diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_amp_update_scale_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_amp_update_scale_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..742268fe55815f22d111b7c7fa6685c6946cc071 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_amp_update_scale_meta_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 meta { + +TORCH_API at::Tensor & _amp_update_scale_(at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_backward_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dacd554c9832d5cd9c2ea42f0099d911bba1e743 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_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 & _cdist_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist); +TORCH_API at::Tensor & _cdist_backward_outf(const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesced_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesced_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eddef49ceb921a59f26806a645dbc09e12237dc3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_coalesced_meta_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 meta { + +TORCH_API at::Tensor & _coalesced_(at::Tensor & self, bool coalesced); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_compute_linear_combination.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_compute_linear_combination.h new file mode 100644 index 0000000000000000000000000000000000000000..074ac6a836dda2dae7a56ef16c7f171577670a3a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_compute_linear_combination.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::_compute_linear_combination(Tensor input, Tensor coefficients) -> Tensor +inline at::Tensor _compute_linear_combination(const at::Tensor & input, const at::Tensor & coefficients) { + return at::_ops::_compute_linear_combination::call(input, coefficients); +} + +// aten::_compute_linear_combination.out(Tensor input, Tensor coefficients, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _compute_linear_combination_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & coefficients) { + return at::_ops::_compute_linear_combination_out::call(input, coefficients, out); +} +// aten::_compute_linear_combination.out(Tensor input, Tensor coefficients, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _compute_linear_combination_outf(const at::Tensor & input, const at::Tensor & coefficients, at::Tensor & out) { + return at::_ops::_compute_linear_combination_out::call(input, coefficients, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a2b48fada15cda09725ea9319c9877b5c08884eb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_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 _cudnn_rnn { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const c10::optional &, const at::Tensor &, const c10::optional &, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, double, bool, bool, c10::SymIntArrayRef, const c10::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cudnn_rnn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional & weight_buf, const at::Tensor & hx, const c10::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const c10::optional & dropout_state); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional & weight_buf, const at::Tensor & hx, const c10::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const c10::optional & dropout_state); +}; + +struct TORCH_API _cudnn_rnn_out { + using schema = ::std::tuple (const at::Tensor &, at::TensorList, int64_t, const c10::optional &, const at::Tensor &, const c10::optional &, int64_t, c10::SymInt, c10::SymInt, int64_t, bool, double, bool, bool, c10::SymIntArrayRef, const c10::optional &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cudnn_rnn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!))") + static ::std::tuple call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional & weight_buf, const at::Tensor & hx, const c10::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const c10::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional & weight_buf, const at::Tensor & hx, const c10::optional & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const c10::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c5fa62c19f4ccb4af811639cce19bdfad1b5ee61 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_backward_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _embedding_bag_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, int64_t padding_idx=-1); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist.h new file mode 100644 index 0000000000000000000000000000000000000000..b350e32aef33da455cd371108a2c293b3a1b95c0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_euclidean_dist.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::_euclidean_dist(Tensor x1, Tensor x2) -> Tensor +inline at::Tensor _euclidean_dist(const at::Tensor & x1, const at::Tensor & x2) { + return at::_ops::_euclidean_dist::call(x1, x2); +} + +// aten::_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _euclidean_dist_out(at::Tensor & out, const at::Tensor & x1, const at::Tensor & x2) { + return at::_ops::_euclidean_dist_out::call(x1, x2, out); +} +// aten::_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _euclidean_dist_outf(const at::Tensor & x1, const at::Tensor & x2, at::Tensor & out) { + return at::_ops::_euclidean_dist_out::call(x1, x2, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dc8494ef3b1449843abe714aa2064f8fa15ef8f1 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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 _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 cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c829188a5280da28b23b0185ee02601099df0f6f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_has_same_storage_numel_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 _has_same_storage_numel(const at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask.h new file mode 100644 index 0000000000000000000000000000000000000000..4acb55513c96e2a08f9793de81e9e0736d022b39 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask.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::_nested_tensor_from_mask(Tensor t, Tensor mask, bool mask_check=True) -> Tensor +inline at::Tensor _nested_tensor_from_mask(const at::Tensor & t, const at::Tensor & mask, bool mask_check=true) { + return at::_ops::_nested_tensor_from_mask::call(t, mask, mask_check); +} + +// aten::_nested_tensor_from_mask.out(Tensor t, Tensor mask, bool mask_check=True, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_from_mask_out(at::Tensor & out, const at::Tensor & t, const at::Tensor & mask, bool mask_check=true) { + return at::_ops::_nested_tensor_from_mask_out::call(t, mask, mask_check, out); +} +// aten::_nested_tensor_from_mask.out(Tensor t, Tensor mask, bool mask_check=True, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_from_mask_outf(const at::Tensor & t, const at::Tensor & mask, bool mask_check, at::Tensor & out) { + return at::_ops::_nested_tensor_from_mask_out::call(t, mask, mask_check, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_pad_packed_sequence_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_pad_packed_sequence_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..15098948b51d7878750cae34deb926a8f71752c1 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_pad_packed_sequence_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 ::std::tuple _pad_packed_sequence(const at::Tensor & data, const at::Tensor & batch_sizes, bool batch_first, const at::Scalar & padding_value, int64_t total_length); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_from_tensor_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_from_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..534720d18a0c7c20f22f05786ea79b57270605ec --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_from_tensor_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 _reshape_from_tensor(const at::Tensor & self, const at::Tensor & shape); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_rowwise_prune_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_rowwise_prune_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3fb2b24304f214becc6718d9c457b975d9953a2e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_rowwise_prune_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 _rowwise_prune(const at::Tensor & weight, const at::Tensor & mask, at::ScalarType compressed_indices_dtype); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sobol_engine_initialize_state_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sobol_engine_initialize_state_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a9653ab22eea22df8e0b947fcfe0a002c84a4483 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sobol_engine_initialize_state_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 & _sobol_engine_initialize_state_(at::Tensor & self, int64_t dimension); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe.h new file mode 100644 index 0000000000000000000000000000000000000000..42594d4d43e70033649abdaa598b0f8bf4befae4 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe.h @@ -0,0 +1,34 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_csc_tensor_unsafe(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_csc_tensor_unsafe(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_sparse_csc_tensor_unsafe::call(ccol_indices, row_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::_sparse_csc_tensor_unsafe(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_csc_tensor_unsafe(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::_sparse_csc_tensor_unsafe::call(ccol_indices, row_indices, values, size, dtype, layout, device, pin_memory); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..73f537de500cb75126ac6b6d71df3a701346c7ac --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d_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 adaptive_avg_pool1d { + using schema = 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::adaptive_avg_pool1d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "adaptive_avg_pool1d(Tensor self, int[1] output_size) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::IntArrayRef output_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/amax_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/amax_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d1c2e1e8a19dde1af8532aa147e85c819ba40f42 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/amax_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor amax(const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); +TORCH_API at::Tensor & amax_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); +TORCH_API at::Tensor & amax_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/arcsin.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/arcsin.h new file mode 100644 index 0000000000000000000000000000000000000000..f184090987c5cbe1953b7fc9cb93cbb6f920b188 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/arcsin.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::arcsin(Tensor self) -> Tensor +inline at::Tensor arcsin(const at::Tensor & self) { + return at::_ops::arcsin::call(self); +} + +// aten::arcsin_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & arcsin_(at::Tensor & self) { + return at::_ops::arcsin_::call(self); +} + +// aten::arcsin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arcsin_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::arcsin_out::call(self, out); +} +// aten::arcsin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arcsin_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::arcsin_out::call(self, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/argwhere.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/argwhere.h new file mode 100644 index 0000000000000000000000000000000000000000..08d0695b5fc578fb4676498278d14b4511e25fdf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/argwhere.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::argwhere(Tensor self) -> Tensor +inline at::Tensor argwhere(const at::Tensor & self) { + return at::_ops::argwhere::call(self); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/asinh_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/asinh_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bd96863997d2b24756dbb309809e0d503347229a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/asinh_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor asinh(const at::Tensor & self); +TORCH_API at::Tensor & asinh_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_not_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_not_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cf94c9e57d6d19a7bea8a2006c2ef250c837e765 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_not_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 bitwise_not(const at::Tensor & self); +TORCH_API at::Tensor & bitwise_not_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & bitwise_not_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & bitwise_not_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cholesky_solve_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cholesky_solve_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4c4179801dc4b4795bbc212c1f56534341c62411 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cholesky_solve_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 cholesky_solve_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cholesky_solve") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cholesky_solve.out(Tensor self, Tensor input2, bool upper=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & input2, bool upper, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & input2, bool upper, at::Tensor & out); +}; + +struct TORCH_API cholesky_solve { + using schema = at::Tensor (const 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::cholesky_solve") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cholesky_solve(Tensor self, Tensor input2, bool upper=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & input2, bool upper); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & input2, bool upper); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/complex.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/complex.h new file mode 100644 index 0000000000000000000000000000000000000000..b49940b0c427ebd2ca7333f65b98d957e3cf488a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/complex.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::complex(Tensor real, Tensor imag) -> Tensor +inline at::Tensor complex(const at::Tensor & real, const at::Tensor & imag) { + return at::_ops::complex::call(real, imag); +} + +// aten::complex.out(Tensor real, Tensor imag, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & complex_out(at::Tensor & out, const at::Tensor & real, const at::Tensor & imag) { + return at::_ops::complex_out::call(real, imag, out); +} +// aten::complex.out(Tensor real, Tensor imag, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & complex_outf(const at::Tensor & real, const at::Tensor & imag, at::Tensor & out) { + return at::_ops::complex_out::call(real, imag, out); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/conj_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/conj_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bd47f05636b9c62ec6ea6e8bee6d14f016919629 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/conj_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 conj(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5e018c22f13f5629534c8c13405fc971d02d3358 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_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 cudnn_batch_norm { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cudnn_batch_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cudnn_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon); +}; + +struct TORCH_API cudnn_batch_norm_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cudnn_batch_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cummin_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cummin_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0b522404cf7975c19a5f2cbdb1ff504a5dd83b43 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/cummin_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 ::std::tuple cummin(const at::Tensor & self, at::Dimname dim); +TORCH_API ::std::tuple cummin_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim); +TORCH_API ::std::tuple cummin_outf(const at::Tensor & self, at::Dimname dim, at::Tensor & values, at::Tensor & indices); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/dequantize_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/dequantize_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..91d8e559c9d85862d9bb3343cebf53998ef619df --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/dequantize_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 dequantize(const at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_copy_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..404299ccc2653d5a2a67613e591d1d3de1e40794 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/diagonal_copy_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 diagonal_copy { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::diagonal_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "diagonal_copy(Tensor self, int offset=0, int dim1=0, int dim2=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2); +}; + +struct TORCH_API diagonal_copy_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::diagonal_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/div_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/div_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..33e1b8c6cbec95a64c5329732d3bf7e9c6b7c39c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/div_compositeexplicitautograd_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 compositeexplicitautograd { + +TORCH_API at::Tensor div(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor div(const at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/elu_backward_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/elu_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b956816a6fd929ac1f7dc186ed08cc68d18a3a2d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/elu_backward_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor elu_backward(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result); +TORCH_API at::Tensor & elu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result); +TORCH_API at::Tensor & elu_backward_outf(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/elu_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/elu_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fc01c74e6acb77b8e705ddc3cc05e348bd5bb87c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/elu_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor elu(const at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); +TORCH_API at::Tensor & elu_(at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fd3a7171863c75f270e163d584ce4dcae892d5ba --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API embedding { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymInt, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::embedding") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor") + static at::Tensor call(const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse); +}; + +struct TORCH_API embedding_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymInt, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::embedding") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/exp2_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/exp2_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c0f2c315108247cc974ba3dc0eb7c2b1ba493e1e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/exp2_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor exp2(const at::Tensor & self); +TORCH_API at::Tensor & exp2_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/feature_dropout_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/feature_dropout_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1a3ca662b32ffec219e226c197e8ec207fa117bc --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/feature_dropout_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor feature_dropout(const at::Tensor & input, double p, bool train); +TORCH_API at::Tensor & feature_dropout_(at::Tensor & self, double p, bool train); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fftfreq_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fftfreq_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f03df4121236d2c2cf9e3f339803c422cf3149d5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fftfreq_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_fftfreq { + using schema = at::Tensor (int64_t, double, 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::fft_fftfreq") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_fftfreq(int n, float d=1.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(int64_t n, double d, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, double d, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +}; + +struct TORCH_API fft_fftfreq_out { + using schema = at::Tensor & (int64_t, double, 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_fftfreq") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_fftfreq.out(int n, float d=1.0, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(int64_t n, double d, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, double d, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fmax_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fmax_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..97054aebdf2a440f0f51abf4f003663fc6d05c32 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/fmax_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor fmax(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmax_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/frobenius_norm_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/frobenius_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..75a9fed675d8c191464e5d3d0ccf742309e189e8 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/frobenius_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 frobenius_norm_dim { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::frobenius_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim); +}; + +struct TORCH_API frobenius_norm_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::frobenius_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/hardsigmoid_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/hardsigmoid_native.h new file mode 100644 index 0000000000000000000000000000000000000000..26bf9e33c217e1467ade2f0a68db013fa9f2f3eb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/hardsigmoid_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_hardsigmoid_out : public at::meta::structured_hardsigmoid { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor hardsigmoid_quantized_cpu(const at::Tensor & self); +TORCH_API at::Tensor & hardsigmoid_out_quantized_cpu(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/heaviside.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/heaviside.h new file mode 100644 index 0000000000000000000000000000000000000000..d276c070bc059328346f2a6257a0df810f58dafd --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/heaviside.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::heaviside.out(Tensor self, Tensor values, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & heaviside_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & values) { + return at::_ops::heaviside_out::call(self, values, out); +} +// aten::heaviside.out(Tensor self, Tensor values, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & heaviside_outf(const at::Tensor & self, const at::Tensor & values, at::Tensor & out) { + return at::_ops::heaviside_out::call(self, values, out); +} + +// aten::heaviside(Tensor self, Tensor values) -> Tensor +inline at::Tensor heaviside(const at::Tensor & self, const at::Tensor & values) { + return at::_ops::heaviside::call(self, values); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/heaviside_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/heaviside_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..39c520468b9d3671e6a5e847d0488e4d2a61635f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/heaviside_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor heaviside(const at::Tensor & self, const at::Tensor & values); +TORCH_API at::Tensor & heaviside_(at::Tensor & self, const at::Tensor & values); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_det_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_det_native.h new file mode 100644 index 0000000000000000000000000000000000000000..26490a7dfa2409255ddb90695075efc94ed0b4c3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_det_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 linalg_det(const at::Tensor & A); +TORCH_API at::Tensor & linalg_det_out(const at::Tensor & A, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_inv_ex_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_inv_ex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2b568c6ef4b47bcbc6ba1eb0157634ec33d68ccd --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_inv_ex_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_linalg_inv_ex_out : public at::meta::structured_linalg_inv_ex { +void impl(const at::Tensor & A, bool check_errors, const at::Tensor & inverse, const at::Tensor & info); +}; +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_tensorsolve_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_tensorsolve_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4067a5a9b33ac5cb9b128aa4960b3e5e007befdf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_tensorsolve_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor linalg_tensorsolve(const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims=c10::nullopt); +TORCH_API at::Tensor & linalg_tensorsolve_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims=c10::nullopt); +TORCH_API at::Tensor & linalg_tensorsolve_outf(const at::Tensor & self, const at::Tensor & other, at::OptionalIntArrayRef dims, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linear_backward_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linear_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8524ed838282448ce502ace50c14d85cc4ec45b2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/linear_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 linear_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linear_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linear_backward(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask) -> (Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask); +}; + +struct TORCH_API linear_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linear_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") + static ::std::tuple call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp2_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp2_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ff8b8d60632394a8aee5908179e552ede62f34fd --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp2_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 logaddexp2(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_unpool3d_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_unpool3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b2b7689b6eaa665d5299d21e633c804a25c685a5 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/max_unpool3d_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API max_unpool3d_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, at::IntArrayRef, 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::max_unpool3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "max_unpool3d.out(Tensor self, Tensor indices, SymInt[3] output_size, int[3] stride, int[3] padding, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); +}; + +struct TORCH_API max_unpool3d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, at::IntArrayRef, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::max_unpool3d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "max_unpool3d(Tensor self, Tensor indices, SymInt[3] output_size, int[3] stride, int[3] padding) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b87be6278a0c7e38199cd1e1f5f176a32c07517d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_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 minimum(const at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_cuda_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..13a50f76303ba1b336f82ecb4e3071506ced7088 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor minimum(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & minimum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & minimum_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/minimum_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6bba249cec6f5b699071724076bb0666935fda48 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_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 minimum { + 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::minimum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "minimum(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 minimum_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::minimum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "minimum.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); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..b16546905bc69c07e1617ff97543d405f17b91e2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_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::miopen_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[]) +inline ::std::tuple> miopen_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional & cx, const at::Tensor & output, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::miopen_rnn_backward::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); +} + +// aten::miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void miopen_rnn_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional & cx, const at::Tensor & output, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::miopen_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); +} +// aten::miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void miopen_rnn_backward_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional & cx, const at::Tensor & output, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3) { + return at::_ops::miopen_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e6fc13b72e17a3f08c66fe1aa23e79fb8aa63192 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_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 mkldnn_rnn_layer_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_rnn_layer_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_rnn_layer_backward(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace); +}; + +struct TORCH_API mkldnn_rnn_layer_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_rnn_layer_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_rnn_layer_backward.out(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5, Tensor(g!) out6) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!))") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_native.h new file mode 100644 index 0000000000000000000000000000000000000000..94bae7e82e4b3a124c25192220928da49a711c82 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/moveaxis_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 moveaxis(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination); +TORCH_API at::Tensor moveaxis(const at::Tensor & self, int64_t source, int64_t destination); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1d00b1584906c347aed0edfe40accd01f634b393 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_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 multilabel_margin_loss_forward_output { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::multilabel_margin_loss_forward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "output") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "multilabel_margin_loss_forward.output(Tensor self, Tensor target, int reduction, *, Tensor(a!) output, Tensor(b!) is_target) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); +}; + +struct TORCH_API multilabel_margin_loss_forward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::multilabel_margin_loss_forward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "multilabel_margin_loss_forward(Tensor self, Tensor target, int reduction) -> (Tensor output, Tensor is_target)") + static ::std::tuple call(const at::Tensor & self, const at::Tensor & target, int64_t reduction); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..604bd80d4c0b5c983b8499052dd70f342a3b604f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_copy.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::narrow_copy(Tensor self, int dim, SymInt start, SymInt length) -> Tensor +inline at::Tensor narrow_copy(const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow_copy::call(self, dim, start, length); +} +namespace symint { + template ::value>> + at::Tensor narrow_copy(const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow_copy::call(self, dim, start, length); + } +} + +// aten::narrow_copy(Tensor self, int dim, SymInt start, SymInt length) -> Tensor +inline at::Tensor narrow_copy_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow_copy::call(self, dim, start, length); +} +namespace symint { + template ::value>> + at::Tensor narrow_copy(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow_copy::call(self, dim, start, length); + } +} + +// aten::narrow_copy.out(Tensor self, int dim, SymInt start, SymInt length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & narrow_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); +} +namespace symint { + template ::value>> + at::Tensor & narrow_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t start, int64_t length) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); + } +} + +// aten::narrow_copy.out(Tensor self, int dim, SymInt start, SymInt length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & narrow_copy_outf(const at::Tensor & self, int64_t dim, int64_t start, int64_t length, at::Tensor & out) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); +} +namespace symint { + template ::value>> + at::Tensor & narrow_copy_outf(const at::Tensor & self, int64_t dim, int64_t start, int64_t length, at::Tensor & out) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); + } +} + +// aten::narrow_copy.out(Tensor self, int dim, SymInt start, SymInt length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & narrow_copy_symint_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); +} +namespace symint { + template ::value>> + at::Tensor & narrow_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); + } +} + +// aten::narrow_copy.out(Tensor self, int dim, SymInt start, SymInt length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & narrow_copy_symint_outf(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length, at::Tensor & out) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); +} +namespace symint { + template ::value>> + at::Tensor & narrow_copy_outf(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length, at::Tensor & out) { + return at::_ops::narrow_copy_out::call(self, dim, start, length, out); + } +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..50dd054b2223ccdf3aa700dc333ac14ea054060c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/native_batch_norm_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple native_batch_norm(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple native_batch_norm_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple native_batch_norm_outf(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_backward_cpu_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a5a7b1838c0d6b6962e4ad283dbb7ee6f7fe0244 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/nll_loss_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight); +TORCH_API at::Tensor nll_loss_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight); +TORCH_API at::Tensor & nll_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight); +TORCH_API at::Tensor & nll_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input); +TORCH_API at::Tensor & nll_loss_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight); +TORCH_API at::Tensor & nll_loss_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/or.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/or.h new file mode 100644 index 0000000000000000000000000000000000000000..95cbe60455dad48eb736d2d146599ba720013440 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/or.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::__or__.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor __or__(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::__or___Scalar::call(self, other); +} + +// aten::__or__.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor __or__(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::__or___Tensor::call(self, other); +} + +} diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/relu_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/relu_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..131b920493179ecfcb882e72806ae09291c8758a --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/relu_meta_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 meta { + +TORCH_API at::Tensor & relu_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2b40e647bb0e21a2d56a120d10b8427dfc2100a4 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor replication_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad1d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad3d_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad3d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..448b656bd8987037bf9e9be7f1e8176ce7420ab7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad3d_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor replication_pad3d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad3d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & replication_pad3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/round_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/round_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2c5ea7bc95cf3837176bdda92f107f0065dfb3cb --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/round_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 round(const at::Tensor & self); +TORCH_API at::Tensor & round_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & round_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & round_(at::Tensor & self); +TORCH_API at::Tensor round(const at::Tensor & self, int64_t decimals); +TORCH_API at::Tensor & round_out(at::Tensor & out, const at::Tensor & self, int64_t decimals); +TORCH_API at::Tensor & round_outf(const at::Tensor & self, int64_t decimals, at::Tensor & out); +TORCH_API at::Tensor & round_(at::Tensor & self, int64_t decimals); + +} // namespace meta +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rrelu_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rrelu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6468b6532937471b856b263df4f6264408c41894 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/rrelu_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 rrelu(const at::Tensor & self, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & rrelu_(at::Tensor & self, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, c10::optional generator=c10::nullopt); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/signbit_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/signbit_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9d9afd34ee4ad9bf8254ef02850d035faf7a961b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/signbit_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 signbit { + 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::signbit") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "signbit(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 signbit_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::signbit") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "signbit.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/slice_copy_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slice_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ea7dcd2ffd363a03ef72d3ff758d052650527354 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slice_copy_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API slice_copy_Tensor { + using schema = at::Tensor (const at::Tensor &, int64_t, c10::optional, c10::optional, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slice_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slice_copy.Tensor(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim, c10::optional start, c10::optional end, c10::SymInt step); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional start, c10::optional end, c10::SymInt step); +}; + +struct TORCH_API slice_copy_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, c10::optional, c10::optional, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slice_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t dim, c10::optional start, c10::optional end, c10::SymInt step, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional start, c10::optional end, c10::SymInt step, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv3d_native.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cd2bf54e7743af06f79ed55025a7875e632eb985 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/slow_conv3d_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 slow_conv3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0); +TORCH_API at::Tensor & slow_conv3d_out(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/soft_margin_loss_compositeexplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/soft_margin_loss_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb536ed9168d5b1b6332b4742e667564b17e4858 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/soft_margin_loss_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 at::Tensor soft_margin_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & soft_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & soft_margin_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/stride_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/stride_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9914ee31e9de530d9a6dcf8e993d76055a925089 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/stride_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 int64_t stride(const at::Tensor & self, int64_t dim); +TORCH_API int64_t stride(const at::Tensor & self, at::Dimname dim); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/svd_compositeimplicitautograd_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/svd_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ded1579c82c630e6e7c4ce60e063f4e32795844 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/svd_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 ::std::tuple svd(const at::Tensor & self, bool some=true, bool compute_uv=true); +TORCH_API ::std::tuple svd_out(at::Tensor & U, at::Tensor & S, at::Tensor & V, const at::Tensor & self, bool some=true, bool compute_uv=true); +TORCH_API ::std::tuple svd_outf(const at::Tensor & self, bool some, bool compute_uv, at::Tensor & U, at::Tensor & S, at::Tensor & V); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tan_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tan_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b84dd7d62e6b8f00b45c5de9dc37b1906d78da79 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tan_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor tan(const at::Tensor & self); +TORCH_API at::Tensor & tan_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tensordot_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tensordot_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..023a1dec6beb2dd53e6e66af495a7247f7fe89ae --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tensordot_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 tensordot { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::tensordot") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "tensordot(Tensor self, Tensor other, int[] dims_self, int[] dims_other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other); +}; + +struct TORCH_API tensordot_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, 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::tensordot") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "tensordot.out(Tensor self, Tensor other, int[] dims_self, int[] dims_other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tril_compositeexplicitautogradnonfunctional_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tril_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3dee6f46b9ab4f6ebaa7afcc0d22a98cd66d42d4 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/tril_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor tril(const at::Tensor & self, int64_t diagonal=0); +TORCH_API at::Tensor & tril_(at::Tensor & self, int64_t diagonal=0); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_ops.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ee985f3e5eee10b25642e05bd885f11d7face79e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_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 unsqueeze_copy { + using schema = at::Tensor (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::unsqueeze_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "unsqueeze_copy(Tensor self, int dim) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +struct TORCH_API unsqueeze_copy_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::unsqueeze_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..48c7575bb9b8010ceb77d7334a9233ff38b20d29 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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_bicubic2d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, 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_nearest2d_backward_meta.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..5cc58b1d564821edb0ebc56699d97ae907edaa1c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_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_nearest2d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, 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_nearest2d_meta_dispatch.h b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e82343ad6bc40c42252924ad2ceb05fb0d77f8ea --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor upsample_nearest2d(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor upsample_nearest2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_outf(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); + +} // namespace meta +} // namespace at