diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6785b651113a5605edd9f05fd27103b3f672b3ab --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_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 & _adaptive_avg_pool2d_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & _adaptive_avg_pool2d_backward_outf(const at::Tensor & grad_output, 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/_assert_scalar_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_scalar_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b97da5d16ea6c57aa37937f4980305377292dbb8 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_scalar_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _assert_scalar { + using schema = void (const at::Scalar &, 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_scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_assert_scalar(Scalar self, str assert_msg) -> ()") + static void call(const at::Scalar & self, c10::string_view assert_msg); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, c10::string_view assert_msg); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9bbf3531834c870b8d7558ba42a18ec5f029547a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_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 & _embedding_bag_per_sample_weights_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); +TORCH_API at::Tensor & _embedding_bag_per_sample_weights_backward_outf(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..da9f8c8717ea414f7bddafce2177a6db7bb74d3e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c28b119f8ca569bd8eefe863f86d09e447428c14 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist_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 _euclidean_dist { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_euclidean_dist") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_euclidean_dist(Tensor x1, Tensor x2) -> Tensor") + static at::Tensor call(const at::Tensor & x1, const at::Tensor & x2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2); +}; + +struct TORCH_API _euclidean_dist_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_euclidean_dist") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x1, const at::Tensor & x2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c3b7af9484fd7f48a4cb60df71b3f8aa6a3e3994 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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 _fake_quantize_learnable_per_channel_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r.h new file mode 100644 index 0000000000000000000000000000000000000000..75471e140c9a3574a40eec5690607cbcafc4a044 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fft_c2r.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::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template ::value>> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r_symint(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template ::value>> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9d34b7718c758821257a9b62f5746099d803d41c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::vector _foreach_norm(at::TensorList self, const at::Scalar & ord=2); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a7f8ece3c3fced9110d63a4030081c6283958d68 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_norm_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 _foreach_norm_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_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[]") + static ::std::vector call(at::TensorList self, const at::Scalar & ord); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & ord); +}; + +struct TORCH_API _foreach_norm_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_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, const at::Scalar & ord, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & ord, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ffb3740521948cb9132945021204345427ef1b42 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::vector _foreach_trunc(at::TensorList self); +TORCH_API void _foreach_trunc_(at::TensorList self); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..80929c51e87de8f7a844b362c70faaad37a4fce0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_moving_avg_obs_fq_helper_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API ::std::tuple _fused_moving_avg_obs_fq_helper_functional(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, const at::Tensor & running_min, const at::Tensor & running_max, const at::Tensor & scale, const at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false); +TORCH_API ::std::tuple _fused_moving_avg_obs_fq_helper_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false); +TORCH_API ::std::tuple _fused_moving_avg_obs_fq_helper_outf(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_new_zeros_with_same_feature_meta_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_new_zeros_with_same_feature_meta_native.h new file mode 100644 index 0000000000000000000000000000000000000000..70704558effc757f0850af7971add65f7b0ace20 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_new_zeros_with_same_feature_meta_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 _new_zeros_with_same_feature_meta(const at::Tensor & self, const at::Tensor & other, int64_t self_num_batch_dims=0); +TORCH_API at::Tensor & _new_zeros_with_same_feature_meta_out(const at::Tensor & self, const at::Tensor & other, int64_t self_num_batch_dims, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_from_tensor.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_from_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..2d21aa9f503f093b4df876410540bc04748ca51a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_from_tensor.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::_reshape_from_tensor(Tensor self, Tensor shape) -> Tensor +inline at::Tensor _reshape_from_tensor(const at::Tensor & self, const at::Tensor & shape) { + return at::_ops::_reshape_from_tensor::call(self, shape); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b31b9dbabecd0d0bcb46003db26efd0f6ca9939c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_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 _scaled_dot_product_cudnn_attention_cuda(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, c10::optional scale=c10::nullopt); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_shape_as_tensor.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_shape_as_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..ad9ff8f05257b38c56897e73a1b722de5c5388c4 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_shape_as_tensor.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::_shape_as_tensor(Tensor self) -> Tensor +inline at::Tensor _shape_as_tensor(const at::Tensor & self) { + return at::_ops::_shape_as_tensor::call(self); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_backward_data_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_backward_data_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..65c1c72c9a15514071f10b65ca16747070204368 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_softmax_backward_data_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__softmax_backward_data : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sum_backward_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sum_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..57a5999e055083a5aebe599ac25fa68736d3e767 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sum_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 _sparse_sum_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_sum_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_sum_backward(Tensor grad, Tensor self, int[] dim) -> Tensor") + static at::Tensor call(const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim); +}; + +struct TORCH_API _sparse_sum_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_sum_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_sum_backward.out(Tensor grad, Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..aba9833ebcebc86aff330796d313bf92b99ac2d9 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_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 _test_autograd_multiple_dispatch_fullcoverage { + 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::_test_autograd_multiple_dispatch") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "fullcoverage") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_autograd_multiple_dispatch.fullcoverage(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 _test_autograd_multiple_dispatch_ntonly { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_test_autograd_multiple_dispatch") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ntonly") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_autograd_multiple_dispatch.ntonly(Tensor self, bool b) -> Tensor") + static at::Tensor call(const at::Tensor & self, bool b); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool b); +}; + +struct TORCH_API _test_autograd_multiple_dispatch_fullcoverage_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::_test_autograd_multiple_dispatch") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "fullcoverage_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_autograd_multiple_dispatch.fullcoverage_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/_test_parallel_materialize_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_parallel_materialize_native.h new file mode 100644 index 0000000000000000000000000000000000000000..72641db0aa6993de3a062c2dfd84a7bd7b82af22 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_test_parallel_materialize_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 _test_parallel_materialize(const at::Tensor & self, int64_t num_parallel, bool skip_first=false); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_bsc.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_bsc.h new file mode 100644 index 0000000000000000000000000000000000000000..9b6ccffa14234c37ffff63fa082e53648f65179f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_bsc.h @@ -0,0 +1,34 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_bsc_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef blocksize, c10::optional dense_dim=c10::nullopt) { + return at::_ops::_to_sparse_bsc_out::call(self, blocksize, dense_dim, out); +} +// aten::_to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_bsc_outf(const at::Tensor & self, at::IntArrayRef blocksize, c10::optional dense_dim, at::Tensor & out) { + return at::_ops::_to_sparse_bsc_out::call(self, blocksize, dense_dim, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/absolute_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/absolute_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e42fb8193b250136b6f6b5b96c95ac7a0a1b7834 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/absolute_compositeimplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor absolute(const at::Tensor & self); +TORCH_API at::Tensor & absolute_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & absolute_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & absolute_(at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_backward_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b8a54daf60841981383e559fdfbd50d8c49ef71a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_backward_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 adaptive_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a4dd3bfe5635f18a68b2a93117c1b0fb8fd2ad26 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_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 adaptive_max_pool3d_out { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef, 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::adaptive_max_pool3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "adaptive_max_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); +}; + +struct TORCH_API adaptive_max_pool3d { + using schema = ::std::tuple (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::adaptive_max_pool3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "adaptive_max_pool3d(Tensor self, int[3] output_size) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & self, at::IntArrayRef output_size); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/aminmax.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/aminmax.h new file mode 100644 index 0000000000000000000000000000000000000000..bca1f59c0cf037d7fe7c4e81e3187f4ac9be21ec --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/aminmax.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::aminmax(Tensor self, *, int? dim=None, bool keepdim=False) -> (Tensor min, Tensor max) +inline ::std::tuple aminmax(const at::Tensor & self, c10::optional dim=c10::nullopt, bool keepdim=false) { + return at::_ops::aminmax::call(self, dim, keepdim); +} + +// aten::aminmax.out(Tensor self, *, int? dim=None, bool keepdim=False, Tensor(a!) min, Tensor(b!) max) -> (Tensor(a!) min, Tensor(b!) max) +inline ::std::tuple aminmax_out(at::Tensor & min, at::Tensor & max, const at::Tensor & self, c10::optional dim=c10::nullopt, bool keepdim=false) { + return at::_ops::aminmax_out::call(self, dim, keepdim, min, max); +} +// aten::aminmax.out(Tensor self, *, int? dim=None, bool keepdim=False, Tensor(a!) min, Tensor(b!) max) -> (Tensor(a!) min, Tensor(b!) max) +inline ::std::tuple aminmax_outf(const at::Tensor & self, c10::optional dim, bool keepdim, at::Tensor & min, at::Tensor & max) { + return at::_ops::aminmax_out::call(self, dim, keepdim, min, max); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/argsort_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/argsort_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cd042073ea98193f0b0a990c6bb8ee4c8594e6a8 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/argsort_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 argsort(const at::Tensor & self, bool stable, int64_t dim=-1, bool descending=false); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/atan_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/atan_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2429ecf6be19d32a6f7dd85bbfc725389e501b74 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/atan_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor atan(const at::Tensor & self); +TORCH_API at::Tensor & atan_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & atan_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & atan_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cartesian_prod.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cartesian_prod.h new file mode 100644 index 0000000000000000000000000000000000000000..48f62afcd6d49ede929d02fa499d3a689f4a409b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cartesian_prod.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::cartesian_prod(Tensor[] tensors) -> Tensor +inline at::Tensor cartesian_prod(at::TensorList tensors) { + return at::_ops::cartesian_prod::call(tensors); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cat_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cat_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7c094d7f83bd88fb770e504923190a5639687223 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cat_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 cat(const at::ITensorListRef & tensors, int64_t dim=0); +TORCH_API at::Tensor & cat_out(at::Tensor & out, const at::ITensorListRef & tensors, int64_t dim=0); +TORCH_API at::Tensor & cat_outf(const at::ITensorListRef & tensors, int64_t dim, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ceil_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ceil_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0f4613a6859dc0e3752f3cbece5267b16bbee823 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ceil_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor 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 cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cholesky_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cholesky_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a624b4e2dabd55b0086d5d64e4a1a5bc69664dfa --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cholesky_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 cholesky(const at::Tensor & self, bool upper=false); +TORCH_API at::Tensor & cholesky_out(const at::Tensor & self, bool upper, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/clamp_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/clamp_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fb8197208e54e9ed1719d4c5c9ddec259388bd19 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/clamp_meta_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 meta { + +TORCH_API at::Tensor clamp(const at::Tensor & self, const c10::optional & min, const c10::optional & max=c10::nullopt); +TORCH_API at::Tensor & clamp_out(at::Tensor & out, const at::Tensor & self, const c10::optional & min, const c10::optional & max=c10::nullopt); +TORCH_API at::Tensor & clamp_outf(const at::Tensor & self, const c10::optional & min, const c10::optional & max, at::Tensor & out); +TORCH_API at::Tensor & clamp_(at::Tensor & self, const c10::optional & min, const c10::optional & max=c10::nullopt); +TORCH_API at::Tensor clamp(const at::Tensor & self, const c10::optional & min={}, const c10::optional & max={}); +TORCH_API at::Tensor & clamp_out(at::Tensor & out, const at::Tensor & self, const c10::optional & min={}, const c10::optional & max={}); +TORCH_API at::Tensor & clamp_outf(const at::Tensor & self, const c10::optional & min, const c10::optional & max, at::Tensor & out); +TORCH_API at::Tensor & clamp_(at::Tensor & self, const c10::optional & min={}, const c10::optional & max={}); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/conv1d_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/conv1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a1188f80b837632a7d9596838046567cf5067d94 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/conv1d_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 conv1d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::conv1d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "conv1d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, SymInt[1] padding=0, SymInt[1] dilation=1, SymInt groups=1) -> 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, c10::SymInt groups); + 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, c10::SymInt groups); +}; + +struct TORCH_API conv1d_padding { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::string_view, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::conv1d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "padding") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "conv1d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, str padding=\"valid\", SymInt[1] dilation=1, SymInt groups=1) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_bag_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_bag_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4c539f8f915d53d1e0e6c7336debc9c5a9c442e7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_bag_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 ::std::tuple embedding_bag(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); +TORCH_API ::std::tuple embedding_bag(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, c10::optional padding_idx); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/expand_as_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/expand_as_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2198ce01f90ba6fa51f1c4c601e619c2b465870c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/expand_as_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 expand_as(const 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/fbgemm_linear_fp16_weight_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8c145586f9822f499a95baaf52082c2dfa410921 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_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 fbgemm_linear_fp16_weight(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_ifftn_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_ifftn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a6ba9276caea8a9b5b050420f59bd6f8761314c9 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_ifftn_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_ifftn { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, 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_ifftn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ifftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional norm); +}; + +struct TORCH_API fft_ifftn_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, 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::fft_ifftn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ifftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_ihfft_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_ihfft_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f41fa60bac61005a669a0b91d206feb0ff7801d5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_ihfft_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_ihfft { + using schema = at::Tensor (const at::Tensor &, c10::optional, 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::fft_ihfft") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ihfft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::optional n, int64_t dim, c10::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional n, int64_t dim, c10::optional norm); +}; + +struct TORCH_API fft_ihfft_out { + using schema = at::Tensor & (const at::Tensor &, c10::optional, 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::fft_ihfft") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ihfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::optional n, int64_t dim, c10::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional n, int64_t dim, c10::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/full_like_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/full_like_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..488f68bc62d9caa662bfadce98a4d7b1837e0ae2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/full_like_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 full_like { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, c10::optional, c10::optional, c10::optional, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::full_like") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "full_like(Tensor self, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & fill_value, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & fill_value, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format); +}; + +struct TORCH_API full_like_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, 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::full_like") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "full_like.out(Tensor self, Scalar fill_value, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & fill_value, c10::optional memory_format, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & fill_value, c10::optional memory_format, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/geqrf_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/geqrf_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80fb5deda707de5d7377460bf0ba574bfd4081e2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/geqrf_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 geqrf_a { + using schema = ::std::tuple (const at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::geqrf") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "a") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau)") + static ::std::tuple call(const at::Tensor & self, at::Tensor & a, at::Tensor & tau); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & a, at::Tensor & tau); +}; + +struct TORCH_API geqrf { + using schema = ::std::tuple (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::geqrf") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "geqrf(Tensor self) -> (Tensor a, Tensor tau)") + static ::std::tuple call(const at::Tensor & self); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..b3e63d53610c179e2cf61ed81accce26e1914372 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::grid_sampler_3d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor) +inline ::std::tuple grid_sampler_3d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask) { + return at::_ops::grid_sampler_3d_backward::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask); +} + +// aten::grid_sampler_3d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple grid_sampler_3d_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask) { + return at::_ops::grid_sampler_3d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1); +} +// aten::grid_sampler_3d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple grid_sampler_3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::grid_sampler_3d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/gru_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/gru_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..edc4efd811868010515bc98366f777d52554cc3c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/gru_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 gru_input { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, at::TensorList, bool, int64_t, double, 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::gru") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "input") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gru.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor)") + static ::std::tuple call(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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API gru_data { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, bool, int64_t, double, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gru") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "data") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gru.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor)") + static ::std::tuple call(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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, 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 at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/igammac_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/igammac_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a3e479bdccd111a7f1d336dda768241b9c8919bf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/igammac_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 igammac_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::igammac") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "igammac.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API igammac { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::igammac") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "igammac(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API igammac_ { + using schema = at::Tensor & (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::igammac_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "igammac_(Tensor(a!) self, Tensor other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/index_add_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/index_add_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4080458b80553ba8663d14ea25b396020aac9d23 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/index_add_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 index_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); +TORCH_API at::Tensor & index_add_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); +TORCH_API at::Tensor & index_add_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & index_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/is_set_to_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/is_set_to_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c912d4021778db272ac4e35e7776216f1126e54c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/is_set_to_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool is_set_to(const at::Tensor & self, const at::Tensor & tensor); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/less_equal_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/less_equal_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c75199545f3c947bc3ee933f6eb1864f362f9df5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/less_equal_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 less_equal(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & less_equal_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & less_equal_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & less_equal_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor less_equal(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & less_equal_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & less_equal_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & less_equal_(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/linalg_eigvals.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_eigvals.h new file mode 100644 index 0000000000000000000000000000000000000000..7034f499ba95fe8a85178867ce88aba2bfcbbb61 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_eigvals.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_eigvals(Tensor self) -> Tensor +inline at::Tensor linalg_eigvals(const at::Tensor & self) { + return at::_ops::linalg_eigvals::call(self); +} + +// aten::linalg_eigvals.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_eigvals_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::linalg_eigvals_out::call(self, out); +} +// aten::linalg_eigvals.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_eigvals_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::linalg_eigvals_out::call(self, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ecf57adf7a6ee88ce14dbb2909a5b6a4d2db8a8 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor log2(const at::Tensor & self); +TORCH_API at::Tensor & log2_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & log2_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & log2_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log_sigmoid_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log_sigmoid_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb562a37cf3c1987a31471370a9b3318b384ddf7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/log_sigmoid_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 log_sigmoid(const at::Tensor & self); +TORCH_API at::Tensor & log_sigmoid_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & log_sigmoid_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logical_and_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logical_and_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..244f48cd663a39d1492af353b51a829c9c22712d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logical_and_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & logical_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9680e33f3f4f259b6cf3f0cd76260b0791c55cbf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API ::std::tuple max(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple max_out(at::Tensor & max, at::Tensor & max_values, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple max_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & max, at::Tensor & max_values); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1d80928e8e32b3eb7dfe4b478502a54371cc55b3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_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 max_pool2d_with_indices_backward(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, const at::Tensor & indices); +TORCH_API at::Tensor & max_pool2d_with_indices_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, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); +TORCH_API at::Tensor & max_pool2d_with_indices_backward_outf(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, const at::Tensor & indices, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nested_to_padded_tensor_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nested_to_padded_tensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5156e5464b02597672915dcc0311292337011dc4 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nested_to_padded_tensor_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API nested_to_padded_tensor { + using schema = at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nested_to_padded_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nested_to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, double padding, at::OptionalIntArrayRef output_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double padding, at::OptionalIntArrayRef output_size); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ones.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ones.h new file mode 100644 index 0000000000000000000000000000000000000000..c67583b0ce9466aabf7a0dc49af41acaf5535a81 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ones.h @@ -0,0 +1,131 @@ +#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::ones.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones(at::IntArrayRef size, c10::optional names, at::TensorOptions options={}) { + return at::_ops::ones_names::call(size, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::ones.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones(at::IntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::ones_names::call(size, names, dtype, layout, device, pin_memory); +} + +// aten::ones(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::ones::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor ones(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::ones::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::ones(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones(at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::ones::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor ones(at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::ones::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::ones(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones_symint(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::ones::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor ones(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::ones::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::ones(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones_symint(c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::ones::call(size, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor ones(c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::ones::call(size, dtype, layout, device, pin_memory); + } +} + +// aten::ones.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::ones_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template ::value>> + at::Tensor & ones_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::ones_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::ones.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::ones_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template ::value>> + at::Tensor & ones_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::ones_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::ones.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_symint_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::ones_out::call(size, out); +} +namespace symint { + template ::value>> + at::Tensor & ones_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::ones_out::call(size, out); + } +} + +// aten::ones.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_symint_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::ones_out::call(size, out); +} +namespace symint { + template ::value>> + at::Tensor & ones_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::ones_out::call(size, out); + } +} + +// aten::ones.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_out(at::Tensor & out, at::IntArrayRef size, c10::optional names) { + return at::_ops::ones_names_out::call(size, names, out); +} +// aten::ones.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_outf(at::IntArrayRef size, c10::optional names, at::Tensor & out) { + return at::_ops::ones_names_out::call(size, names, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/quantize_per_channel_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/quantize_per_channel_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dd330fa5684a36e2137ec72ab617bd413e59bb40 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/quantize_per_channel_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 quantize_per_channel { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, 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_channel") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantize_per_channel(Tensor self, Tensor scales, Tensor zero_points, int axis, ScalarType dtype) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::ScalarType dtype); +}; + +struct TORCH_API quantize_per_channel_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, 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_channel") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantize_per_channel.out(Tensor self, Tensor scales, Tensor zero_points, int axis, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::ScalarType dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::ScalarType dtype, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ravel.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ravel.h new file mode 100644 index 0000000000000000000000000000000000000000..364f3fcf425a04bffa01c2a90f37ffdf7909d0b7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/ravel.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::ravel(Tensor(a) self) -> Tensor(a) +inline at::Tensor ravel(const at::Tensor & self) { + return at::_ops::ravel::call(self); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/real_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/real_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..217dac7768bb8a651a91880631d19ece290632ff --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/real_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API real { + 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::real") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "real(Tensor(a) self) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad2d_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8afc7cf4146a084c29cf6e6dafe878b7d7ee810e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad2d_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API reflection_pad2d_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::reflection_pad2d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); +}; + +struct TORCH_API reflection_pad2d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::reflection_pad2d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad3d_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ee92d8a790a1291c8da8edf14fdeac7871896bd7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad3d_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 reflection_pad3d_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::reflection_pad3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "reflection_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); +}; + +struct TORCH_API reflection_pad3d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::reflection_pad3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "reflection_pad3d(Tensor self, SymInt[6] padding) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0fce1cb2483ef81ad59e4beb8e1a1575c3e640e5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor replication_pad1d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & replication_pad1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/requires_grad.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/requires_grad.h new file mode 100644 index 0000000000000000000000000000000000000000..b7ed7777aeddf556b373d49b5842f27a1ff3176e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/requires_grad.h @@ -0,0 +1,26 @@ +#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 { + + + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reshape_compositeimplicitautogradnestedtensor_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reshape_compositeimplicitautogradnestedtensor_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b5d11e58c6f78cf74c1800e319c306669e128453 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/reshape_compositeimplicitautogradnestedtensor_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 compositeimplicitautogradnestedtensor { + +TORCH_API at::Tensor reshape(const at::Tensor & self, at::IntArrayRef shape); +TORCH_API at::Tensor reshape_symint(const at::Tensor & self, c10::SymIntArrayRef shape); + +} // namespace compositeimplicitautogradnestedtensor +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/scatter_add_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/scatter_add_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..59328cbc756e7ecc5072c49732afe74680451ed6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/scatter_add_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor scatter_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_add_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_add_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out); +TORCH_API at::Tensor & scatter_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/silu_backward_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/silu_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f818543a7cbc54a3c884e3707f64963873da7821 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/silu_backward_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +TORCH_API at::Tensor math_silu_backward(const at::Tensor & grad_output, const at::Tensor & self); +struct TORCH_API structured_silu_backward_out : public at::meta::structured_silu_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & grad_input); +}; +TORCH_API at::Tensor silu_backward_nested(const at::Tensor & grad_output, const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sinc_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sinc_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..97c2167b9d293f218d17596ed2e08d1a9e146ae2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/sinc_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor sinc(const at::Tensor & self); +TORCH_API at::Tensor & sinc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sinc_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinc_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv3d_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..987480ced80627b1f0f848ce0036bee4e43213fa --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv3d_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_conv3d_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const c10::optional &, 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_conv3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slow_conv3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, *, 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, 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, at::Tensor & out); +}; + +struct TORCH_API slow_conv3d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const c10::optional &, 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_conv3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slow_conv3d(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0) -> 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); + 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); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_i1e_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_i1e_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f7829c9f5b21dfc7c86a94872ceb3592edf4ccdb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_i1e_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 special_i1e(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_legendre_polynomial_p.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_legendre_polynomial_p.h new file mode 100644 index 0000000000000000000000000000000000000000..4c692de9a799906d6d4f8a205ebed20f6b2d2dcd --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_legendre_polynomial_p.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_legendre_polynomial_p(Tensor x, Tensor n) -> Tensor +inline at::Tensor special_legendre_polynomial_p(const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_legendre_polynomial_p::call(x, n); +} + +// aten::special_legendre_polynomial_p.x_scalar(Scalar x, Tensor n) -> Tensor +inline at::Tensor special_legendre_polynomial_p(const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_legendre_polynomial_p_x_scalar::call(x, n); +} + +// aten::special_legendre_polynomial_p.n_scalar(Tensor x, Scalar n) -> Tensor +inline at::Tensor special_legendre_polynomial_p(const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_legendre_polynomial_p_n_scalar::call(x, n); +} + +// aten::special_legendre_polynomial_p.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_legendre_polynomial_p_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_legendre_polynomial_p_out::call(x, n, out); +} +// aten::special_legendre_polynomial_p.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_legendre_polynomial_p_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_legendre_polynomial_p_out::call(x, n, out); +} + +// aten::special_legendre_polynomial_p.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_legendre_polynomial_p_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_legendre_polynomial_p_x_scalar_out::call(x, n, out); +} +// aten::special_legendre_polynomial_p.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_legendre_polynomial_p_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_legendre_polynomial_p_x_scalar_out::call(x, n, out); +} + +// aten::special_legendre_polynomial_p.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_legendre_polynomial_p_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_legendre_polynomial_p_n_scalar_out::call(x, n, out); +} +// aten::special_legendre_polynomial_p.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_legendre_polynomial_p_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { + return at::_ops::special_legendre_polynomial_p_n_scalar_out::call(x, n, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6f57a5360904b20817e617360fb7c38ffba83001 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_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_i0(const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i0_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i0_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/stride.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/stride.h new file mode 100644 index 0000000000000000000000000000000000000000..1923284ec2d446f13f98b81f554a231767d692b6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/stride.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::stride.int(Tensor self, int dim) -> int +inline int64_t __dispatch_stride(const at::Tensor & self, int64_t dim) { + return at::_ops::stride_int::call(self, dim); +} + +// aten::stride.Dimname(Tensor self, Dimname dim) -> int +inline int64_t stride(const at::Tensor & self, at::Dimname dim) { + return at::_ops::stride_Dimname::call(self, dim); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/t_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/t_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8f001ff5cbb6e8980286929dcc5ec848006c5767 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/t_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 t(const at::Tensor & self); +TORCH_API at::Tensor & t_(at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triu_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triu_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..8b1203dde7a3d7f3deaea73e0fb1efa9c89669f3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/triu_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_triu : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, int64_t diagonal); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..3c1dc571ee89da6e1136a732b135cf8ea1de89d3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::upsample_nearest2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::upsample_nearest2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & upsample_nearest2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::upsample_nearest2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & upsample_nearest2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::upsample_nearest2d_backward_grad_input::call(grad_output, output_size, input_size, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & upsample_nearest2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::upsample_nearest2d_backward_grad_input::call(grad_output, output_size, input_size, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest2d_backward_grad_input::call(grad_output, output_size, input_size, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & upsample_nearest2d_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest2d_backward_grad_input::call(grad_output, output_size, input_size, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_nearest2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::upsample_nearest2d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor upsample_nearest2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::upsample_nearest2d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_h, scales_w); + } +} + +// aten::upsample_nearest2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_nearest2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::upsample_nearest2d_backward::call(grad_output, output_size, input_size, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor upsample_nearest2d_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt) { + return at::_ops::upsample_nearest2d_backward::call(grad_output, output_size, input_size, scales_h, scales_w); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..3484ddae0f65e155506572fdef80bdd781dc1baf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_upsample_trilinear3d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, bool align_corners, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w); +}; + +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..45d3cdaf5a6c51d494955fdc7ae0d66f089bb2f6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_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 { +TORCH_API at::Tensor upsample_trilinear3d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, c10::optional> scale_factors); +struct TORCH_API structured_upsample_trilinear3d_out_cpu : public at::meta::structured_upsample_trilinear3d { +void impl(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, const at::Tensor & out); +}; +struct TORCH_API structured_upsample_trilinear3d_out_cuda : public at::meta::structured_upsample_trilinear3d { +void impl(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/where_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/where_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f47c36a91f2d70d6fc347e2b9940a4ab754202a7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/where_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 where(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & where_out(at::Tensor & out, const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & where_outf(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at