a142 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/smooth_l1_loss_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor smooth_l1_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double beta=1.0); +TORCH_API at::Tensor & smooth_l1_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double beta=1.0); +TORCH_API at::Tensor & smooth_l1_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sort_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sort_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9cd0612fbaad6c1491c6484e4d12a1e2bba2ba6a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sort_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple sort(const at::Tensor & self, at::Dimname dim, bool descending=false); +TORCH_API ::std::tuple sort_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool descending=false); +TORCH_API ::std::tuple sort_outf(const at::Tensor & self, at::Dimname dim, bool descending, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple sort(const at::Tensor & self, c10::optional stable, at::Dimname dim, bool descending=false); +TORCH_API ::std::tuple sort_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::optional stable, at::Dimname dim, bool descending=false); +TORCH_API ::std::tuple sort_outf(const at::Tensor & self, c10::optional stable, at::Dimname dim, bool descending, at::Tensor & values, at::Tensor & indices); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..d45c7d9ee21e232c6e0c3ec3d454262f7a6707ad --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_chebyshev_polynomial_t : public TensorIteratorBase { + + + void meta(const at::Tensor & x, const at::Tensor & n); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w.h new file mode 100644 index 0000000000000000000000000000000000000000..bd4dc7c3904e86e84e63eb50535e9e6df94ea1a1 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_w.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_chebyshev_polynomial_w(Tensor x, Tensor n) -> Tensor +inline at::Tensor special_chebyshev_polynomial_w(const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_w::call(x, n); +} + +// aten::special_chebyshev_polynomial_w.x_scalar(Scalar x, Tensor n) -> Tensor +inline at::Tensor special_chebyshev_polynomial_w(const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_w_x_scalar::call(x, n); +} + +// aten::special_chebyshev_polynomial_w.n_scalar(Tensor x, Scalar n) -> Tensor +inline at::Tensor special_chebyshev_polynomial_w(const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_chebyshev_polynomial_w_n_scalar::call(x, n); +} + +// aten::special_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_w_out::call(x, n, out); +} +// aten::special_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_chebyshev_polynomial_w_out::call(x, n, out); +} + +// aten::special_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_chebyshev_polynomial_w_x_scalar_out::call(x, n, out); +} +// aten::special_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_chebyshev_polynomial_w_x_scalar_out::call(x, n, out); +} + +// aten::special_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_chebyshev_polynomial_w_n_scalar_out::call(x, n, out); +} +// aten::special_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_chebyshev_polynomial_w_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { + return at::_ops::special_chebyshev_polynomial_w_n_scalar_out::call(x, n, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_log1p.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_log1p.h new file mode 100644 index 0000000000000000000000000000000000000000..06d83f91b0e0d7a56ec1ec5f7caa5940d9f8ebd7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_log1p.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_log1p(Tensor self) -> Tensor +inline at::Tensor special_log1p(const at::Tensor & self) { + return at::_ops::special_log1p::call(self); +} + +// aten::special_log1p.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_log1p_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_log1p_out::call(self, out); +} +// aten::special_log1p.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_log1p_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_log1p_out::call(self, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..178225d062c9cde23f22d4c53cbe47d889924228 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_modified_bessel_i1(const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_xlog1py_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_xlog1py_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..5c20a02a5a3d94700bdfc3ca635e854bd44f83d0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_xlog1py_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_xlog1py : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/std_mean_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/std_mean_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dec364e687427a1546e8d767fe7776e905a3de2f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/std_mean_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple std_mean_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, at::OptionalIntArrayRef dim=c10::nullopt, const c10::optional & correction=c10::nullopt, bool keepdim=false); +TORCH_API ::std::tuple std_mean_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, const c10::optional & correction, bool keepdim, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_constrain_range_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_constrain_range_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..74d30815471bcfe303fd85c097fa5f9fda4f88ee --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_constrain_range_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sym_constrain_range { + using schema = void (const at::Scalar &, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sym_constrain_range") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sym_constrain_range(Scalar size, *, int? min=None, int? max=None) -> ()") + static void call(const at::Scalar & size, c10::optional min, c10::optional max); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & size, c10::optional min, c10::optional max); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_size_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44634d72c4541d512729ac492766758ccfc3c657 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_size_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API c10::SymInt sym_size(const at::Tensor & self, int64_t dim); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tanh_backward_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tanh_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..22a1209a52adf3814701f3f60b22ace6de2fb8cc --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tanh_backward_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_tanh_backward : public TensorIteratorBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & output); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tanh_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tanh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..729c490a0328035dea4e34daaf771e63954c842a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tanh_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor tanh(const at::Tensor & self); +TORCH_API at::Tensor & tanh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & tanh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & tanh_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..12c2ca49bb344b59345d2f281530afca9350a2e4 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/trunc.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/trunc.h new file mode 100644 index 0000000000000000000000000000000000000000..a04023cd657db06b9b1d262c23ce6e2b7a2efc4d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/trunc.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::trunc(Tensor self) -> Tensor +inline at::Tensor trunc(const at::Tensor & self) { + return at::_ops::trunc::call(self); +} + +// aten::trunc_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & trunc_(at::Tensor & self) { + return at::_ops::trunc_::call(self); +} + +// aten::trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & trunc_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::trunc_out::call(self, out); +} +// aten::trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & trunc_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::trunc_out::call(self, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..95cd64face574b0c6e026a1b91b4ddc2a7c93554 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API unsafe_split_Tensor { + using schema = ::std::vector (const at::Tensor &, c10::SymInt, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::unsafe_split") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "unsafe_split.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[]") + static ::std::vector call(const at::Tensor & self, c10::SymInt split_size, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim); +}; + +struct TORCH_API unsafe_split_Tensor_out { + using schema = void (const at::Tensor &, c10::SymInt, int64_t, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::unsafe_split") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> ()") + static void call(const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1049b7b4874e7f50311bef4b819d0f79a3bf15fe --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & vdot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & vdot_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at