diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e173e65104b68e2fae33f7b501402fcc0a21a1ef --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_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 _adaptive_avg_pool2d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor _adaptive_avg_pool2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_async_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_async_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cfdf4be4fa4dead18edb85e332dc3b67a9c09031 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_async_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 _assert_async { + using schema = void (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::_assert_async") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_assert_async(Tensor self) -> ()") + static void call(const at::Tensor & self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API _assert_async_msg { + using schema = void (const at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_assert_async") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "msg") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_assert_async.msg(Tensor self, str assert_msg) -> ()") + static void call(const at::Tensor & self, c10::string_view assert_msg); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view assert_msg); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Float_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Float_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a40f8edfc1397152c931fc33f076f8f658621373 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Float_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _cast_Float(const at::Tensor & self, bool non_blocking=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..077b8a4c0201b0dea8408721ad478b9e649ab18b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_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 _convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, c10::SymIntArrayRef, c10::SymInt, bool, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32); +}; + +struct TORCH_API _convolution_deprecated { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, at::IntArrayRef, c10::SymInt, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "deprecated") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_convolution.deprecated(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, int[] output_padding, SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled); +}; + +struct TORCH_API _convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, c10::SymIntArrayRef, c10::SymInt, bool, bool, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..13794a49fb9aeec975f9ff6a3a07d9f38355dc88 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_ctc_loss_backward_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 _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); +TORCH_API at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ed70977835f4549fb593ec4e04f6f0a362f11c8c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _embedding_bag_forward_only_out(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +TORCH_API ::std::tuple _embedding_bag_forward_only_cpu(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +TORCH_API ::std::tuple _embedding_bag_forward_only_cuda(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..deaea95755d4fe1e258d15dfeb6e2b5f316bf9a7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _embedding_bag_forward_only { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, int64_t, bool, const c10::optional &, bool, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_embedding_bag_forward_only") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_embedding_bag_forward_only(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1) -> (Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx); +}; + +struct TORCH_API _embedding_bag_forward_only_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, int64_t, bool, const c10::optional &, bool, int64_t, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_embedding_bag_forward_only") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_embedding_bag_forward_only.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))") + static ::std::tuple call(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6325ee0bc6fb94d7f358ee089e686995e31f754f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_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 _fake_quantize_learnable_per_tensor_affine_backward(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..404ef09f9ba20807eeffeb22ef366b8c8373bd17 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log2_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_log2(at::TensorList self); +TORCH_API void _foreach_log2_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e54d9524184eddcd7535a85610313c1535790958 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_minimum_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_minimum_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_minimum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_minimum.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_minimum__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_minimum_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_minimum_.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_minimum_List { + using schema = ::std::vector (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_minimum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "List") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[]") + static ::std::vector call(at::TensorList self, at::TensorList other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_minimum__List { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_minimum_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "List") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> ()") + static void call(at::TensorList self, at::TensorList other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_minimum_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_minimum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ScalarList") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_minimum.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_minimum__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_minimum_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ScalarList") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_minimum_.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_minimum_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_minimum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_minimum.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_minimum_List_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_minimum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "List_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::TensorList other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out); +}; + +struct TORCH_API _foreach_minimum_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_minimum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ScalarList_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_minimum.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/_foreach_trunc_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2e76048965ddab344ad9285f932ca154881df83e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_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_trunc(at::TensorList self); +TORCH_API void _foreach_trunc_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..deac70c306c727e074b5f636c68f23a995be3687 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _fw_primal_copy_out(at::Tensor & out, const at::Tensor & self, int64_t level); +TORCH_API at::Tensor & _fw_primal_copy_outf(const at::Tensor & self, int64_t level, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true.h new file mode 100644 index 0000000000000000000000000000000000000000..d40e5c3748f80ccd978279a6a81be09dd7b7d9be --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_is_any_true.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::_is_any_true(Tensor self) -> Tensor +inline at::Tensor _is_any_true(const at::Tensor & self) { + return at::_ops::_is_any_true::call(self); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_svd_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_svd_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2829f9c3f0b5ec74fce1c41fa4c924d0a1318709 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_svd_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 _linalg_svd(const at::Tensor & A, bool full_matrices=false, bool compute_uv=true, c10::optional driver=c10::nullopt); +TORCH_API ::std::tuple _linalg_svd_out(at::Tensor & U, at::Tensor & S, at::Tensor & Vh, const at::Tensor & A, bool full_matrices=false, bool compute_uv=true, c10::optional driver=c10::nullopt); +TORCH_API ::std::tuple _linalg_svd_outf(const at::Tensor & A, bool full_matrices, bool compute_uv, c10::optional driver, at::Tensor & U, at::Tensor & S, at::Tensor & Vh); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_from_padded_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_from_padded_native.h new file mode 100644 index 0000000000000000000000000000000000000000..02519fded2261c87f047483e858e60aa66c0078a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_from_padded_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 & _nested_from_padded_out(const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213, at::Tensor & out); +TORCH_API at::Tensor nested_from_padded_generic(const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213=false); +TORCH_API at::Tensor nested_from_padded_cuda(const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213=false); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_copy.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..58df5f06892d8e4e784d4d59a197dda98b40c1dc --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_copy.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::_reshape_copy(Tensor self, SymInt[] size) -> Tensor +inline at::Tensor _reshape_copy(const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::_reshape_copy::call(self, c10::fromIntArrayRefSlow(size)); +} +namespace symint { + template ::value>> + at::Tensor _reshape_copy(const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::_reshape_copy::call(self, c10::fromIntArrayRefSlow(size)); + } +} + +// aten::_reshape_copy(Tensor self, SymInt[] size) -> Tensor +inline at::Tensor _reshape_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::_reshape_copy::call(self, size); +} +namespace symint { + template ::value>> + at::Tensor _reshape_copy(const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::_reshape_copy::call(self, size); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..54740ced4327022e708e8ccedb7ac63c0f56fbaf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _upsample_bicubic2d_aa(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, c10::optional> scale_factors); +TORCH_API at::Tensor _upsample_bicubic2d_aa_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, c10::optional> scale_factors); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/add_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/add_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..76bdc28274e26c2993bfe226dcfbae9429e554c3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/add_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor add(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & add_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/addcmul_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/addcmul_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..5346e560bc2449dd2bd0259a11e4fd0af3d56d58 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/addcmul_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_addcmul : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/arccos_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/arccos_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0e70f1a4c4090439c9fd796d11c4cc7e8c75da66 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/arccos_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 arccos(const at::Tensor & self); +TORCH_API at::Tensor & arccos_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & arccos_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_scatter_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_scatter_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b8231436159ad9ab4fd8420175adb12e67a27cf2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_scatter_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 & as_strided_scatter_out_symint(const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional storage_offset, at::Tensor & out); +TORCH_API at::Tensor as_strided_scatter_symint(const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional storage_offset=c10::nullopt); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_scatter_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_scatter_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..30666480885b9a85b4c495333ba834a32ccee5d2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_scatter_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 as_strided_scatter { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::as_strided_scatter") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "as_strided_scatter(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional storage_offset); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional storage_offset); +}; + +struct TORCH_API as_strided_scatter_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::as_strided_scatter") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "as_strided_scatter.out(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional storage_offset, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional storage_offset, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool2d_backward.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..23f6176900f3d550f366ebd775df8f16cf6924b6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool2d_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::avg_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & avg_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override) { + return at::_ops::avg_pool2d_backward_grad_input::call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, grad_input); +} +// aten::avg_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & avg_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override, at::Tensor & grad_input) { + return at::_ops::avg_pool2d_backward_grad_input::call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, grad_input); +} + +// aten::avg_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, bool ceil_mode, bool count_include_pad, int? divisor_override) -> Tensor +inline at::Tensor avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override) { + return at::_ops::avg_pool2d_backward::call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_elemt_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_elemt_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9bcb852633608c23608b99fb457032332ff03b85 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_elemt_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 batch_norm_backward_elemt(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & weight, const at::Tensor & sum_dy, const at::Tensor & sum_dy_xmu, const at::Tensor & count); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/block_diag_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/block_diag_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0bc63c65d84860e1863e82c2c524c2188326e366 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/block_diag_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 block_diag { + using schema = at::Tensor (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::block_diag") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "block_diag(Tensor[] tensors) -> Tensor") + static at::Tensor call(at::TensorList tensors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +struct TORCH_API block_diag_out { + using schema = at::Tensor & (at::TensorList, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::block_diag") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "block_diag.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(at::TensorList tensors, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ceil_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ceil_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cf57f017c020e8183907662dd305e028dffb198a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ceil_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 ceil(const at::Tensor & self); +TORCH_API at::Tensor & ceil_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & ceil_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & ceil_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_backward_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..07937ca03e7cd598b3656f3ac57f2ffb51340fb2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_backward_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple cudnn_batch_norm_backward_out(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional & running_mean, const c10::optional & running_var, const c10::optional & save_mean, const c10::optional & save_var, double epsilon, const at::Tensor & reserveSpace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple cudnn_batch_norm_backward(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional & running_mean, const c10::optional & running_var, const c10::optional & save_mean, const c10::optional & save_var, double epsilon, const at::Tensor & reserveSpace); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_backward_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2c708e6f0338385bcb35228673040f53e34fb87d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_backward_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 cudnn_grid_sampler_backward(const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal.h new file mode 100644 index 0000000000000000000000000000000000000000..6c4710cf0fef2f0c7b4a8989a880fb9e9b3b990e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal.h @@ -0,0 +1,35 @@ +#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::diagonal(Tensor(a) self, int offset=0, int dim1=0, int dim2=1) -> Tensor(a) +inline at::Tensor diagonal(const at::Tensor & self, int64_t offset=0, int64_t dim1=0, int64_t dim2=1) { + return at::_ops::diagonal::call(self, offset, dim1, dim2); +} + +// aten::diagonal.Dimname(Tensor(a) self, *, Dimname outdim, Dimname dim1, Dimname dim2, int offset=0) -> Tensor(a) +inline at::Tensor diagonal(const at::Tensor & self, at::Dimname outdim, at::Dimname dim1, at::Dimname dim2, int64_t offset=0) { + return at::_ops::diagonal_Dimname::call(self, outdim, dim1, dim2, offset); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft2_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..930f97250b1c9c85a97fac65132fe26f81864411 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft2_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 fft_hfft2 { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fft_hfft2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_hfft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm); +}; + +struct TORCH_API fft_hfft2_out { + using schema = const at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, c10::optional, 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::fft_hfft2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") + static const at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm, const at::Tensor & out); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm, const at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..502520a7bb66020d631daf8397bd4a4e42db55dd --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor fft_hfft(const at::Tensor & self, c10::optional n=c10::nullopt, int64_t dim=-1, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor fft_hfft_symint(const at::Tensor & self, c10::optional n=c10::nullopt, int64_t dim=-1, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_hfft_out(at::Tensor & out, const at::Tensor & self, c10::optional n=c10::nullopt, int64_t dim=-1, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_hfft_outf(const at::Tensor & self, c10::optional n, int64_t dim, c10::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_hfft_symint_out(at::Tensor & out, const at::Tensor & self, c10::optional n=c10::nullopt, int64_t dim=-1, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_hfft_symint_outf(const at::Tensor & self, c10::optional n, int64_t dim, c10::optional norm, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_irfftn_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_irfftn_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2c1a57699055dd2e154031cb899068f8971b4f32 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_irfftn_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor fft_irfftn(const at::Tensor & self, at::OptionalIntArrayRef s=c10::nullopt, at::OptionalIntArrayRef dim=c10::nullopt, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor fft_irfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=c10::nullopt, at::OptionalIntArrayRef dim=c10::nullopt, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_irfftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=c10::nullopt, at::OptionalIntArrayRef dim=c10::nullopt, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_irfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_irfftn_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=c10::nullopt, at::OptionalIntArrayRef dim=c10::nullopt, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_irfftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional norm, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/gelu_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/gelu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..57605e5bbd5ac9cd49d18cdad673f260b2358ff5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/gelu_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 gelu_out { + using schema = at::Tensor & (const at::Tensor &, c10::string_view, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gelu") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gelu.out(Tensor self, *, str approximate='none', Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::string_view approximate, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view approximate, at::Tensor & out); +}; + +struct TORCH_API gelu_ { + using schema = at::Tensor & (at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gelu_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gelu_(Tensor(a!) self, *, str approximate='none') -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, c10::string_view approximate); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, c10::string_view approximate); +}; + +struct TORCH_API gelu { + using schema = at::Tensor (const at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gelu") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gelu(Tensor self, *, str approximate='none') -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::string_view approximate); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view approximate); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ger_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ger_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1329ffbb662862ee4e443e5403305dafdc8a6ea6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ger_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 ger(const at::Tensor & self, const at::Tensor & vec2); +TORCH_API at::Tensor & ger_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec2); +TORCH_API at::Tensor & ger_outf(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/greater_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/greater_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..87975e91d719d2773de635bf566799e4d315e9bb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/greater_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor greater(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & greater_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & greater_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & greater_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor greater(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & greater_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & greater_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & greater_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/greater_equal.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/greater_equal.h new file mode 100644 index 0000000000000000000000000000000000000000..14be05f2c3f4735edb36e99fa51a7cf31bc281a0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/greater_equal.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::greater_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & greater_equal_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::greater_equal_Scalar_out::call(self, other, out); +} +// aten::greater_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & greater_equal_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::greater_equal_Scalar_out::call(self, other, out); +} + +// aten::greater_equal.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor greater_equal(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::greater_equal_Scalar::call(self, other); +} + +// aten::greater_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & greater_equal_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::greater_equal_Tensor_out::call(self, other, out); +} +// aten::greater_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & greater_equal_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::greater_equal_Tensor_out::call(self, other, out); +} + +// aten::greater_equal.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor greater_equal(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::greater_equal_Tensor::call(self, other); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/gru_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/gru_native.h new file mode 100644 index 0000000000000000000000000000000000000000..94649437a4ec84ad4b929bbc1cd103c463e5904b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/gru_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple gru(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first); +TORCH_API ::std::tuple gru(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/histogram_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/histogram_native.h new file mode 100644 index 0000000000000000000000000000000000000000..71fbf4fa8a2ad04a91610a07eadd13c0d760da59 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/histogram_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple histogram(const at::Tensor & self, const at::Tensor & bins, const c10::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_out(const at::Tensor & self, const at::Tensor & bins, const c10::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); +TORCH_API ::std::tuple histogram(const at::Tensor & self, int64_t bins=100, c10::optional> range=c10::nullopt, const c10::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_out(const at::Tensor & self, int64_t bins, c10::optional> range, const c10::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/index.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/index.h new file mode 100644 index 0000000000000000000000000000000000000000..766921bf327db2202cebedf8659ca5b8e7135426 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/index.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::index.Tensor(Tensor self, Tensor?[] indices) -> Tensor +inline at::Tensor index(const at::Tensor & self, const c10::List> & indices) { + return at::_ops::index_Tensor::call(self, indices); +} + +// aten::index.Tensor_out(Tensor self, Tensor?[] indices, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & index_out(at::Tensor & out, const at::Tensor & self, const c10::List> & indices) { + return at::_ops::index_Tensor_out::call(self, indices, out); +} +// aten::index.Tensor_out(Tensor self, Tensor?[] indices, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & index_outf(const at::Tensor & self, const c10::List> & indices, at::Tensor & out) { + return at::_ops::index_Tensor_out::call(self, indices, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/isnan_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/isnan_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d6f6d12ce72dc94ab37559c899704fe5cb68d44f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/isnan_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & isnan_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & isnan_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/isneginf_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/isneginf_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..529d9ee2f8f1c19066bd1d104e2887e49aa11593 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/isneginf_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor isneginf(const at::Tensor & self); +TORCH_API at::Tensor & isneginf_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & isneginf_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/kaiser_window.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/kaiser_window.h new file mode 100644 index 0000000000000000000000000000000000000000..d6e96599a7505352bd331e7bdfc0d4f9d24ca8bb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/kaiser_window.h @@ -0,0 +1,79 @@ +#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::kaiser_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor kaiser_window(int64_t window_length, at::TensorOptions options={}) { + return at::_ops::kaiser_window::call(window_length, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::kaiser_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor kaiser_window(int64_t window_length, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::kaiser_window::call(window_length, dtype, layout, device, pin_memory); +} + +// aten::kaiser_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor kaiser_window(int64_t window_length, bool periodic, at::TensorOptions options={}) { + return at::_ops::kaiser_window_periodic::call(window_length, periodic, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::kaiser_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor kaiser_window(int64_t window_length, bool periodic, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::kaiser_window_periodic::call(window_length, periodic, dtype, layout, device, pin_memory); +} + +// aten::kaiser_window.beta(int window_length, bool periodic, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor kaiser_window(int64_t window_length, bool periodic, double beta, at::TensorOptions options={}) { + return at::_ops::kaiser_window_beta::call(window_length, periodic, beta, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::kaiser_window.beta(int window_length, bool periodic, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline 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) { + return at::_ops::kaiser_window_beta::call(window_length, periodic, beta, dtype, layout, device, pin_memory); +} + +// aten::kaiser_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & kaiser_window_out(at::Tensor & out, int64_t window_length) { + return at::_ops::kaiser_window_out::call(window_length, out); +} +// aten::kaiser_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & kaiser_window_outf(int64_t window_length, at::Tensor & out) { + return at::_ops::kaiser_window_out::call(window_length, out); +} + +// aten::kaiser_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & kaiser_window_out(at::Tensor & out, int64_t window_length, bool periodic) { + return at::_ops::kaiser_window_periodic_out::call(window_length, periodic, out); +} +// aten::kaiser_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & kaiser_window_outf(int64_t window_length, bool periodic, at::Tensor & out) { + return at::_ops::kaiser_window_periodic_out::call(window_length, periodic, out); +} + +// aten::kaiser_window.beta_out(int window_length, bool periodic, float beta, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & kaiser_window_out(at::Tensor & out, int64_t window_length, bool periodic, double beta) { + return at::_ops::kaiser_window_beta_out::call(window_length, periodic, beta, out); +} +// aten::kaiser_window.beta_out(int window_length, bool periodic, float beta, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & kaiser_window_outf(int64_t window_length, bool periodic, double beta, at::Tensor & out) { + return at::_ops::kaiser_window_beta_out::call(window_length, periodic, beta, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_backward_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bd257b124e91c289c6103716780a26926147928 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor leaky_relu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_matrix_power.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_matrix_power.h new file mode 100644 index 0000000000000000000000000000000000000000..f0059452be84cba674780292dea71aa0701f1d06 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_matrix_power.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linalg_matrix_power(Tensor self, int n) -> Tensor +inline at::Tensor linalg_matrix_power(const at::Tensor & self, int64_t n) { + return at::_ops::linalg_matrix_power::call(self, n); +} + +// aten::linalg_matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_matrix_power_out(at::Tensor & out, const at::Tensor & self, int64_t n) { + return at::_ops::linalg_matrix_power_out::call(self, n, out); +} +// aten::linalg_matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_matrix_power_outf(const at::Tensor & self, int64_t n, at::Tensor & out) { + return at::_ops::linalg_matrix_power_out::call(self, n, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_qr_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_qr_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3dcbd8ee55d501448ed804d5925eaf1ad56f5732 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_qr_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 linalg_qr(const at::Tensor & A, c10::string_view mode="reduced"); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vecdot_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vecdot_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8aaa570fcec57b70ea8626cc9eebe62acb39aafc --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vecdot_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 linalg_vecdot(const at::Tensor & x, const at::Tensor & y, int64_t dim=-1); +TORCH_API at::Tensor & linalg_vecdot_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & y, int64_t dim=-1); +TORCH_API at::Tensor & linalg_vecdot_outf(const at::Tensor & x, const at::Tensor & y, int64_t dim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log_sigmoid_forward_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log_sigmoid_forward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e091a8b009506eedddc0ec194bd8dfe99422605f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log_sigmoid_forward_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 log_sigmoid_forward(const at::Tensor & self); +TORCH_API ::std::tuple log_sigmoid_forward_out(at::Tensor & output, at::Tensor & buffer, const at::Tensor & self); +TORCH_API ::std::tuple log_sigmoid_forward_outf(const at::Tensor & self, at::Tensor & output, at::Tensor & buffer); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log_softmax_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f89cc73bb04dad56225b164d77689259dab35e1a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log_softmax_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 log_softmax_int { + using schema = at::Tensor (const at::Tensor &, int64_t, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::log_softmax") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "int") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "log_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim, c10::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional dtype); +}; + +struct TORCH_API log_softmax_int_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::log_softmax") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "int_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "log_softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t dim, c10::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional dtype, at::Tensor & out); +}; + +struct TORCH_API log_softmax_Dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::log_softmax") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Dimname") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "log_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::Dimname dim, c10::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, c10::optional dtype); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/masked_fill_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/masked_fill_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f4d67377d710ba6fdb83e22773d4f79809e3abeb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/masked_fill_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 masked_fill(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); +TORCH_API at::Tensor & masked_fill_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); +TORCH_API at::Tensor & masked_fill_outf(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor masked_fill(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); +TORCH_API at::Tensor & masked_fill_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); +TORCH_API at::Tensor & masked_fill_outf(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_backward_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c6310664f9e97a948750f802ec6ddd08f3ddb152 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_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 max_pool2d_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::max_pool2d_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +struct TORCH_API max_pool2d_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::max_pool2d_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7dfb0a0798f7684a6a6906bd14904fbeab332eea --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_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 & miopen_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor & miopen_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out); +TORCH_API at::Tensor & miopen_convolution_transpose_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor & miopen_convolution_transpose_symint_outf(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ne_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ne_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f4847a150f978cc90217b44533e962d4567a7aac --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ne_cuda_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor ne(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & ne_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & ne_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & ne_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor ne(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & ne_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & ne_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & ne_(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/negative_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/negative_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2cbf842bbd0825a9f0ec4574ad7f0d066f6b0881 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/negative_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 negative { + 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::negative") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "negative(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 negative_ { + 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::negative_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "negative_(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 negative_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::negative") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "negative.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/nll_loss_backward.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..0d71edfcf48fff6eb711b3000032cd1a62ef7e60 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_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::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & nll_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); + } +} + +// aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & nll_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); + } +} + +// aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & nll_loss_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); + } +} + +// aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & nll_loss_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & nll_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input) { + return at::_ops::nll_loss_backward_grad_input::call(grad_output, self, target, weight, reduction, ignore_index, total_weight, grad_input); + } +} + +// aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor +inline at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward::call(grad_output, self, target, weight, reduction, ignore_index, total_weight); +} +namespace symint { + template ::value>> + at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward::call(grad_output, self, target, weight, reduction, ignore_index, total_weight); + } +} + +// aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor +inline at::Tensor nll_loss_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward::call(grad_output, self, target, weight, reduction, ignore_index, total_weight); +} +namespace symint { + template ::value>> + at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight) { + return at::_ops::nll_loss_backward::call(grad_output, self, target, weight, reduction, ignore_index, total_weight); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/pad_sequence.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/pad_sequence.h new file mode 100644 index 0000000000000000000000000000000000000000..9981f845733ee67046ab8067500f69e46a03d725 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/pad_sequence.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::pad_sequence(Tensor[] sequences, bool batch_first=False, float padding_value=0.0) -> Tensor +inline at::Tensor pad_sequence(at::TensorList sequences, bool batch_first=false, double padding_value=0.0) { + return at::_ops::pad_sequence::call(sequences, batch_first, padding_value); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/poisson_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/poisson_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a50988f59dd2ad87153f3fc790b75643bbceb80d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/poisson_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 & poisson_out(const at::Tensor & self, c10::optional generator, at::Tensor & out); +TORCH_API at::Tensor _s_poisson_cpu(const at::Tensor & self, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor _s_poisson_cuda(const at::Tensor & self, c10::optional generator=c10::nullopt); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/qr_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/qr_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1b69e399fbb719684c1636c710c889187f40e6e3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/qr_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple qr(const at::Tensor & self, bool some=true); +TORCH_API ::std::tuple qr_out(const at::Tensor & self, bool some, at::Tensor & Q, at::Tensor & R); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/quantize_per_tensor_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/quantize_per_tensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b2094e1a0857358494f1adcfd35329181303485c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/quantize_per_tensor_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API quantize_per_tensor { + using schema = at::Tensor (const at::Tensor &, double, int64_t, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantize_per_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantize_per_tensor(Tensor self, float scale, int zero_point, ScalarType dtype) -> Tensor") + static at::Tensor call(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype); +}; + +struct TORCH_API quantize_per_tensor_tensor_qparams { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantize_per_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "tensor_qparams") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantize_per_tensor.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype); +}; + +struct TORCH_API quantize_per_tensor_tensors { + using schema = ::std::vector (at::TensorList, 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::quantize_per_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "tensors") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantize_per_tensor.tensors(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype) -> Tensor[]") + static ::std::vector call(at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype); +}; + +struct TORCH_API quantize_per_tensor_out { + using schema = at::Tensor & (const at::Tensor &, double, int64_t, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantize_per_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantize_per_tensor.out(Tensor self, float scale, int zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype, at::Tensor & out); +}; + +struct TORCH_API quantize_per_tensor_tensor_qparams_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantize_per_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "tensor_qparams_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantize_per_tensor.tensor_qparams_out(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype, at::Tensor & out); +}; + +struct TORCH_API quantize_per_tensor_tensors_out { + using schema = void (at::TensorList, const at::Tensor &, const at::Tensor &, at::ScalarType, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantize_per_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "tensors_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantize_per_tensor.tensors_out(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_batch_norm_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_batch_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4ac157211a175a682f1c956138e32ada96f4ebc1 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_batch_norm_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 & quantized_batch_norm_out(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const at::Tensor & mean, const at::Tensor & var, double eps, double output_scale, int64_t output_zero_point, at::Tensor & out); +TORCH_API at::Tensor quantized_batch_norm(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const at::Tensor & mean, const at::Tensor & var, double eps, double output_scale, int64_t output_zero_point); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/range_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/range_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2643c297a11c7c19013e7cf61eef0cbbd02a89c0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/range_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor range(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step=1, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & range_out(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); +TORCH_API at::Tensor & range_cuda_out(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); +TORCH_API at::Tensor range(const at::Scalar & start, const at::Scalar & end, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & range_out_no_step(const at::Scalar & start, const at::Scalar & end, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/result_type.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/result_type.h new file mode 100644 index 0000000000000000000000000000000000000000..8f23d204a0bd49fbe537100a6025c024753a925f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/result_type.h @@ -0,0 +1,45 @@ +#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::result_type.Tensor(Tensor tensor, Tensor other) -> ScalarType +inline at::ScalarType result_type(const at::Tensor & tensor, const at::Tensor & other) { + return at::_ops::result_type_Tensor::call(tensor, other); +} + +// aten::result_type.Scalar(Tensor tensor, Scalar other) -> ScalarType +inline at::ScalarType result_type(const at::Tensor & tensor, const at::Scalar & other) { + return at::_ops::result_type_Scalar::call(tensor, other); +} + +// aten::result_type.Scalar_Tensor(Scalar scalar, Tensor tensor) -> ScalarType +inline at::ScalarType result_type(const at::Scalar & scalar, const at::Tensor & tensor) { + return at::_ops::result_type_Scalar_Tensor::call(scalar, tensor); +} + +// aten::result_type.Scalar_Scalar(Scalar scalar1, Scalar scalar2) -> ScalarType +inline at::ScalarType result_type(const at::Scalar & scalar1, const at::Scalar & scalar2) { + return at::_ops::result_type_Scalar_Scalar::call(scalar1, scalar2); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/silu_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/silu_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f5f19532df803e04b495f8f02703407e73fd9684 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/silu_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor silu(const at::Tensor & self); +TORCH_API at::Tensor & silu_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slice_scatter_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slice_scatter_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b9dc44806dfc0abe0e2244925e22e9654e0ee222 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slice_scatter_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 slice_scatter { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, c10::optional, c10::optional, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slice_scatter") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slice_scatter(Tensor self, Tensor src, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::optional start, c10::optional end, c10::SymInt step); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::optional start, c10::optional end, c10::SymInt step); +}; + +struct TORCH_API slice_scatter_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, c10::optional, c10::optional, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slice_scatter") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slice_scatter.out(Tensor self, Tensor src, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::optional start, c10::optional end, c10::SymInt step, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::optional start, c10::optional end, c10::SymInt step, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv_dilated2d_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv_dilated2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2faa6c605fe1030f66d48b853006c0d96818cb12 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv_dilated2d_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 slow_conv_dilated2d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slow_conv_dilated2d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slow_conv_dilated2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation); +}; + +struct TORCH_API slow_conv_dilated2d_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const c10::optional &, c10::SymIntArrayRef, 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::slow_conv_dilated2d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slow_conv_dilated2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/softshrink_backward_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/softshrink_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9cad570f44b4cd8cb3c9cb8310823fe71e65076c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/softshrink_backward_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor softshrink_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd); +TORCH_API at::Tensor & softshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd); +TORCH_API at::Tensor & softshrink_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_native.h new file mode 100644 index 0000000000000000000000000000000000000000..34e2cb69964de6643cf40dbf9cd6bd11326ee791 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_hermite_polynomial_h_native.h @@ -0,0 +1,27 @@ +#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_special_hermite_polynomial_h_out : public at::meta::structured_special_hermite_polynomial_h { +void impl(const at::Tensor & x, const at::Tensor & n, const at::Tensor & out); +}; +TORCH_API at::Tensor special_hermite_polynomial_h(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_h_out(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_hermite_polynomial_h(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_hermite_polynomial_h_out(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..89a3420e6e8d57a3e2c8c35d810fccb7e63118ee --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_modified_bessel_i1(const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_polygamma_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_polygamma_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b0c23fb9de4f151e6a55b8bdf051e91edadcb45f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_polygamma_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_polygamma(int64_t n, const at::Tensor & self); +TORCH_API at::Tensor & special_polygamma_out(at::Tensor & out, int64_t n, const at::Tensor & self); +TORCH_API at::Tensor & special_polygamma_outf(int64_t n, 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/special_softmax_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_softmax_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3a3d3cca0106fa2297e4fa1233400e004aec5ef1 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_softmax_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 special_softmax(const at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sqrt_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sqrt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7be1ba026f21fcd83b33a73e364ec3692408636b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sqrt_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sqrt { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sqrt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sqrt(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API sqrt_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sqrt_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sqrt_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API sqrt_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sqrt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_constrain_range.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_constrain_range.h new file mode 100644 index 0000000000000000000000000000000000000000..fad7ca9d57eea769d7ccec818c7d0b08118d1f1f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_constrain_range.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::sym_constrain_range(Scalar size, *, int? min=None, int? max=None) -> () +inline void sym_constrain_range(const at::Scalar & size, c10::optional min=c10::nullopt, c10::optional max=c10::nullopt) { + return at::_ops::sym_constrain_range::call(size, min, max); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_stride_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_stride_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2db949a65823a66ebab3bb304a9e946d2f51c286 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sym_stride_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API c10::SymInt sym_stride(const at::Tensor & self, int64_t dim); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/to_mkldnn_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/to_mkldnn_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7fb62745e4e0b9c6e942bac48a5d172592a30a4f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/to_mkldnn_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & to_mkldnn_out(at::Tensor & out, const at::Tensor & self, c10::optional dtype=c10::nullopt); +TORCH_API at::Tensor & to_mkldnn_outf(const at::Tensor & self, c10::optional dtype, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsc_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b9e5ae864c27e3e2fc078fe1ea8c48c25cc50739 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsc_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor to_sparse_bsc(const at::Tensor & self, at::IntArrayRef blocksize, c10::optional dense_dim=c10::nullopt); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..484d95c32872e5d10ead57b5aea9ed548c53c272 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API ::std::tuple topk(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true); +TORCH_API ::std::tuple topk_symint(const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true); +TORCH_API ::std::tuple topk_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true); +TORCH_API ::std::tuple topk_outf(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices); +TORCH_API ::std::tuple topk_symint_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true); +TORCH_API ::std::tuple topk_symint_outf(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices); + +} // namespace meta +} // namespace at