diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_backward_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8a192cb8630f67a4120da9443dccc94c583b924b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API void _backward(const at::Tensor & self, at::TensorList inputs, const c10::optional & gradient={}, c10::optional retain_graph=c10::nullopt, bool create_graph=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_double_backward_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_double_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1c0ad3879b658222bdbbe956c86301c46621b8a0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_double_backward_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _convolution_double_backward(const c10::optional & ggI, const c10::optional & ggW, const c10::optional & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..327d4612ee4c22149de11a457f94c84a76ac9c6d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _embedding_bag_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymInt, bool, int64_t, bool, const c10::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_embedding_bag_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor") + static at::Tensor call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, int64_t padding_idx); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, int64_t padding_idx); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ac1683c7b80cdfa64cb57aa44524de9b83c4bdc8 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_abs_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void _foreach_abs_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_abs_outf(at::TensorList self, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e9afa44536c8f8fc7bf0fd93c58202fc92c00530 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_add_native.h @@ -0,0 +1,40 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void _foreach_add_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API ::std::vector foreach_tensor_add_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_add_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_add_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_add_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_add_List_out(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +TORCH_API ::std::vector foreach_tensor_add_list_kernel_slow(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void foreach_tensor_add_list_kernel_slow_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector foreach_tensor_add_list_kernel_cuda(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void foreach_tensor_add_list_kernel_cuda_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_add_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API ::std::vector foreach_tensor_add_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_add_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_add_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_add_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_add_Tensor_out(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha, at::TensorList out); +TORCH_API ::std::vector foreach_tensor_add_tensor_kernel_slow(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API void foreach_tensor_add_tensor_kernel_slow_(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API ::std::vector foreach_tensor_add_tensor_kernel_cuda(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API void foreach_tensor_add_tensor_kernel_cuda_(at::TensorList self, const at::Tensor & other, const at::Scalar & alpha=1); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0e23be16a45c5d84168a701937942fb4fcc7a3f9 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bf5db61e25d93e07963945d6ad690e81dca92397 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_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 ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..61acf4f14a5523bf81aeeeccce4ad1ae1538dfba --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_asin_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_asin(at::TensorList self); +TORCH_API void _foreach_asin_(at::TensorList self); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..025e9316e836822a6b73c145edb90ed52cab0c64 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_lgamma_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void _foreach_lgamma_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_lgamma_outf(at::TensorList self, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..00360daac7ed49fbf5745313dcfea321c0fd3a87 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_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_sinh(at::TensorList self); +TORCH_API void _foreach_sinh_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c9b1bfcd1f037556aca59dd99dd8f7b236a859b2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_ops.h @@ -0,0 +1,116 @@ +#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_sub_Scalar { + using schema = ::std::vector (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_sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sub.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]") + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_sub__Scalar { + using schema = void (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_sub_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sub_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()") + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_sub_List { + 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_sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "List") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[]") + static ::std::vector call(at::TensorList self, at::TensorList other, const at::Scalar & alpha); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_sub__List { + 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_sub_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "List") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> ()") + static void call(at::TensorList self, at::TensorList other, const at::Scalar & alpha); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha); +}; + +struct TORCH_API _foreach_sub_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ScalarList") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]") + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_sub__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_sub_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ScalarList") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()") + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_sub_Scalar_out { + using schema = void (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_sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_sub_List_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_sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "List_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out); +}; + +struct TORCH_API _foreach_sub_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, 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_sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ScalarList_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..837cbdb157ace79160d6103c1730e8fffb7dbaa7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _fw_primal_copy(const at::Tensor & self, int64_t level); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..99991535d51e614607e63137b027e065bed49f06 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_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 bool _has_compatible_shallow_copy_type(const at::Tensor & self, const at::Tensor & from); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_det_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_det_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e12eafccb489d355d79922077d8acb44e99b615 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_det_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 ::std::tuple _linalg_det(const at::Tensor & A); +TORCH_API ::std::tuple _linalg_det_out(at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, const at::Tensor & A); +TORCH_API ::std::tuple _linalg_det_outf(const at::Tensor & A, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_masked_softmax_backward_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_masked_softmax_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4a316c0b4b76ca4f9fc4835cbeddfc5f625114ba --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_masked_softmax_backward_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 _masked_softmax_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & mask, c10::optional dim=c10::nullopt); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_neg_view_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_neg_view_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..37530952213f8af0b831467f6a5638b54e03bdc3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_neg_view_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 at::Tensor _neg_view(const at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_rowwise_prune_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_rowwise_prune_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b9996b919a40c75266c9bdfe0f1c637bb4a24e47 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_rowwise_prune_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 _rowwise_prune { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_rowwise_prune") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_rowwise_prune(Tensor weight, Tensor mask, ScalarType compressed_indices_dtype) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & weight, const at::Tensor & mask, at::ScalarType compressed_indices_dtype); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & mask, at::ScalarType compressed_indices_dtype); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_saturate_weight_to_fp16_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_saturate_weight_to_fp16_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1f2c1b55c5bca6ead5de91db2c3cc36a1d314e20 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_saturate_weight_to_fp16_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 _saturate_weight_to_fp16 { + 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::_saturate_weight_to_fp16") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_saturate_weight_to_fp16(Tensor weight) -> Tensor") + static at::Tensor call(const at::Tensor & weight); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..80890bfaa5d8d6d0a003b9595d2c5c3b30ea6ddf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_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 _scaled_dot_product_flash_attention(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, c10::optional scale=c10::nullopt); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_csr_tensor_unsafe.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_csr_tensor_unsafe.h new file mode 100644 index 0000000000000000000000000000000000000000..55846b6e2bb1be7b3f495059cdece2b87b4b1d28 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_csr_tensor_unsafe.h @@ -0,0 +1,34 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_csr_tensor_unsafe(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_csr_tensor_unsafe(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_sparse_csr_tensor_unsafe::call(crow_indices, col_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::_sparse_csr_tensor_unsafe(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_csr_tensor_unsafe(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::_sparse_csr_tensor_unsafe::call(crow_indices, col_indices, values, size, dtype, layout, device, pin_memory); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_standard_gamma_grad.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_standard_gamma_grad.h new file mode 100644 index 0000000000000000000000000000000000000000..b10ee2d60b85f10e1de83c5194bb1b7645d41269 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_standard_gamma_grad.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::_standard_gamma_grad(Tensor self, Tensor output) -> Tensor +inline at::Tensor _standard_gamma_grad(const at::Tensor & self, const at::Tensor & output) { + return at::_ops::_standard_gamma_grad::call(self, output); +} + +// aten::_standard_gamma_grad.out(Tensor self, Tensor output, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _standard_gamma_grad_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & output) { + return at::_ops::_standard_gamma_grad_out::call(self, output, out); +} +// aten::_standard_gamma_grad.out(Tensor self, Tensor output, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _standard_gamma_grad_outf(const at::Tensor & self, const at::Tensor & output, at::Tensor & out) { + return at::_ops::_standard_gamma_grad_out::call(self, output, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_serialization_subcmul_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_serialization_subcmul_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..eb6dc75b3cb97cf591f4cc7672de6cb56eb8a14f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_serialization_subcmul_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 _test_serialization_subcmul { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_test_serialization_subcmul") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_serialization_subcmul(Tensor self, Tensor other, Scalar alpha=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..d069aeea25e4ae5adf608e7a289c1a50fdaad61c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_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_nearest_exact3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_nearest_exact3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_nearest_exact3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_nearest_exact3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_nearest_exact3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_nearest_exact3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_nearest_exact3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact3d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_nearest_exact3d_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_nearest_exact3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_nearest_exact3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_nearest_exact3d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor _upsample_nearest_exact3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_nearest_exact3d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w); + } +} + +// aten::_upsample_nearest_exact3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_nearest_exact3d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_nearest_exact3d_backward::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor _upsample_nearest_exact3d_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::_upsample_nearest_exact3d_backward::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fb791ade54edefa89b33384498c10e2f819f80d5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API ::std::tuple adaptive_max_pool3d(const at::Tensor & self, at::IntArrayRef output_size); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/amax.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/amax.h new file mode 100644 index 0000000000000000000000000000000000000000..193d377398c84884a9691bcb98520948b78b13fb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/amax.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::amax(Tensor self, int[1] dim=[], bool keepdim=False) -> Tensor +inline at::Tensor amax(const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false) { + return at::_ops::amax::call(self, dim, keepdim); +} + +// aten::amax.out(Tensor self, int[1] dim=[], bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & amax_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false) { + return at::_ops::amax_out::call(self, dim, keepdim, out); +} +// aten::amax.out(Tensor self, int[1] dim=[], bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & amax_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { + return at::_ops::amax_out::call(self, dim, keepdim, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/atanh.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/atanh.h new file mode 100644 index 0000000000000000000000000000000000000000..ef8f623d81ced109acccd04e7f1420cdbff3ad4a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/atanh.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::atanh(Tensor self) -> Tensor +inline at::Tensor atanh(const at::Tensor & self) { + return at::_ops::atanh::call(self); +} + +// aten::atanh_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & atanh_(at::Tensor & self) { + return at::_ops::atanh_::call(self); +} + +// aten::atanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atanh_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::atanh_out::call(self, out); +} +// aten::atanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atanh_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::atanh_out::call(self, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_stats_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_stats_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8cccc5161ee51d88e2db99dca34ff66462da036f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_stats_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 batch_norm_stats_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & input, double eps); +TORCH_API ::std::tuple batch_norm_stats_outf(const at::Tensor & input, double eps, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/bmm_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/bmm_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..81ef8f49f347021549da10b30576e58c7b3d67e3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/bmm_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor bmm(const at::Tensor & self, const at::Tensor & mat2); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cosh_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cosh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..eb671173d21101742e86a95d36dc90dc2c2e2ee1 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cosh_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 cosh { + 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::cosh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cosh(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 cosh_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cosh_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cosh_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API cosh_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::cosh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cosh.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/cross_entropy_loss.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cross_entropy_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..6b55ff56f0017e833d56b1f14a8e2532dd5271da --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cross_entropy_loss.h @@ -0,0 +1,47 @@ +#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::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, float label_smoothing=0.0) -> Tensor +inline at::Tensor cross_entropy_loss(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean, int64_t ignore_index=-100, double label_smoothing=0.0) { + return at::_ops::cross_entropy_loss::call(self, target, weight, reduction, ignore_index, label_smoothing); +} +namespace symint { + template ::value>> + at::Tensor cross_entropy_loss(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean, int64_t ignore_index=-100, double label_smoothing=0.0) { + return at::_ops::cross_entropy_loss::call(self, target, weight, reduction, ignore_index, label_smoothing); + } +} + +// aten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, float label_smoothing=0.0) -> Tensor +inline at::Tensor cross_entropy_loss_symint(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean, c10::SymInt ignore_index=-100, double label_smoothing=0.0) { + return at::_ops::cross_entropy_loss::call(self, target, weight, reduction, ignore_index, label_smoothing); +} +namespace symint { + template ::value>> + at::Tensor cross_entropy_loss(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean, c10::SymInt ignore_index=-100, double label_smoothing=0.0) { + return at::_ops::cross_entropy_loss::call(self, target, weight, reduction, ignore_index, label_smoothing); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_backward_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6065622b0f1419b0ab221c4171b93e0bc1023ec3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor diagonal_backward(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +TORCH_API at::Tensor diagonal_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +TORCH_API at::Tensor & diagonal_backward_out(at::Tensor & out, const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +TORCH_API at::Tensor & diagonal_backward_outf(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); +TORCH_API at::Tensor & diagonal_backward_symint_out(at::Tensor & out, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +TORCH_API at::Tensor & diagonal_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/empty_like.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/empty_like.h new file mode 100644 index 0000000000000000000000000000000000000000..f60e0b8776ff5d4fe7ac355b7b9319a5b2d8c2a5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/empty_like.h @@ -0,0 +1,43 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::empty_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor empty_like(const at::Tensor & self, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt) { + return at::_ops::empty_like::call(self, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +// aten::empty_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor empty_like(const at::Tensor & self, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format) { + return at::_ops::empty_like::call(self, dtype, layout, device, pin_memory, memory_format); +} + +// aten::empty_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & empty_like_out(at::Tensor & out, const at::Tensor & self, c10::optional memory_format=c10::nullopt) { + return at::_ops::empty_like_out::call(self, memory_format, out); +} +// aten::empty_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & empty_like_outf(const at::Tensor & self, c10::optional memory_format, at::Tensor & out) { + return at::_ops::empty_like_out::call(self, memory_format, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/empty_strided_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/empty_strided_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fd3a1d44caf0941417c7f1b9c9d122e4c77a0336 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/empty_strided_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API empty_strided { + using schema = at::Tensor (c10::SymIntArrayRef, c10::SymIntArrayRef, c10::optional, 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::empty_strided") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "empty_strided(SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +}; + +struct TORCH_API empty_strided_out { + using schema = at::Tensor & (c10::SymIntArrayRef, 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::empty_strided") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "empty_strided.out(SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/exp.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/exp.h new file mode 100644 index 0000000000000000000000000000000000000000..7c71dd13fcc89dd54e1d47d7991d518b5a48679e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/exp.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::exp(Tensor self) -> Tensor +inline at::Tensor exp(const at::Tensor & self) { + return at::_ops::exp::call(self); +} + +// aten::exp_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & exp_(at::Tensor & self) { + return at::_ops::exp_::call(self); +} + +// aten::exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & exp_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::exp_out::call(self, out); +} +// aten::exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & exp_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::exp_out::call(self, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/exp2_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/exp2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..957976aea53b2c6e591d42b48fa23830351e7186 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/exp2_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 exp2 { + 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::exp2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "exp2(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 exp2_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::exp2_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "exp2_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API exp2_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::exp2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "exp2.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/fake_quantize_per_tensor_affine_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_native.h new file mode 100644 index 0000000000000000000000000000000000000000..52b775a61a833014a934aebbc6f6bece66c8293f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_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 fake_quantize_per_tensor_affine(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max); +TORCH_API at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fliplr_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fliplr_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9ee54af05f3c9af5ebd95544f733b4e69c746e83 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fliplr_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 fliplr { + 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::fliplr") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fliplr(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/geqrf_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/geqrf_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a6f18f26a9b422ba359fdbf1dbb9e6acfdb5e35 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/geqrf_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple geqrf(const at::Tensor & self); +TORCH_API ::std::tuple geqrf_out(at::Tensor & a, at::Tensor & tau, const at::Tensor & self); +TORCH_API ::std::tuple geqrf_outf(const at::Tensor & self, at::Tensor & a, at::Tensor & tau); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/greater_equal_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/greater_equal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ade497a68beb97a1fa52691e6790f05358b65f3a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/greater_equal_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & greater_equal_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & greater_equal_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & greater_equal_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & greater_equal_(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/index_copy_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/index_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..60fdbe6930a37e428bfaa7e238ed6c6d95b084ce --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/index_copy_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 +#include + +namespace at { +namespace native { +struct TORCH_API structured_index_copy_out : public at::meta::structured_index_copy { +void impl(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Tensor & out); +}; +TORCH_API at::Tensor & index_copy_(at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source); +TORCH_API at::Tensor index_copy(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/is_nonzero_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/is_nonzero_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6985552fa21a5903ee26a765baeeb81f02c19aff --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/is_nonzero_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API is_nonzero { + using schema = bool (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::is_nonzero") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "is_nonzero(Tensor self) -> bool") + static bool call(const at::Tensor & self); + static bool 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/istft.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/istft.h new file mode 100644 index 0000000000000000000000000000000000000000..97744e4cd48ac0f5494c2c197f01d4663d407519 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/istft.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::istft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool center=True, bool normalized=False, bool? onesided=None, int? length=None, bool return_complex=False) -> Tensor +inline at::Tensor istft(const at::Tensor & self, int64_t n_fft, c10::optional hop_length=c10::nullopt, c10::optional win_length=c10::nullopt, const c10::optional & window={}, bool center=true, bool normalized=false, c10::optional onesided=c10::nullopt, c10::optional length=c10::nullopt, bool return_complex=false) { + return at::_ops::istft::call(self, n_fft, hop_length, win_length, window, center, normalized, onesided, length, return_complex); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/kaiser_window_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/kaiser_window_native.h new file mode 100644 index 0000000000000000000000000000000000000000..006ba4dac47872057c3ca61e5cec022f5377d806 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/kaiser_window_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor kaiser_window(int64_t window_length, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & kaiser_window_out(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & kaiser_window_periodic_out(int64_t window_length, bool periodic, at::Tensor & out); +TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, double beta, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & kaiser_window_beta_out(int64_t window_length, bool periodic, double beta, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/lerp_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/lerp_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c236873f881c152b00dd9fe191329df719486f0a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/lerp_compositeexplicitautogradnonfunctional_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 compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor lerp(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +TORCH_API at::Tensor & lerp_(at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +TORCH_API at::Tensor lerp(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); +TORCH_API at::Tensor & lerp_(at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/lgamma_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/lgamma_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..9a7e1f2ac3f16dcee4786d1752184e6f05d3937b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/lgamma_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_lgamma : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log2_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log2_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f885a233fbed2c46b8d73c615b32dc327be5cae5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log2_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor log2(const at::Tensor & self); +TORCH_API at::Tensor & log2_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & log2_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & log2_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mish.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mish.h new file mode 100644 index 0000000000000000000000000000000000000000..477141a7e12bf7382059b1e5b38b1cb7e143620a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mish.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::mish(Tensor self) -> Tensor +inline at::Tensor mish(const at::Tensor & self) { + return at::_ops::mish::call(self); +} + +// aten::mish_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & mish_(at::Tensor & self) { + return at::_ops::mish_::call(self); +} + +// aten::mish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mish_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::mish_out::call(self, out); +} +// aten::mish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & mish_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::mish_out::call(self, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bde301cc371ac8c109799990542656f18b6b3d98 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mode_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 ::std::tuple mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f0a1f10a46a03d544a331e7795f66503a1e825d8 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_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 multinomial(const at::Tensor & self, int64_t num_samples, bool replacement=false, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, int64_t num_samples, bool replacement=false, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & multinomial_outf(const at::Tensor & self, int64_t num_samples, bool replacement, c10::optional generator, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_native.h new file mode 100644 index 0000000000000000000000000000000000000000..22d5ef1e9703e98b9b562e5d1cd80dcb4e5b27e0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nanmean_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 nanmean(const at::Tensor & self, at::OptionalIntArrayRef dim=c10::nullopt, bool keepdim=false, c10::optional dtype=c10::nullopt); +TORCH_API at::Tensor & nanmean_out(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional dtype, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/neg_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/neg_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..690d24220b768a96ea9c14035037407b5bcbb617 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/neg_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 neg(const at::Tensor & self); +TORCH_API at::Tensor & neg_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & neg_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & neg_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nonzero_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nonzero_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80a2822eae34421ac1a5ccaedfa5157ae3e57017 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nonzero_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 nonzero_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::nonzero") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nonzero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API nonzero { + 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::nonzero") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nonzero(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/normal_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/normal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..003ec71f62360b5a1e24f28ee7b34adbca164db6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/normal_native.h @@ -0,0 +1,40 @@ +#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 normal_functional(const at::Tensor & self, double mean=0, double std=1, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_out(const at::Tensor & self, double mean, double std, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor & normal_(at::Tensor & self, double mean=0, double std=1, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_nested_(at::Tensor & self, double mean=0, double std=1, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_sparse_csr_(at::Tensor & self, double mean=0, double std=1, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_meta_(at::Tensor & self, double mean=0, double std=1, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor normal(const at::Tensor & mean, double std=1, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_out(const at::Tensor & mean, double std, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal_meta(const at::Tensor & mean, double std=1, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_out_meta(const at::Tensor & mean, double std, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(double mean, const at::Tensor & std, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_out(double mean, const at::Tensor & std, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal_meta(double mean, const at::Tensor & std, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_out_meta(double mean, const at::Tensor & std, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(const at::Tensor & mean, const at::Tensor & std, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_out(const at::Tensor & mean, const at::Tensor & std, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal_meta(const at::Tensor & mean, const at::Tensor & std, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & normal_out_meta(const at::Tensor & mean, const at::Tensor & std, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(double mean, double std, at::IntArrayRef size, c10::optional generator=c10::nullopt, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & normal_out(double mean, double std, at::IntArrayRef size, c10::optional generator, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/prelu_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/prelu_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..15753a36ddb31bbf04ea3432d342f5bf3456c69b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/prelu_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor prelu(const at::Tensor & self, const at::Tensor & weight); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/randint_like.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/randint_like.h new file mode 100644 index 0000000000000000000000000000000000000000..4d9b50d01f3c9d7948f1e57b5037990c786c5050 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/randint_like.h @@ -0,0 +1,201 @@ +#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::randint_like(Tensor self, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t high, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like::call(self, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template ::value>> + at::Tensor randint_like(const at::Tensor & self, int64_t high, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like::call(self, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like(Tensor self, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t high, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format) { + return at::_ops::randint_like::call(self, high, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template ::value>> + at::Tensor randint_like(const at::Tensor & self, int64_t high, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format) { + return at::_ops::randint_like::call(self, high, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like(Tensor self, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt high, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like::call(self, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template ::value>> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt high, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like::call(self, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like(Tensor self, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt high, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format) { + return at::_ops::randint_like::call(self, high, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template ::value>> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt high, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format) { + return at::_ops::randint_like::call(self, high, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.low_dtype(Tensor self, SymInt low, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_low_dtype::call(self, low, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template ::value>> + at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_low_dtype::call(self, low, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like.low_dtype(Tensor self, SymInt low, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format) { + return at::_ops::randint_like_low_dtype::call(self, low, high, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template ::value>> + at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format) { + return at::_ops::randint_like_low_dtype::call(self, low, high, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.low_dtype(Tensor self, SymInt low, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt low, c10::SymInt high, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_low_dtype::call(self, low, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template ::value>> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt low, c10::SymInt high, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_low_dtype::call(self, low, high, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::randint_like.low_dtype(Tensor self, SymInt low, SymInt high, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor +inline at::Tensor randint_like_symint(const at::Tensor & self, c10::SymInt low, c10::SymInt high, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format) { + return at::_ops::randint_like_low_dtype::call(self, low, high, dtype, layout, device, pin_memory, memory_format); +} +namespace symint { + template ::value>> + at::Tensor randint_like(const at::Tensor & self, c10::SymInt low, c10::SymInt high, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format) { + return at::_ops::randint_like_low_dtype::call(self, low, high, dtype, layout, device, pin_memory, memory_format); + } +} + +// aten::randint_like.out(Tensor self, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t high, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t high, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); + } +} + +// aten::randint_like.out(Tensor self, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_outf(const at::Tensor & self, int64_t high, c10::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & randint_like_outf(const at::Tensor & self, int64_t high, c10::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); + } +} + +// aten::randint_like.out(Tensor self, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt high, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, c10::SymInt high, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); + } +} + +// aten::randint_like.out(Tensor self, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_outf(const at::Tensor & self, c10::SymInt high, c10::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & randint_like_outf(const at::Tensor & self, c10::SymInt high, c10::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_out::call(self, high, memory_format, out); + } +} + +// aten::randint_like.low_dtype_out(Tensor self, SymInt low, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t low, int64_t high, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, int64_t low, int64_t high, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); + } +} + +// aten::randint_like.low_dtype_out(Tensor self, SymInt low, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_outf(const at::Tensor & self, int64_t low, int64_t high, c10::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & randint_like_outf(const at::Tensor & self, int64_t low, int64_t high, c10::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); + } +} + +// aten::randint_like.low_dtype_out(Tensor self, SymInt low, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt low, c10::SymInt high, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & randint_like_out(at::Tensor & out, const at::Tensor & self, c10::SymInt low, c10::SymInt high, c10::optional memory_format=c10::nullopt) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); + } +} + +// aten::randint_like.low_dtype_out(Tensor self, SymInt low, SymInt high, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randint_like_symint_outf(const at::Tensor & self, c10::SymInt low, c10::SymInt high, c10::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & randint_like_outf(const at::Tensor & self, c10::SymInt low, c10::SymInt high, c10::optional memory_format, at::Tensor & out) { + return at::_ops::randint_like_low_dtype_out::call(self, low, high, memory_format, out); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/random_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/random_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4c12198695e108160da0897ba9c431f80b839250 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/random_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 & random_(at::Tensor & self, int64_t from, c10::optional to, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & random_(at::Tensor & self, int64_t to, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & random_(at::Tensor & self, c10::optional generator=c10::nullopt); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/repeat_interleave.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/repeat_interleave.h new file mode 100644 index 0000000000000000000000000000000000000000..36c47352ba6a66ee439a3a788f0e06f69be8dbee --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/repeat_interleave.h @@ -0,0 +1,135 @@ +#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::repeat_interleave.Tensor(Tensor repeats, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave(const at::Tensor & repeats, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_Tensor::call(repeats, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt); +} +namespace symint { + template ::value>> + at::Tensor repeat_interleave(const at::Tensor & repeats, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_Tensor::call(repeats, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt); + } +} + +// aten::repeat_interleave.Tensor(Tensor repeats, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave_symint(const at::Tensor & repeats, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_Tensor::call(repeats, output_size); +} +namespace symint { + template ::value>> + at::Tensor repeat_interleave(const at::Tensor & repeats, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_Tensor::call(repeats, output_size); + } +} + +// aten::repeat_interleave.self_Tensor(Tensor self, Tensor repeats, int? dim=None, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave(const at::Tensor & self, const at::Tensor & repeats, c10::optional dim=c10::nullopt, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_self_Tensor::call(self, repeats, dim, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt); +} +namespace symint { + template ::value>> + at::Tensor repeat_interleave(const at::Tensor & self, const at::Tensor & repeats, c10::optional dim=c10::nullopt, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_self_Tensor::call(self, repeats, dim, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt); + } +} + +// aten::repeat_interleave.self_Tensor(Tensor self, Tensor repeats, int? dim=None, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave_symint(const at::Tensor & self, const at::Tensor & repeats, c10::optional dim=c10::nullopt, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_self_Tensor::call(self, repeats, dim, output_size); +} +namespace symint { + template ::value>> + at::Tensor repeat_interleave(const at::Tensor & self, const at::Tensor & repeats, c10::optional dim=c10::nullopt, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_self_Tensor::call(self, repeats, dim, output_size); + } +} + +// aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave(const at::Tensor & self, int64_t repeats, c10::optional dim=c10::nullopt, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_self_int::call(self, repeats, dim, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt); +} +namespace symint { + template ::value>> + at::Tensor repeat_interleave(const at::Tensor & self, int64_t repeats, c10::optional dim=c10::nullopt, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_self_int::call(self, repeats, dim, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt); + } +} + +// aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, SymInt? output_size=None) -> Tensor +inline at::Tensor repeat_interleave_symint(const at::Tensor & self, c10::SymInt repeats, c10::optional dim=c10::nullopt, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_self_int::call(self, repeats, dim, output_size); +} +namespace symint { + template ::value>> + at::Tensor repeat_interleave(const at::Tensor & self, c10::SymInt repeats, c10::optional dim=c10::nullopt, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_self_int::call(self, repeats, dim, output_size); + } +} + +// aten::repeat_interleave.Tensor_out(Tensor repeats, *, SymInt? output_size=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & repeat_interleave_out(at::Tensor & out, const at::Tensor & repeats, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt, out); +} +namespace symint { + template ::value>> + at::Tensor & repeat_interleave_out(at::Tensor & out, const at::Tensor & repeats, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt, out); + } +} + +// aten::repeat_interleave.Tensor_out(Tensor repeats, *, SymInt? output_size=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & repeat_interleave_outf(const at::Tensor & repeats, c10::optional output_size, at::Tensor & out) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt, out); +} +namespace symint { + template ::value>> + at::Tensor & repeat_interleave_outf(const at::Tensor & repeats, c10::optional output_size, at::Tensor & out) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size.has_value() ? c10::make_optional(c10::SymInt(*output_size)) : c10::nullopt, out); + } +} + +// aten::repeat_interleave.Tensor_out(Tensor repeats, *, SymInt? output_size=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & repeat_interleave_symint_out(at::Tensor & out, const at::Tensor & repeats, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size, out); +} +namespace symint { + template ::value>> + at::Tensor & repeat_interleave_out(at::Tensor & out, const at::Tensor & repeats, c10::optional output_size=c10::nullopt) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size, out); + } +} + +// aten::repeat_interleave.Tensor_out(Tensor repeats, *, SymInt? output_size=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & repeat_interleave_symint_outf(const at::Tensor & repeats, c10::optional output_size, at::Tensor & out) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size, out); +} +namespace symint { + template ::value>> + at::Tensor & repeat_interleave_outf(const at::Tensor & repeats, c10::optional output_size, at::Tensor & out) { + return at::_ops::repeat_interleave_Tensor_out::call(repeats, output_size, out); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rrelu_with_noise_backward.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rrelu_with_noise_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..9d652d0c281bdafcc2758ea46c734889a9b92edb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rrelu_with_noise_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::rrelu_with_noise_backward(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result) -> Tensor +inline at::Tensor rrelu_with_noise_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result) { + return at::_ops::rrelu_with_noise_backward::call(grad_output, self, noise, lower, upper, training, self_is_result); +} + +// aten::rrelu_with_noise_backward.out(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rrelu_with_noise_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result) { + return at::_ops::rrelu_with_noise_backward_out::call(grad_output, self, noise, lower, upper, training, self_is_result, out); +} +// aten::rrelu_with_noise_backward.out(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rrelu_with_noise_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result, at::Tensor & out) { + return at::_ops::rrelu_with_noise_backward_out::call(grad_output, self, noise, lower, upper, training, self_is_result, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..77d72373651e551df5654b3440119ad2ba181f5a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_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 slow_conv_dilated3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor slow_conv_dilated3d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const c10::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/soft_margin_loss_backward_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/soft_margin_loss_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6044e0969ba6848205c5ea7813907ac565c76c64 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/soft_margin_loss_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 soft_margin_loss_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::soft_margin_loss_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "grad_input") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "soft_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); +}; + +struct TORCH_API soft_margin_loss_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::soft_margin_loss_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "soft_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_mask_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_mask_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a5e86ec3122dfbf1dbf2af1e18e931558ac81434 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_mask_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 sparse_mask { + 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::sparse_mask") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sparse_mask(Tensor self, Tensor mask) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & mask); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask); +}; + +struct TORCH_API sparse_mask_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::sparse_mask") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sparse_mask.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_i0e_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_i0e_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..6de4593cf0007f4aec805b0ad9b9539f829899b3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_i0e_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_i0e : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_round.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_round.h new file mode 100644 index 0000000000000000000000000000000000000000..7a07125cbf1bc15f6416794ae2a5f7a7debad7dc --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_round.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_round(Tensor self, *, int decimals=0) -> Tensor +inline at::Tensor special_round(const at::Tensor & self, int64_t decimals=0) { + return at::_ops::special_round::call(self, decimals); +} + +// aten::special_round.out(Tensor self, *, int decimals=0, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_round_out(at::Tensor & out, const at::Tensor & self, int64_t decimals=0) { + return at::_ops::special_round_out::call(self, decimals, out); +} +// aten::special_round.out(Tensor self, *, int decimals=0, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_round_outf(const at::Tensor & self, int64_t decimals, at::Tensor & out) { + return at::_ops::special_round_out::call(self, decimals, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_sinc_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_sinc_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..74445dc75e6b7d73b60b78926c9fd2551de451c2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_sinc_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor special_sinc(const at::Tensor & self); +TORCH_API at::Tensor & special_sinc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_sinc_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/square_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/square_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8478d8fe1378c94a2d5fff7dc8d25d9ad5f9296c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/square_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 square(const at::Tensor & self); +TORCH_API at::Tensor & square_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & square_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sub_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sub_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ff484b19f1bf1e3cea32192a2e4cad37162776ed --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sub_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor sub(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & sub_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & sub_outf(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & sub_(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f28095cff8865335712fdbfcdd4c06dfc57e5543 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor swapdims(const at::Tensor & self, int64_t dim0, int64_t dim1); +TORCH_API at::Tensor & swapdims_(at::Tensor & self, int64_t dim0, int64_t dim1); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/trace_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/trace_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1d87e5101da56c8087d383f7ba76981d8c2284f6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/trace_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 trace(const at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..63c2733ef14f9a567bbe9f108e2f4cbb8c323bd5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_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 trapz_x { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::trapz") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "x") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "trapz.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor") + static at::Tensor call(const at::Tensor & y, const at::Tensor & x, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, const at::Tensor & x, int64_t dim); +}; + +struct TORCH_API trapz_dx { + using schema = at::Tensor (const at::Tensor &, double, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::trapz") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dx") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "trapz.dx(Tensor y, *, float dx=1, int dim=-1) -> Tensor") + static at::Tensor call(const at::Tensor & y, double dx, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, double dx, int64_t dim); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..70760f9cba5efd983f6fcdf61bd43007106d842a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_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_triangular_solve : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..615866269f1ff66aae727d7e4c392bf1d2c18a05 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_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 ::std::tuple triangular_solve(const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false); +TORCH_API ::std::tuple triangular_solve_out(at::Tensor & X, at::Tensor & M, const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false); +TORCH_API ::std::tuple triangular_solve_outf(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/uniform.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/uniform.h new file mode 100644 index 0000000000000000000000000000000000000000..4d44ffd4e3f77ed411ceb4a134e6431e118893eb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/uniform.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::uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & uniform_out(at::Tensor & out, const at::Tensor & self, double from=0, double to=1, c10::optional generator=c10::nullopt) { + return at::_ops::uniform_out::call(self, from, to, generator, out); +} +// aten::uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & uniform_outf(const at::Tensor & self, double from, double to, c10::optional generator, at::Tensor & out) { + return at::_ops::uniform_out::call(self, from, to, generator, out); +} + +// aten::uniform(Tensor self, float from=0, float to=1, *, Generator? generator=None) -> Tensor +inline at::Tensor uniform(const at::Tensor & self, double from=0, double to=1, c10::optional generator=c10::nullopt) { + return at::_ops::uniform::call(self, from, to, generator); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze.h new file mode 100644 index 0000000000000000000000000000000000000000..f5efa01f8a335dfdf44863b350f2ca5a5c562039 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze.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::unsqueeze(Tensor(a) self, int dim) -> Tensor(a) +inline at::Tensor unsqueeze(const at::Tensor & self, int64_t dim) { + return at::_ops::unsqueeze::call(self, dim); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..323c083f5b5346aac90afbb5582c2c8f68aab0de --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_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 vdot(const at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_complex_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_complex_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b867f9f4f550b2bbb12b9b494a27af850fc87c46 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_complex_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 view_as_complex(const at::Tensor & self); + +} // namespace cpu +} // namespace at