diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d8ec93edd045a2e69319ea5586a1fb2eb0666710 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _adaptive_avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..56af52705451b8e0eeeff5ebcbc9dbaa66059ed7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_backward_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _adaptive_avg_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_tensor_metadata_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_tensor_metadata_native.h new file mode 100644 index 0000000000000000000000000000000000000000..688315e5172ce0d692d862c72f332c1d3086c6c6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_tensor_metadata_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 void _assert_tensor_metadata(const at::Tensor & a, at::OptionalIntArrayRef size=::std::nullopt, at::OptionalIntArrayRef stride=::std::nullopt, ::std::optional dtype=::std::nullopt, ::std::optional device=::std::nullopt, ::std::optional layout=::std::nullopt); +TORCH_API void _assert_tensor_metadata_meta_symint(const at::Tensor & a, at::OptionalSymIntArrayRef size=::std::nullopt, at::OptionalSymIntArrayRef stride=::std::nullopt, ::std::optional dtype=::std::nullopt, ::std::optional device=::std::nullopt, ::std::optional layout=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_impl_index_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_impl_index_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..56e424c5d86f1a1ce87eb87196eb1747b2556dd6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_impl_index_backward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _batch_norm_impl_index_backward { + using schema = ::std::tuple (int64_t, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, ::std::array, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_batch_norm_impl_index_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_batch_norm_impl_index_backward(int impl_index, Tensor input, Tensor grad_output, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var_transform, bool train, float eps, bool[3] output_mask, Tensor reservedSpace) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(int64_t impl_index, const at::Tensor & input, const at::Tensor & grad_output, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var_transform, bool train, double eps, ::std::array output_mask, const at::Tensor & reservedSpace); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, int64_t impl_index, const at::Tensor & input, const at::Tensor & grad_output, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var_transform, bool train, double eps, ::std::array output_mask, const at::Tensor & reservedSpace); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_impl_index_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_impl_index_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3a7b63bc13d70f556d567656ab41173a03e4a7cb --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_batch_norm_impl_index_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 _batch_norm_impl_index { + using schema = ::std::tuple (const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, double, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_batch_norm_impl_index"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_batch_norm_impl_index(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> (Tensor, Tensor, Tensor, Tensor, int)"; + static ::std::tuple call(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, bool cudnn_enabled); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, bool cudnn_enabled); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Char.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Char.h new file mode 100644 index 0000000000000000000000000000000000000000..0721c7ea4a383b7fffd091fcd6b8f1224c6aa95b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Char.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::_cast_Char(Tensor self, bool non_blocking=False) -> Tensor +inline at::Tensor _cast_Char(const at::Tensor & self, bool non_blocking=false) { + return at::_ops::_cast_Char::call(self, non_blocking); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Long_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Long_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f052cfe278e6244aec649ec854d8776af0781571 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Long_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _cast_Long(const at::Tensor & self, bool non_blocking=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd0011ea888d427d54847829d02e4da0842bc233 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _cdist_forward(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cholesky_solve_helper_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cholesky_solve_helper_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bdd7f77021e40da59b02212be6eda3ed789e7297 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cholesky_solve_helper_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 & _cholesky_solve_helper_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & A, bool upper); +TORCH_API at::Tensor & _cholesky_solve_helper_outf(const at::Tensor & self, const at::Tensor & A, bool upper, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_choose_qparams_per_tensor_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_choose_qparams_per_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d5c44c4287c5ef2ec95b7e14c01799154e3b88a6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_choose_qparams_per_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 ::std::tuple _choose_qparams_per_tensor(const at::Tensor & self, bool reduce_range=false); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat.h new file mode 100644 index 0000000000000000000000000000000000000000..d270ada1243cda646c6d44f39340a323bed50b23 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_chunk_cat.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::_chunk_cat(Tensor[] tensors, int dim, int num_chunks) -> Tensor +inline at::Tensor _chunk_cat(at::TensorList tensors, int64_t dim, int64_t num_chunks) { + return at::_ops::_chunk_cat::call(tensors, dim, num_chunks); +} + +// aten::_chunk_cat.out(Tensor[] tensors, int dim, int num_chunks, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _chunk_cat_out(at::Tensor & out, at::TensorList tensors, int64_t dim, int64_t num_chunks) { + return at::_ops::_chunk_cat_out::call(tensors, dim, num_chunks, out); +} +// aten::_chunk_cat.out(Tensor[] tensors, int dim, int num_chunks, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _chunk_cat_outf(at::TensorList tensors, int64_t dim, int64_t num_chunks, at::Tensor & out) { + return at::_ops::_chunk_cat_out::call(tensors, dim, num_chunks, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..166e5728756316f68c5d978b6370e961cf2c22fc --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _conj_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1c2f42159777c782b471196c73b52d71362ca3b6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_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 _cslt_sparse_mm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, ::std::optional, bool, int64_t, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_cslt_sparse_mm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_cslt_sparse_mm(Tensor compressed_A, Tensor dense_B, Tensor? bias=None, Tensor? alpha=None, ScalarType? out_dtype=None, bool transpose_result=False, int alg_id=0, int split_k=1, bool split_k_one_kernel=True) -> Tensor"; + static at::Tensor call(const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias, const ::std::optional & alpha, ::std::optional out_dtype, bool transpose_result, int64_t alg_id, int64_t split_k, bool split_k_one_kernel); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias, const ::std::optional & alpha, ::std::optional out_dtype, bool transpose_result, int64_t alg_id, int64_t split_k, bool split_k_one_kernel); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ed1a0ebdf20ea9deb348f24e2b1fbc1d1f5a29bc --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); +TORCH_API at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2682f353aad5047ffd6b9bbb38af36dad7b2a5c9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_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 ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..685aca13f12f50deef95d8e4dfaff9625d0d5b5c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple> _cudnn_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +TORCH_API ::std::tuple> _cudnn_rnn_backward_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, 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 ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..496ae020a4c1efba6876d2f95683b47b3bdf7a69 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight.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::_cudnn_rnn_flatten_weight(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional) -> Tensor +inline at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional); +} +namespace symint { + template >> + at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional); + } +} + +// aten::_cudnn_rnn_flatten_weight(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional) -> Tensor +inline at::Tensor _cudnn_rnn_flatten_weight_symint(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional); +} +namespace symint { + template >> + at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional); + } +} + +// aten::_cudnn_rnn_flatten_weight.out(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_rnn_flatten_weight_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); +} +namespace symint { + template >> + at::Tensor & _cudnn_rnn_flatten_weight_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); + } +} + +// aten::_cudnn_rnn_flatten_weight.out(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_rnn_flatten_weight_outf(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); +} +namespace symint { + template >> + at::Tensor & _cudnn_rnn_flatten_weight_outf(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); + } +} + +// aten::_cudnn_rnn_flatten_weight.out(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_rnn_flatten_weight_symint_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); +} +namespace symint { + template >> + at::Tensor & _cudnn_rnn_flatten_weight_out(at::Tensor & out, at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); + } +} + +// aten::_cudnn_rnn_flatten_weight.out(Tensor[] weight_arr, int weight_stride0, SymInt input_size, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, bool bidirectional, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _cudnn_rnn_flatten_weight_symint_outf(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); +} +namespace symint { + template >> + at::Tensor & _cudnn_rnn_flatten_weight_outf(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional, at::Tensor & out) { + return at::_ops::_cudnn_rnn_flatten_weight_out::call(weight_arr, weight_stride0, input_size, mode, hidden_size, proj_size, num_layers, batch_first, bidirectional, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..705f92e0dae8a12bcf85b48320db4e505c88530e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional); +TORCH_API at::Tensor _cudnn_rnn_flatten_weight_symint(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_dimV_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_dimV_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..95c0edf226fded20520042e898dd9725ee9e1c01 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_dimV_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 _dimV { + using schema = int64_t (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_dimV"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_dimV(Tensor self) -> int"; + static int64_t call(const at::Tensor & self); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9a69aac8687a192d7535222f15b2c52d74a69e98 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple _embedding_bag_forward_only(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..65ddcff310c5838c0ae908b471e4cbbbbaffb868 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_empty_per_channel_affine_quantized_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _empty_per_channel_affine_quantized { + using schema = at::Tensor (c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, int64_t, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_empty_per_channel_affine_quantized"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_empty_per_channel_affine_quantized(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor"; + static at::Tensor call(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +}; + +struct TORCH_API _empty_per_channel_affine_quantized_out { + using schema = at::Tensor & (c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, int64_t, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_empty_per_channel_affine_quantized"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_empty_per_channel_affine_quantized.out(SymInt[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, ::std::optional memory_format, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..34d22bbeaba66cbcf922a82099ba7b280783eb4e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _fake_quantize_learnable_per_channel_affine_backward(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..038d80f96d37cb279eb5599dfe06f76ca68efbe5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _fake_quantize_learnable_per_channel_affine_backward(const at::Tensor & grad, 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 native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7b82288d3309966ba842d96ffc33c3c69de0df17 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fake_quantize_learnable_per_channel_affine_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, int64_t, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fake_quantize_learnable_per_channel_affine_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fake_quantize_learnable_per_channel_affine_backward(Tensor grad, Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & grad, 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); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, 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); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c3b7af9484fd7f48a4cb60df71b3f8aa6a3e3994 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _fake_quantize_learnable_per_channel_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7cec2fedff17ebc8ea4b8113bdf6b27634edd9e7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max); +TORCH_API ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_outf(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2bfb7862cd1a3c3f826a782f7ff89debaa18920f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c_native.h new file mode 100644 index 0000000000000000000000000000000000000000..995ca852b8e0be9dc0b22e9990571bc98b9b9160 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _fft_c2c_mkl(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward); +TORCH_API at::Tensor & _fft_c2c_mkl_out(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out); +TORCH_API at::Tensor _fft_c2c_cufft(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward); +TORCH_API at::Tensor & _fft_c2c_cufft_out(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask.h new file mode 100644 index 0000000000000000000000000000000000000000..2d3c16c4a88230880b143d01cf8d401be33bddda --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask.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::_fill_mem_eff_dropout_mask_(Tensor(a!) self, float dropout_p, int seed, int offset) -> Tensor(a!) +inline at::Tensor & _fill_mem_eff_dropout_mask_(at::Tensor & self, double dropout_p, int64_t seed, int64_t offset) { + return at::_ops::_fill_mem_eff_dropout_mask_::call(self, dropout_p, seed, offset); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcdiv_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcdiv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a64e2556827f030577127aad4d0d307dc46f30d5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcdiv_ops.h @@ -0,0 +1,116 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_addcdiv_Scalar { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); +}; + +struct TORCH_API _foreach_addcdiv_ScalarList { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_addcdiv_Tensor { + using schema = ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +}; + +struct TORCH_API _foreach_addcdiv__Scalar { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value); +}; + +struct TORCH_API _foreach_addcdiv__ScalarList { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_addcdiv__Tensor { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +}; + +struct TORCH_API _foreach_addcdiv_Scalar_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_addcdiv.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +}; + +struct TORCH_API _foreach_addcdiv_ScalarList_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_addcdiv.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +}; + +struct TORCH_API _foreach_addcdiv_Tensor_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_addcdiv"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f3cd6728a550d3bddc18143858bb2f70ce18b7bd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h @@ -0,0 +1,34 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcmul(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cosh_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cosh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ebd2c1bce1bcbe9b400f5a33f260ad4cee13abe --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cosh_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_cosh(at::TensorList self); +TORCH_API void _foreach_cosh_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erf_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erf_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9b81a69870a4a9c05f8e07445de08c69686107c4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erf_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_erf(at::TensorList self); +TORCH_API void _foreach_erf_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_lerp_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_lerp_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e6884f9eed8fb17538a954a09e07c2abd1247f91 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_lerp_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, at::TensorList weights); +TORCH_API ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +TORCH_API ::std::vector _foreach_lerp(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +TORCH_API void _foreach_lerp_(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_neg_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_neg_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2712134847d4fea3c58c91f02a0251ba627f2eb5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_neg_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_neg(at::TensorList self); +TORCH_API void _foreach_neg_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_pow_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_pow_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f89adc4c560263653349462ca34174f26a7deb22 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_pow_ops.h @@ -0,0 +1,127 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_pow_List { + using schema = ::std::vector (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_pow.List(Tensor[] self, Tensor[] exponent) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList exponent); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList exponent); +}; + +struct TORCH_API _foreach_pow_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_pow.Scalar(Tensor[] self, Scalar exponent) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & exponent); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & exponent); +}; + +struct TORCH_API _foreach_pow_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_pow.ScalarList(Tensor[] self, Scalar[] exponent) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef exponent); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef exponent); +}; + +struct TORCH_API _foreach_pow_ScalarAndTensor { + using schema = ::std::vector (const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow"; + static constexpr const char* overload_name = "ScalarAndTensor"; + static constexpr const char* schema_str = "_foreach_pow.ScalarAndTensor(Scalar self, Tensor[] exponent) -> Tensor[]"; + static ::std::vector call(const at::Scalar & self, at::TensorList exponent); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, at::TensorList exponent); +}; + +struct TORCH_API _foreach_pow__List { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_pow_.List(Tensor(a!)[] self, Tensor[] exponent) -> ()"; + static void call(at::TensorList self, at::TensorList exponent); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList exponent); +}; + +struct TORCH_API _foreach_pow__Scalar { + using schema = void (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_pow_.Scalar(Tensor(a!)[] self, Scalar exponent) -> ()"; + static void call(at::TensorList self, const at::Scalar & exponent); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & exponent); +}; + +struct TORCH_API _foreach_pow__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_pow_.ScalarList(Tensor(a!)[] self, Scalar[] exponent) -> ()"; + static void call(at::TensorList self, at::ArrayRef exponent); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef exponent); +}; + +struct TORCH_API _foreach_pow_List_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_pow.List_out(Tensor[] self, Tensor[] exponent, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList exponent, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList exponent, at::TensorList out); +}; + +struct TORCH_API _foreach_pow_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_pow.Scalar_out(Tensor[] self, Scalar exponent, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & exponent, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & exponent, at::TensorList out); +}; + +struct TORCH_API _foreach_pow_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_pow"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_pow.ScalarList_out(Tensor[] self, Scalar[] exponent, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef exponent, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef exponent, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fb35f93cfc7dd6f1470cd1914b54ee0b1f588aab --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_round { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_round"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_round(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_round_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_round_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_round_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_round_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_round"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_round.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt.h new file mode 100644 index 0000000000000000000000000000000000000000..189b9462cc3a8c2982dcab8de8943fb9357d25b6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_rsqrt.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_rsqrt(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_rsqrt(at::TensorList self) { + return at::_ops::_foreach_rsqrt::call(self); +} + +// aten::_foreach_rsqrt_(Tensor(a!)[] self) -> () +inline void _foreach_rsqrt_(at::TensorList self) { + return at::_ops::_foreach_rsqrt_::call(self); +} + +// aten::_foreach_rsqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_rsqrt_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_rsqrt_out::call(self, out); +} +// aten::_foreach_rsqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_rsqrt_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_rsqrt_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sign_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sign_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2c8820fd662ba35de5bd8cf18ee7487c43592446 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sign_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_sign { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sign"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sign(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sign_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sign_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sign_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sign_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_sign"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_sign.out(Tensor[] self, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sin_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sin_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d6c5d3515c9bc8f66a412bdb689e03e0cb445a2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sin_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_sin(at::TensorList self); +TORCH_API void _foreach_sin_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_sin_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_sin_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tan_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tan_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ff335e42968c0d878590d91fa19272ef7140419 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_tan_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_tan(at::TensorList self); +TORCH_API void _foreach_tan_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fa05dda89d878f598d323a08390dea758dc05c62 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adamw_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API void _fused_adamw_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adamw_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_dropout.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_dropout.h new file mode 100644 index 0000000000000000000000000000000000000000..f032737f9228b7262e69301fe98fa540d09dfe90 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_dropout.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::_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor) +inline ::std::tuple _fused_dropout(const at::Tensor & self, double p, ::std::optional generator=::std::nullopt) { + return at::_ops::_fused_dropout::call(self, p, generator); +} + +// aten::_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _fused_dropout_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, double p, ::std::optional generator=::std::nullopt) { + return at::_ops::_fused_dropout_out::call(self, p, generator, out0, out1); +} +// aten::_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _fused_dropout_outf(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_fused_dropout_out::call(self, p, generator, out0, out1); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal.h new file mode 100644 index 0000000000000000000000000000000000000000..139c213b2cd12649e246a82ac0621ac6f3198aaf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c1cb1e3b98461d927bf2bbde0318c752823e349e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_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 _fw_primal(const at::Tensor & self, int64_t level); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_gather_sparse_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_gather_sparse_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b6b0eeb61bf0075de2429cf6497861868960f69c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_gather_sparse_backward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _gather_sparse_backward { + using schema = at::Tensor (const at::Tensor &, int64_t, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_gather_sparse_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_gather_sparse_backward(Tensor self, int dim, Tensor index, Tensor grad) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts.h new file mode 100644 index 0000000000000000000000000000000000000000..bbb93fb4ec24016573a3cde48db4d9db6a555950 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts.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::_histogramdd_from_bin_cts(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False) -> Tensor +inline at::Tensor _histogramdd_from_bin_cts(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false) { + return at::_ops::_histogramdd_from_bin_cts::call(self, bins, range, weight, density); +} + +// aten::_histogramdd_from_bin_cts.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _histogramdd_from_bin_cts_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false) { + return at::_ops::_histogramdd_from_bin_cts_out::call(self, bins, range, weight, density, out); +} +// aten::_histogramdd_from_bin_cts.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _histogramdd_from_bin_cts_outf(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density, at::Tensor & out) { + return at::_ops::_histogramdd_from_bin_cts_out::call(self, bins, range, weight, density, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_indices_copy.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_indices_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..6952097a50446749a287bb47394c43f52431129e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_indices_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_indices_copy(Tensor self) -> Tensor +inline at::Tensor _indices_copy(const at::Tensor & self) { + return at::_ops::_indices_copy::call(self); +} + +// aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _indices_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::_indices_copy_out::call(self, out); +} +// aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _indices_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::_indices_copy_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f5e98cc3184bb7d4fa6da515a8513bd71ff6552d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_indices_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _indices_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_int_mm_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_int_mm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..48896f821ee21ac0539b065dcaa92c2e1c65604e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_int_mm_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 _int_mm { + 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 const char* name = "aten::_int_mm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_int_mm(Tensor self, Tensor mat2) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2); +}; + +struct TORCH_API _int_mm_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 const char* name = "aten::_int_mm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_int_mm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_is_all_true_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_is_all_true_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e6c8a1fe3f476d0e53edd2855eb6c6cb84ac8322 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_is_all_true_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _is_all_true { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_is_all_true"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_is_all_true(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_check_errors_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_check_errors_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bfce0fa450862838384fe638756dc1343de078b9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_check_errors_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void _linalg_check_errors(const at::Tensor & info, c10::string_view api_name, bool is_matrix); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det.h new file mode 100644 index 0000000000000000000000000000000000000000..4be65268b81e3f64c85cce1c7946e7d0d6da86ab --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_linalg_det(Tensor A) -> (Tensor result, Tensor LU, Tensor pivots) +inline ::std::tuple _linalg_det(const at::Tensor & A) { + return at::_ops::_linalg_det::call(A); +} + +// aten::_linalg_det.result(Tensor A, *, Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots) -> (Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots) +inline ::std::tuple _linalg_det_out(at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, const at::Tensor & A) { + return at::_ops::_linalg_det_result::call(A, result, LU, pivots); +} +// aten::_linalg_det.result(Tensor A, *, Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots) -> (Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots) +inline ::std::tuple _linalg_det_outf(const at::Tensor & A, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots) { + return at::_ops::_linalg_det_result::call(A, result, LU, pivots); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..580051ab9404f559ceb37313f84908bf25dcfc92 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigh_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _linalg_eigh { + using schema = ::std::tuple (const at::Tensor &, c10::string_view, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_linalg_eigh"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_linalg_eigh(Tensor A, str UPLO=\"L\", bool compute_v=True) -> (Tensor eigenvalues, Tensor eigenvectors)"; + static ::std::tuple call(const at::Tensor & A, c10::string_view UPLO, bool compute_v); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::string_view UPLO, bool compute_v); +}; + +struct TORCH_API _linalg_eigh_eigenvalues { + using schema = ::std::tuple (const at::Tensor &, c10::string_view, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_linalg_eigh"; + static constexpr const char* overload_name = "eigenvalues"; + static constexpr const char* schema_str = "_linalg_eigh.eigenvalues(Tensor A, str UPLO=\"L\", bool compute_v=True, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors)"; + static ::std::tuple call(const at::Tensor & A, c10::string_view UPLO, bool compute_v, at::Tensor & eigenvalues, at::Tensor & eigenvectors); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::string_view UPLO, bool compute_v, at::Tensor & eigenvalues, at::Tensor & eigenvectors); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..17840deff334d536daf88ee898404145f17b9968 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_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 _linalg_eigvals(const at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80895cfb84e1f413ca00171e7993f40b67a3b822 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _linalg_eigvals { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_linalg_eigvals"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_linalg_eigvals(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_slogdet_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_slogdet_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cbb7035b8ec58ad2122d66397e789d4499a95bc7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_slogdet_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__linalg_slogdet : public at::impl::MetaBase { + + + void meta(const at::Tensor & A); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_slogdet_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_slogdet_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..35c906a3224ae5c15f1b03f943ea8891b342a3ee --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_slogdet_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API ::std::tuple _linalg_slogdet(const at::Tensor & A); +TORCH_API ::std::tuple _linalg_slogdet_out(at::Tensor & sign, at::Tensor & logabsdet, at::Tensor & LU, at::Tensor & pivots, const at::Tensor & A); +TORCH_API ::std::tuple _linalg_slogdet_outf(const at::Tensor & A, at::Tensor & sign, at::Tensor & logabsdet, at::Tensor & LU, at::Tensor & pivots); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data.h new file mode 100644 index 0000000000000000000000000000000000000000..49a171471f82ab33eb69fa97851c4b82cb0ed285 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_log_softmax_backward_data.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::_log_softmax_backward_data(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype) -> Tensor +inline at::Tensor _log_softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype) { + return at::_ops::_log_softmax_backward_data::call(grad_output, output, dim, input_dtype); +} + +// aten::_log_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _log_softmax_backward_data_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype) { + return at::_ops::_log_softmax_backward_data_out::call(grad_output, output, dim, input_dtype, out); +} +// aten::_log_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _log_softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, at::Tensor & out) { + return at::_ops::_log_softmax_backward_data_out::call(grad_output, output, dim, input_dtype, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dep_token_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dep_token_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6f97f3fbec883002ebb45a5412a25b77370a4757 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dep_token_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 _make_dep_token_cpu(::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..da485c0759a9203d7f22b8fa9b6d4e9710114cac --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _make_per_channel_quantized_tensor(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2a6f90dd87402c9c39151641e0e75aaaaa433f29 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _make_per_channel_quantized_tensor_out(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, at::Tensor & out); +TORCH_API at::Tensor make_per_channel_quantized_tensor_cpu(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis); +TORCH_API at::Tensor make_per_channel_quantized_tensor_cuda(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..64ac82065ba6ef71422b1353954d5eacba996ebd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_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 & _mps_convolution_out_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_copy_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b8668ad456185eac24242e80f3f77bc5229d8a38 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_copy_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 & _neg_view_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _neg_view_copy(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_and_nested_example_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_and_nested_example_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0510927a120e8a6353faf3fa05542c42510e6893 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_and_nested_example_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 & _nested_from_padded_and_nested_example_out(at::Tensor & out, const at::Tensor & padded, const at::Tensor & nt_example); +TORCH_API at::Tensor & _nested_from_padded_and_nested_example_outf(const at::Tensor & padded, const at::Tensor & nt_example, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_and_nested_example_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_and_nested_example_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1b989b3e646e5e26b66bf55cae162dfd4d40c310 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_and_nested_example_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _nested_from_padded_and_nested_example { + 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 const char* name = "aten::_nested_from_padded_and_nested_example"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_nested_from_padded_and_nested_example(Tensor padded, Tensor nt_example) -> Tensor"; + static at::Tensor call(const at::Tensor & padded, const at::Tensor & nt_example); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & padded, const at::Tensor & nt_example); +}; + +struct TORCH_API _nested_from_padded_and_nested_example_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 const char* name = "aten::_nested_from_padded_and_nested_example"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_nested_from_padded_and_nested_example.out(Tensor padded, Tensor nt_example, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & padded, const at::Tensor & nt_example, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & padded, const at::Tensor & nt_example, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_native.h new file mode 100644 index 0000000000000000000000000000000000000000..067faef95f97eb2a9d5af925253795b6a89ad3ba --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _nested_from_padded_out(const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213, at::Tensor & out); +TORCH_API at::Tensor nested_from_padded_generic(const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213=false); +TORCH_API at::Tensor nested_from_padded_cuda(const at::Tensor & padded, const at::Tensor & cpu_nested_shape_example, bool fuse_transform_0213=false); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_min_seqlen.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_min_seqlen.h new file mode 100644 index 0000000000000000000000000000000000000000..204712f426f4d97dc081d3f5c5109dc492d57cd9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_min_seqlen.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::_nested_get_min_seqlen(Tensor self) -> Tensor +inline at::Tensor _nested_get_min_seqlen(const at::Tensor & self) { + return at::_ops::_nested_get_min_seqlen::call(self); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_tensor_list.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_tensor_list.h new file mode 100644 index 0000000000000000000000000000000000000000..b90534f8e1d9107658dcad2694cdc69d2f3e7de6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_tensor_list.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_tensor_list(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _nested_tensor_from_tensor_list(at::TensorList list, ::std::optional dtype=::std::nullopt, ::std::optional layout=::std::nullopt, ::std::optional device=::std::nullopt, ::std::optional pin_memory=::std::nullopt) { + return at::_ops::_nested_tensor_from_tensor_list::call(list, dtype, layout, device, pin_memory); +} + +// aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_from_tensor_list_out(at::Tensor & out, at::TensorList list, ::std::optional dtype=::std::nullopt, ::std::optional layout=::std::nullopt, ::std::optional device=::std::nullopt, ::std::optional pin_memory=::std::nullopt) { + return at::_ops::_nested_tensor_from_tensor_list_out::call(list, dtype, layout, device, pin_memory, out); +} +// aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_tensor_from_tensor_list_outf(at::TensorList list, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, at::Tensor & out) { + return at::_ops::_nested_tensor_from_tensor_list_out::call(list, dtype, layout, device, pin_memory, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_jagged_copy_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_jagged_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc7d764d9fa523fc8e957a1a46f6a55f9d4d2d15 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_jagged_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _nested_view_from_jagged_copy(const at::Tensor & self, const at::Tensor & offsets, const at::Tensor & dummy, const ::std::optional & lengths={}, int64_t ragged_idx=1, const ::std::optional & min_seqlen={}, const ::std::optional & max_seqlen={}); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..94a9000ced75aba2e3f40d463d08cc5c0c8bb5e3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_compositeexplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple _pack_padded_sequence(const at::Tensor & input, const at::Tensor & lengths, bool batch_first); +TORCH_API ::std::tuple _pack_padded_sequence_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & input, const at::Tensor & lengths, bool batch_first); +TORCH_API ::std::tuple _pack_padded_sequence_outf(const at::Tensor & input, const at::Tensor & lengths, bool batch_first, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_enum_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_enum_native.h new file mode 100644 index 0000000000000000000000000000000000000000..23bc4e837316874a917f979842127e2566737d92 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_pad_enum_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 _pad_enum_symint(const at::Tensor & self, c10::SymIntArrayRef pad, int64_t mode, ::std::optional value=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_forward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..7a8f5ef257ac204a58bb46975b4a5667c0487c52 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_pdist_forward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_pdist_forward(Tensor self, float p=2) -> Tensor +inline at::Tensor _pdist_forward(const at::Tensor & self, double p=2) { + return at::_ops::_pdist_forward::call(self, p); +} + +// aten::_pdist_forward.out(Tensor self, float p=2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _pdist_forward_out(at::Tensor & out, const at::Tensor & self, double p=2) { + return at::_ops::_pdist_forward_out::call(self, p, out); +} +// aten::_pdist_forward.out(Tensor self, float p=2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _pdist_forward_outf(const at::Tensor & self, double p, at::Tensor & out) { + return at::_ops::_pdist_forward_out::call(self, p, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..362e14dfb08822ac710295ebd436bee0732bf35f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_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 _prelu_kernel { + 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 const char* name = "aten::_prelu_kernel"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_prelu_kernel(Tensor self, Tensor weight) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b5a9bdf468d3a47c1b9f961c011d96df65918e01 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet_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 _sample_dirichlet(const at::Tensor & self, ::std::optional generator=::std::nullopt); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_for_cpu_backward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_for_cpu_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..1bc8658b8542f0f4ee70e4604603fd2ebd4d74bb --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_for_cpu_backward.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::_scaled_dot_product_flash_attention_for_cpu_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, float dropout_p, bool is_causal, *, Tensor? attn_mask=None, float? scale=None) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value) +inline ::std::tuple _scaled_dot_product_flash_attention_for_cpu_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, double dropout_p, bool is_causal, const ::std::optional & attn_mask={}, ::std::optional scale=::std::nullopt) { + return at::_ops::_scaled_dot_product_flash_attention_for_cpu_backward::call(grad_out, query, key, value, out, logsumexp, dropout_p, is_causal, attn_mask, scale); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable.h new file mode 100644 index 0000000000000000000000000000000000000000..391738d7a8a97ddd39f998fda1532d5d551b4890 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_fused_attention_overrideable.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::_scaled_dot_product_fused_attention_overrideable(Tensor query, Tensor key, Tensor value, Tensor? attn_bias=None, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False, *, float? scale=None) -> (Tensor output, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, Tensor philox_seed, Tensor philox_offset, Tensor debug_attn_mask) +inline ::std::tuple _scaled_dot_product_fused_attention_overrideable(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias={}, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt) { + return at::_ops::_scaled_dot_product_fused_attention_overrideable::call(query, key, value, attn_bias, dropout_p, is_causal, return_debug_mask, scale); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_mm_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..789b89bd65f665b1f51ba73d319449be4e4ecf23 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_mm_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 _scaled_mm(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scale_a, const at::Tensor & scale_b, const ::std::optional & bias={}, const ::std::optional & scale_result={}, ::std::optional out_dtype=::std::nullopt, bool use_fast_accum=false); +TORCH_API at::Tensor & _scaled_mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scale_a, const at::Tensor & scale_b, const ::std::optional & bias={}, const ::std::optional & scale_result={}, ::std::optional out_dtype=::std::nullopt, bool use_fast_accum=false); +TORCH_API at::Tensor & _scaled_mm_outf(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scale_a, const at::Tensor & scale_b, const ::std::optional & bias, const ::std::optional & scale_result, ::std::optional out_dtype, bool use_fast_accum, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_forward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..e9caff9795a949267f7e8ee8f63eff36bf8bab1c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_slow_conv2d_forward.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::_slow_conv2d_forward.output(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) output) -> Tensor(a!) +inline at::Tensor & _slow_conv2d_forward_out(at::Tensor & output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::_slow_conv2d_forward_output::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output); +} +namespace symint { + template >> + at::Tensor & _slow_conv2d_forward_out(at::Tensor & output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::_slow_conv2d_forward_output::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output); + } +} + +// aten::_slow_conv2d_forward.output(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) output) -> Tensor(a!) +inline at::Tensor & _slow_conv2d_forward_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & output) { + return at::_ops::_slow_conv2d_forward_output::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output); +} +namespace symint { + template >> + at::Tensor & _slow_conv2d_forward_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & output) { + return at::_ops::_slow_conv2d_forward_output::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), output); + } +} + +// aten::_slow_conv2d_forward.output(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) output) -> Tensor(a!) +inline at::Tensor & _slow_conv2d_forward_symint_out(at::Tensor & output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding) { + return at::_ops::_slow_conv2d_forward_output::call(self, weight, kernel_size, bias, stride, padding, output); +} +namespace symint { + template >> + at::Tensor & _slow_conv2d_forward_out(at::Tensor & output, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding) { + return at::_ops::_slow_conv2d_forward_output::call(self, weight, kernel_size, bias, stride, padding, output); + } +} + +// aten::_slow_conv2d_forward.output(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, *, Tensor(a!) output) -> Tensor(a!) +inline at::Tensor & _slow_conv2d_forward_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & output) { + return at::_ops::_slow_conv2d_forward_output::call(self, weight, kernel_size, bias, stride, padding, output); +} +namespace symint { + template >> + at::Tensor & _slow_conv2d_forward_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & output) { + return at::_ops::_slow_conv2d_forward_output::call(self, weight, kernel_size, bias, stride, padding, output); + } +} + +// aten::_slow_conv2d_forward(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding) -> Tensor +inline at::Tensor _slow_conv2d_forward(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::_slow_conv2d_forward::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding)); +} +namespace symint { + template >> + at::Tensor _slow_conv2d_forward(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding) { + return at::_ops::_slow_conv2d_forward::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding)); + } +} + +// aten::_slow_conv2d_forward(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding) -> Tensor +inline at::Tensor _slow_conv2d_forward_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding) { + return at::_ops::_slow_conv2d_forward::call(self, weight, kernel_size, bias, stride, padding); +} +namespace symint { + template >> + at::Tensor _slow_conv2d_forward(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding) { + return at::_ops::_slow_conv2d_forward::call(self, weight, kernel_size, bias, stride, padding); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f33ec99bd02c7ecbebee8a4df0e291bf2b51004a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_backward_data_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 _softmax_backward_data { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_softmax_backward_data"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_softmax_backward_data(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype); +}; + +struct TORCH_API _softmax_backward_data_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_softmax_backward_data"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, ScalarType input_dtype, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, at::Tensor & grad_input); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsc_tensor_unsafe_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsc_tensor_unsafe_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..98da0bbcf379d819f884e34ef483207ef8613eda --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_bsc_tensor_unsafe_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 _sparse_bsc_tensor_unsafe(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _sparse_bsc_tensor_unsafe(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims.h new file mode 100644 index 0000000000000000000000000000000000000000..f7de83b215e2c7b595fe45cf68d92aa22333d95c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims.h @@ -0,0 +1,43 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_coo_tensor_with_dims(int sparse_dim, int dense_dim, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor _sparse_coo_tensor_with_dims(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, at::TensorOptions options) { + return at::_ops::_sparse_coo_tensor_with_dims::call(sparse_dim, dense_dim, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::_sparse_coo_tensor_with_dims(int sparse_dim, int dense_dim, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor _sparse_coo_tensor_with_dims(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_sparse_coo_tensor_with_dims::call(sparse_dim, dense_dim, size, dtype, layout, device, pin_memory); +} + +// aten::_sparse_coo_tensor_with_dims.out(int sparse_dim, int dense_dim, int[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_coo_tensor_with_dims_out(at::Tensor & out, int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size) { + return at::_ops::_sparse_coo_tensor_with_dims_out::call(sparse_dim, dense_dim, size, out); +} +// aten::_sparse_coo_tensor_with_dims.out(int sparse_dim, int dense_dim, int[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_coo_tensor_with_dims_outf(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::_sparse_coo_tensor_with_dims_out::call(sparse_dim, dense_dim, size, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f09b8bd061c72b47b896e289c75cd9fc57f17d4c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors_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 & _sparse_coo_tensor_with_dims_and_tensors_out_symint(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional is_coalesced, at::Tensor & out); +TORCH_API at::Tensor new_with_dims_and_tensor_sparse_symint(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional is_coalesced=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..23c2ea8335ed4834e8afc7bd6e7d14784951258f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_csc_tensor_unsafe { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_csc_tensor_unsafe"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_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"; + static at::Tensor call(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_sum_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_sum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9b537b525f75b9e908b1142532567e1ea6f42652 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_csr_sum_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_csr_sum_dim_dtype { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_csr_sum"; + static constexpr const char* overload_name = "dim_dtype"; + static constexpr const char* schema_str = "_sparse_csr_sum.dim_dtype(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, ::std::optional dtype); +}; + +struct TORCH_API _sparse_csr_sum_dim_dtype_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_csr_sum"; + static constexpr const char* overload_name = "dim_dtype_out"; + static constexpr const char* schema_str = "_sparse_csr_sum.dim_dtype_out(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mask_projection_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mask_projection_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3d4a57750d06a2c4e39c3190a56621ad48401ff7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mask_projection_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 & _sparse_mask_projection_out(const at::Tensor & self, const at::Tensor & mask, bool accumulate_matches, at::Tensor & out); +TORCH_API at::Tensor sparse_mask_projection(const at::Tensor & self, const at::Tensor & mask, bool accumulate_matches=false); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2295eb9344e1c0a6c1cfdea5ed1a673adb486e4a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_apply_dense_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_semi_structured_apply_dense { + 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 const char* name = "aten::_sparse_semi_structured_apply_dense"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_semi_structured_apply_dense(Tensor input, Tensor thread_masks) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & thread_masks); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & thread_masks); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile.h new file mode 100644 index 0000000000000000000000000000000000000000..ba331ca7fe3f35181825d75fd3b2fed31ff63659 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_tile.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::_sparse_semi_structured_tile(Tensor input, str algorithm="", bool use_cutlass=True) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _sparse_semi_structured_tile(const at::Tensor & input, c10::string_view algorithm="", bool use_cutlass=true) { + return at::_ops::_sparse_semi_structured_tile::call(input, algorithm, use_cutlass); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_standard_gamma_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_standard_gamma_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9738b8cef0b330c3bcf11e59ae8159d2a6d25942 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_standard_gamma_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 _standard_gamma(const at::Tensor & self, ::std::optional generator=::std::nullopt); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_standard_gamma_grad_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_standard_gamma_grad_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1283483fa2b049407686c413d091844c0581cfd3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_standard_gamma_grad_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _standard_gamma_grad(const at::Tensor & self, const at::Tensor & output); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_test_functorch_fallback_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_test_functorch_fallback_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cf48c5a2923e68114c1ac96801370f75eaaba58e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_test_functorch_fallback_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 & _test_functorch_fallback_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & _test_functorch_fallback_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_gru_cell_backward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_gru_cell_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..93db2464aa078700dc640d3b6cb11be4fe35cd61 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_differentiable_gru_cell_backward.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::_thnn_differentiable_gru_cell_backward(Tensor grad_hy, Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias, Tensor? hidden_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _thnn_differentiable_gru_cell_backward(const at::Tensor & grad_hy, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const ::std::optional & input_bias, const ::std::optional & hidden_bias) { + return at::_ops::_thnn_differentiable_gru_cell_backward::call(grad_hy, input_gates, hidden_gates, hx, input_bias, hidden_bias); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e06b2dc1c25f8656c0ef3c69188493c613b65a34 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _thnn_fused_lstm_cell(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & cx, const ::std::optional & input_bias={}, const ::std::optional & hidden_bias={}); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1b600d5838db8608a6caaef3a2aced8d044481ed --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_lstm_cell_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _thnn_fused_lstm_cell_out(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & cx, const ::std::optional & input_bias, const ::std::optional & hidden_bias, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple _thnn_fused_lstm_cell_cuda(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & cx, const ::std::optional & input_bias={}, const ::std::optional & hidden_bias={}); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csr_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csr_native.h new file mode 100644 index 0000000000000000000000000000000000000000..edc8e63b151c021fa86bfba046abe0113fd7c56b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csr_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _to_sparse_csr_out(const at::Tensor & self, ::std::optional dense_dim, at::Tensor & out); +TORCH_API at::Tensor dense_to_sparse_csr(const at::Tensor & self, ::std::optional dense_dim=::std::nullopt); +TORCH_API at::Tensor coo_to_sparse_csr(const at::Tensor & self, ::std::optional dense_dim=::std::nullopt); +TORCH_API at::Tensor sparse_compressed_to_sparse_csr(const at::Tensor & self, ::std::optional dense_dim=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c017c14b244d3329f0e8c722013a4631d9da9d51 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_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 _to_sparse_semi_structured(const at::Tensor & dense); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_transform_bias_rescale_qkv_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_transform_bias_rescale_qkv_native.h new file mode 100644 index 0000000000000000000000000000000000000000..02a1859489c7efddfe672dab79cdcf62e9ecc37e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_transform_bias_rescale_qkv_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _transform_bias_rescale_qkv_out(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple transform_bias_rescale_qkv_cpu(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads); +TORCH_API ::std::tuple transform_bias_rescale_qkv_cuda(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e65a3fecd87733d2c90986156818616c5365e517 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_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 _unsafe_index(const at::Tensor & self, const c10::List<::std::optional> & indices); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_put_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_put_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fbbed79cb0549b9bac57e3650cd846ed11f6f1d8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_index_put_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 _unsafe_index_put { + using schema = at::Tensor (const at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_unsafe_index_put"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_unsafe_index_put(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_masked_index_put_accumulate_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_masked_index_put_accumulate_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..66c3e4bbda462e44652862a9bc5b176ac1a59fdb --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_unsafe_masked_index_put_accumulate_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor _unsafe_masked_index_put_accumulate(const at::Tensor & self, const at::Tensor & mask, const c10::List<::std::optional> & indices, const at::Tensor & values); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa.h new file mode 100644 index 0000000000000000000000000000000000000000..ff33d65b5ae7f0b1808c724a97df9c76de957551 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa.h @@ -0,0 +1,113 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor _upsample_bicubic2d_aa(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::_upsample_bicubic2d_aa_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors); +} +namespace symint { + template >> + at::Tensor _upsample_bicubic2d_aa(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::_upsample_bicubic2d_aa_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors); + } +} + +// aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor _upsample_bicubic2d_aa_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::_upsample_bicubic2d_aa_vec::call(input, output_size, align_corners, scale_factors); +} +namespace symint { + template >> + at::Tensor _upsample_bicubic2d_aa(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::_upsample_bicubic2d_aa_vec::call(input, output_size, align_corners, scale_factors); + } +} + +// aten::_upsample_bicubic2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_bicubic2d_aa_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & _upsample_bicubic2d_aa_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); + } +} + +// aten::_upsample_bicubic2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_bicubic2d_aa_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::_upsample_bicubic2d_aa_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & _upsample_bicubic2d_aa_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::_upsample_bicubic2d_aa_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); + } +} + +// aten::_upsample_bicubic2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_bicubic2d_aa_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_out::call(self, output_size, align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & _upsample_bicubic2d_aa_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_out::call(self, output_size, align_corners, scales_h, scales_w, out); + } +} + +// aten::_upsample_bicubic2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_bicubic2d_aa_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::_upsample_bicubic2d_aa_out::call(self, output_size, align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & _upsample_bicubic2d_aa_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out) { + return at::_ops::_upsample_bicubic2d_aa_out::call(self, output_size, align_corners, scales_h, scales_w, out); + } +} + +// aten::_upsample_bicubic2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bicubic2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor _upsample_bicubic2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w); + } +} + +// aten::_upsample_bicubic2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bicubic2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa::call(self, output_size, align_corners, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor _upsample_bicubic2d_aa(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa::call(self, output_size, align_corners, scales_h, scales_w); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ceca4601949c92e60da7383a6988d30c6b061050 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured__upsample_bicubic2d_aa_backward_out_cpu : public at::meta::structured__upsample_bicubic2d_aa_backward { +void impl(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & grad_input); +}; +struct TORCH_API structured__upsample_bicubic2d_aa_backward_out_cuda : public at::meta::structured__upsample_bicubic2d_aa_backward { +void impl(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..029dd476e0ce01d5e2c91e5b8711f4033df48ec0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_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 _upsample_bicubic2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_bicubic2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d.h new file mode 100644 index 0000000000000000000000000000000000000000..e44c74a58fef930d265fe3b426a3cf4c5b51fb40 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d.h @@ -0,0 +1,113 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor +inline at::Tensor _upsample_nearest_exact1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::_upsample_nearest_exact1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors); +} +namespace symint { + template >> + at::Tensor _upsample_nearest_exact1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::_upsample_nearest_exact1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors); + } +} + +// aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor +inline at::Tensor _upsample_nearest_exact1d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::_upsample_nearest_exact1d_vec::call(input, output_size, scale_factors); +} +namespace symint { + template >> + at::Tensor _upsample_nearest_exact1d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors) { + return at::_ops::_upsample_nearest_exact1d_vec::call(input, output_size, scale_factors); + } +} + +// aten::_upsample_nearest_exact1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); +} +namespace symint { + template >> + at::Tensor & _upsample_nearest_exact1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); + } +} + +// aten::_upsample_nearest_exact1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); +} +namespace symint { + template >> + at::Tensor & _upsample_nearest_exact1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out); + } +} + +// aten::_upsample_nearest_exact1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, output_size, scales, out); +} +namespace symint { + template >> + at::Tensor & _upsample_nearest_exact1d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, output_size, scales, out); + } +} + +// aten::_upsample_nearest_exact1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _upsample_nearest_exact1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, output_size, scales, out); +} +namespace symint { + template >> + at::Tensor & _upsample_nearest_exact1d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales, at::Tensor & out) { + return at::_ops::_upsample_nearest_exact1d_out::call(self, output_size, scales, out); + } +} + +// aten::_upsample_nearest_exact1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor +inline at::Tensor _upsample_nearest_exact1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d::call(self, c10::fromIntArrayRefSlow(output_size), scales); +} +namespace symint { + template >> + at::Tensor _upsample_nearest_exact1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d::call(self, c10::fromIntArrayRefSlow(output_size), scales); + } +} + +// aten::_upsample_nearest_exact1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor +inline at::Tensor _upsample_nearest_exact1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d::call(self, output_size, scales); +} +namespace symint { + template >> + at::Tensor _upsample_nearest_exact1d(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales=::std::nullopt) { + return at::_ops::_upsample_nearest_exact1d::call(self, output_size, scales); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..21a38844d40c015fac3cb2e53060f77d00f66be1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_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 _upsample_nearest_exact2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..66c9fd664709ed37fbe2f5ff8a5ebba06f4ddb0b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_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_nearest_exact3d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact3d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & _upsample_nearest_exact3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_ctc_loss_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_ctc_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2f5b2cd33f4e455a9735486bfc0c9e8cbb2b7d47 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_use_cudnn_ctc_loss_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 bool _use_cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank); +TORCH_API bool _use_cudnn_ctc_loss_tensor(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_compressed_tensor_args_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_compressed_tensor_args_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8aba56b3590d7ea56a676389fc8a50d3f92f4f29 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_compressed_tensor_args_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 _validate_sparse_compressed_tensor_args { + using schema = void (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::Layout); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_validate_sparse_compressed_tensor_args"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_validate_sparse_compressed_tensor_args(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, Layout layout) -> ()"; + static void call(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::Layout layout); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::Layout layout); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_for_cpu_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_for_cpu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e0fce324c8701cc2c1355003534a46ca3108c8ad --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_for_cpu_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 _weight_int4pack_mm_for_cpu { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_weight_int4pack_mm_for_cpu"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_weight_int4pack_mm_for_cpu(Tensor self, Tensor mat2, int qGroupSize, Tensor qScaleAndZeros) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int8pack_mm_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int8pack_mm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4b33b7ffa1169b936abadb08e051c9911128cab --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int8pack_mm_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 _weight_int8pack_mm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_weight_int8pack_mm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_weight_int8pack_mm(Tensor self, Tensor mat2, Tensor scales) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scales); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scales); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/abs_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/abs_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..585d0e3ba84cfdf4f0e946b3befd3a96f213c41e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/abs_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API abs { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::abs"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "abs(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 abs_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::abs_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "abs_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API abs_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 const char* name = "aten::abs"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "abs.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/lib/python3.12/site-packages/torch/include/ATen/ops/acos_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/acos_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6c4a4e7c645a899bd9cc9781e05e86746312cb3e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/acos_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_acos_out : public at::meta::structured_acos { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/acos_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/acos_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f03dd28c2552b62a5dc4fec8033161a318e249f7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/acos_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API acos { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::acos"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "acos(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 acos_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::acos_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "acos_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API acos_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 const char* name = "aten::acos"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "acos.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/lib/python3.12/site-packages/torch/include/ATen/ops/acosh_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/acosh_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ae4983cc9b3e8d29b47009639e4b2e99d9278333 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/acosh_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor acosh(const at::Tensor & self); +TORCH_API at::Tensor & acosh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & acosh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & acosh_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d.h new file mode 100644 index 0000000000000000000000000000000000000000..2b22eb9720f1f4389efcf7c4cfba72df11bcbd4b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d.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::adaptive_avg_pool1d(Tensor self, int[1] output_size) -> Tensor +inline at::Tensor adaptive_avg_pool1d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_avg_pool1d::call(self, output_size); +} + +// aten::adaptive_avg_pool1d.out(Tensor self, int[1] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & adaptive_avg_pool1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_avg_pool1d_out::call(self, output_size, out); +} +// aten::adaptive_avg_pool1d.out(Tensor self, int[1] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & adaptive_avg_pool1d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::adaptive_avg_pool1d_out::call(self, output_size, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool2d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cc8471af844df6630716da05485aa872d457caef --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool2d_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor adaptive_avg_pool2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size); +TORCH_API at::Tensor & adaptive_avg_pool2d_out_cpu(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); +TORCH_API at::Tensor & adaptive_avg_pool2d_out_cuda(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); +TORCH_API at::Tensor & mkldnn_adaptive_avg_pool2d_out_stub(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d_backward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0bdc3b57dbdc573db11947d8c9292e26fd3e3dd7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_avg_pool3d_backward_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & adaptive_avg_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & adaptive_avg_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..008c56ea2268378e30fe051a11a8c57308ef3a24 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API addcmul_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addcmul"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "addcmul.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); +}; + +struct TORCH_API addcmul { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addcmul"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "addcmul(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); +}; + +struct TORCH_API addcmul_ { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addcmul_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "addcmul_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5e4d348d2233fe80bec99157752079ad3f203168 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor addmm(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addmm_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & addmm_(at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/affine_grid_generator_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/affine_grid_generator_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..86e2de15198b2af040675ff6a81569c5d17d7c9e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/affine_grid_generator_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor affine_grid_generator(const at::Tensor & theta, at::IntArrayRef size, bool align_corners); +TORCH_API at::Tensor affine_grid_generator_symint(const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners); +TORCH_API at::Tensor & affine_grid_generator_out(at::Tensor & out, const at::Tensor & theta, at::IntArrayRef size, bool align_corners); +TORCH_API at::Tensor & affine_grid_generator_outf(const at::Tensor & theta, at::IntArrayRef size, bool align_corners, at::Tensor & out); +TORCH_API at::Tensor & affine_grid_generator_symint_out(at::Tensor & out, const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners); +TORCH_API at::Tensor & affine_grid_generator_symint_outf(const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/align_as_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/align_as_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d7bfe849a6cb9a92f8646a7e197c0ec5e3eaf05f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/align_as_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API align_as { + 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 const char* name = "aten::align_as"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "align_as(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/allclose.h b/lib/python3.12/site-packages/torch/include/ATen/ops/allclose.h new file mode 100644 index 0000000000000000000000000000000000000000..9695a909e47648782fae237a4fb4ebda3efc62c3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/allclose.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::allclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> bool +inline bool allclose(const at::Tensor & self, const at::Tensor & other, double rtol=1e-05, double atol=1e-08, bool equal_nan=false) { + return at::_ops::allclose::call(self, other, rtol, atol, equal_nan); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/allclose_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/allclose_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cdf19a48de854e67197387681749d9121174e44c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/allclose_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API bool allclose(const at::Tensor & self, const at::Tensor & other, double rtol=1e-05, double atol=1e-08, bool equal_nan=false); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/amin_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/amin_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5ac7db91e25df7ee4eae5d59a12f50249715d4f9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/amin_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 amin(const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/amin_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/amin_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f0856cc60036408d643e3c7184d4c179e896368c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/amin_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 amin { + 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 const char* name = "aten::amin"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "amin(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 amin_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 const char* name = "aten::amin"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "amin.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/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7758a4494e03179b03282bc993706fa892649b07 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/aminmax_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_aminmax_out : public at::meta::structured_aminmax { +void impl(const at::Tensor & self, ::std::optional dim, bool keepdim, const at::Tensor & min, const at::Tensor & max); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/and.h b/lib/python3.12/site-packages/torch/include/ATen/ops/and.h new file mode 100644 index 0000000000000000000000000000000000000000..587ecb8b07038883a108d64bd5a503d66d9654ac --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/and.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::__and__.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor __and__(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::__and___Scalar::call(self, other); +} + +// aten::__and__.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor __and__(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::__and___Tensor::call(self, other); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/any_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/any_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d1c89b9aa8374aeb2c8d6ddaba291c8493ab26ec --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/any_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 any(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API at::Tensor & any_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/argmin_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/argmin_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c334bac16d947884237e3cc8d3bdbd9a7c21dc00 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/argmin_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 argmin { + using schema = at::Tensor (const at::Tensor &, ::std::optional, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::argmin"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "argmin(Tensor self, int? dim=None, bool keepdim=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dim, bool keepdim); +}; + +struct TORCH_API argmin_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::argmin"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "argmin.out(Tensor self, int? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional dim, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dim, bool keepdim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/argsort.h b/lib/python3.12/site-packages/torch/include/ATen/ops/argsort.h new file mode 100644 index 0000000000000000000000000000000000000000..4344b870a8c3030b9b0b18868ced07005bd9958f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/argsort.h @@ -0,0 +1,49 @@ +#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::argsort(Tensor self, int dim=-1, bool descending=False) -> Tensor +inline at::Tensor argsort(const at::Tensor & self, int64_t dim=-1, bool descending=false) { + return at::_ops::argsort::call(self, dim, descending); +} + +// aten::argsort.stable(Tensor self, *, bool stable, int dim=-1, bool descending=False) -> Tensor +inline at::Tensor argsort(const at::Tensor & self, bool stable, int64_t dim=-1, bool descending=false) { + return at::_ops::argsort_stable::call(self, stable, dim, descending); +} + +// aten::argsort.stable_out(Tensor self, *, bool stable, int dim=-1, bool descending=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & argsort_out(at::Tensor & out, const at::Tensor & self, bool stable, int64_t dim=-1, bool descending=false) { + return at::_ops::argsort_stable_out::call(self, stable, dim, descending, out); +} +// aten::argsort.stable_out(Tensor self, *, bool stable, int dim=-1, bool descending=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & argsort_outf(const at::Tensor & self, bool stable, int64_t dim, bool descending, at::Tensor & out) { + return at::_ops::argsort_stable_out::call(self, stable, dim, descending, out); +} + +// aten::argsort.dimname(Tensor self, Dimname dim, bool descending=False) -> Tensor +inline at::Tensor argsort(const at::Tensor & self, at::Dimname dim, bool descending=false) { + return at::_ops::argsort_dimname::call(self, dim, descending); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/argsort_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/argsort_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d790738426620029e734bd39533a7b7392d335c1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/argsort_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor argsort(const at::Tensor & self, int64_t dim=-1, bool descending=false); +TORCH_API at::Tensor argsort(const at::Tensor & self, bool stable, int64_t dim=-1, bool descending=false); +TORCH_API at::Tensor & argsort_out(const at::Tensor & self, bool stable, int64_t dim, bool descending, at::Tensor & out); +TORCH_API at::Tensor argsort(const at::Tensor & self, at::Dimname dim, bool descending=false); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/argwhere_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/argwhere_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..447c527eea89dd3baa1df83ea48343bca141deb6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/argwhere_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 argwhere { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::argwhere"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "argwhere(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_scatter_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_scatter_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc0962f4b8c45771696c1b5854b85778575781d7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided_scatter_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & as_strided_scatter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt); +TORCH_API at::Tensor & as_strided_scatter_outf(const at::Tensor & self, const at::Tensor & src, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset, at::Tensor & out); +TORCH_API at::Tensor & as_strided_scatter_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt); +TORCH_API at::Tensor & as_strided_scatter_symint_outf(const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/asinh.h b/lib/python3.12/site-packages/torch/include/ATen/ops/asinh.h new file mode 100644 index 0000000000000000000000000000000000000000..1637cb1225bda457398c42c452ba32bb4f045815 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/asinh.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::asinh(Tensor self) -> Tensor +inline at::Tensor asinh(const at::Tensor & self) { + return at::_ops::asinh::call(self); +} + +// aten::asinh_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & asinh_(at::Tensor & self) { + return at::_ops::asinh_::call(self); +} + +// aten::asinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & asinh_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::asinh_out::call(self, out); +} +// aten::asinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & asinh_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::asinh_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/asinh_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/asinh_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bd96863997d2b24756dbb309809e0d503347229a --- /dev/null +++ b/lib/python3.12/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/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool1d_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool1d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fef87a340e63567458dd628a3eca338d116dde96 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool1d_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 & avg_pool1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true); +TORCH_API at::Tensor & avg_pool1d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5ff0f7e72506b360ce1cce7f26ba57def24f063a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_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 avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +TORCH_API at::Tensor & avg_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..34c323feaef7a59e4c658a6ab5b785da42836886 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_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 avg_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, ::std::optional divisor_override=::std::nullopt); +TORCH_API at::Tensor & avg_pool2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, ::std::optional divisor_override=::std::nullopt); +TORCH_API at::Tensor & avg_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..24dbeb99a18eb154937a86933d48a6d2fcddee39 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_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_avg_pool3d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bartlett_window.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bartlett_window.h new file mode 100644 index 0000000000000000000000000000000000000000..66431efb4f61201b9bcba6d950b6f479c97761ec --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bartlett_window.h @@ -0,0 +1,61 @@ +#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::bartlett_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor bartlett_window(int64_t window_length, at::TensorOptions options={}) { + return at::_ops::bartlett_window::call(window_length, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::bartlett_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor bartlett_window(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::bartlett_window::call(window_length, dtype, layout, device, pin_memory); +} + +// aten::bartlett_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor bartlett_window(int64_t window_length, bool periodic, at::TensorOptions options={}) { + return at::_ops::bartlett_window_periodic::call(window_length, periodic, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::bartlett_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor bartlett_window(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::bartlett_window_periodic::call(window_length, periodic, dtype, layout, device, pin_memory); +} + +// aten::bartlett_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bartlett_window_out(at::Tensor & out, int64_t window_length) { + return at::_ops::bartlett_window_out::call(window_length, out); +} +// aten::bartlett_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bartlett_window_outf(int64_t window_length, at::Tensor & out) { + return at::_ops::bartlett_window_out::call(window_length, out); +} + +// aten::bartlett_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bartlett_window_out(at::Tensor & out, int64_t window_length, bool periodic) { + return at::_ops::bartlett_window_periodic_out::call(window_length, periodic, out); +} +// aten::bartlett_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bartlett_window_outf(int64_t window_length, bool periodic, at::Tensor & out) { + return at::_ops::bartlett_window_periodic_out::call(window_length, periodic, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce.h b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce.h new file mode 100644 index 0000000000000000000000000000000000000000..6492e9166b6842fd0ba8b52195004986938ce1af --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce.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::batch_norm_backward_reduce(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, bool input_g, bool weight_g, bool bias_g) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple batch_norm_backward_reduce(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & weight, bool input_g, bool weight_g, bool bias_g) { + return at::_ops::batch_norm_backward_reduce::call(grad_out, input, mean, invstd, weight, input_g, weight_g, bias_g); +} + +// aten::batch_norm_backward_reduce.out(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, bool input_g, bool weight_g, bool bias_g, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple batch_norm_backward_reduce_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & weight, bool input_g, bool weight_g, bool bias_g) { + return at::_ops::batch_norm_backward_reduce_out::call(grad_out, input, mean, invstd, weight, input_g, weight_g, bias_g, out0, out1, out2, out3); +} +// aten::batch_norm_backward_reduce.out(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, bool input_g, bool weight_g, bool bias_g, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple batch_norm_backward_reduce_outf(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & weight, bool input_g, bool weight_g, bool bias_g, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { + return at::_ops::batch_norm_backward_reduce_out::call(grad_out, input, mean, invstd, weight, input_g, weight_g, bias_g, out0, out1, out2, out3); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8be75742af8729e30dcce934816318f5047ac93d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API batch_norm_gather_stats { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, double, double, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::batch_norm_gather_stats"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "batch_norm_gather_stats(Tensor input, Tensor mean, Tensor invstd, Tensor? running_mean, Tensor? running_var, float momentum, float eps, int count) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, int64_t count); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, int64_t count); +}; + +struct TORCH_API batch_norm_gather_stats_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, double, double, int64_t, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::batch_norm_gather_stats"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "batch_norm_gather_stats.out(Tensor input, Tensor mean, Tensor invstd, Tensor? running_mean, Tensor? running_var, float momentum, float eps, int count, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, int64_t count, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, double eps, int64_t count, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_update_stats_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_update_stats_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d45b54b8d4e5dc7cdcf2bac3a585b1d0f3b2a94a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_update_stats_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple batch_norm_update_stats_out(const at::Tensor & input, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple batch_norm_update_stats_cpu(const at::Tensor & input, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum); +TORCH_API ::std::tuple batch_norm_update_stats_cuda(const at::Tensor & input, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bilinear_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bilinear_native.h new file mode 100644 index 0000000000000000000000000000000000000000..62f837f48fc89019ac6d5760c4e0c103258a1417 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bilinear_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 bilinear(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & weight, const ::std::optional & bias={}); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_left_shift_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_left_shift_native.h new file mode 100644 index 0000000000000000000000000000000000000000..953e27cb5164e6abd721475ed629108b4fa9ade7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_left_shift_native.h @@ -0,0 +1,28 @@ +#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_bitwise_left_shift_out : public at::meta::structured_bitwise_left_shift_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +TORCH_API at::Tensor bitwise_left_shift(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & bitwise_left_shift_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_left_shift_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor bitwise_left_shift(const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_left_shift_Scalar_Tensor_out(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..16af18f329b0f0aee61f8992b703171dc0a8c126 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_right_shift_compositeexplicitautograd_dispatch.h @@ -0,0 +1,29 @@ +#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 bitwise_right_shift(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_right_shift_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor bitwise_right_shift(const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_right_shift_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_xor_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_xor_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a3b2cd3cae43c69fcc3d4abe8d2f92d09c20d9d0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_xor_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor bitwise_xor(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_xor_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_xor_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_xor_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cdist_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cdist_native.h new file mode 100644 index 0000000000000000000000000000000000000000..eb7f4ecb6e3345adec8545468bf8fc75683c0996 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cdist_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 cdist(const at::Tensor & x1, const at::Tensor & x2, double p=2, ::std::optional compute_mode=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4d60cf31c53f6c0f73c57ff2bda9ed456b0848f8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_clamp_max_out : public at::meta::structured_clamp_max { +void impl(const at::Tensor & self, const at::Scalar & max, const at::Tensor & out); +}; +struct TORCH_API structured_clamp_max_Tensor_out : public at::meta::structured_clamp_max_Tensor { +void impl(const at::Tensor & self, const at::Tensor & max, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_min_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_min_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a0bae20593e0afbb49ed518858e5d393352e71ed --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_min_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API clamp_min { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_min"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "clamp_min(Tensor self, Scalar min) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & min); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & min); +}; + +struct TORCH_API clamp_min_Tensor { + 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 const char* name = "aten::clamp_min"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "clamp_min.Tensor(Tensor self, Tensor min) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & min); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & min); +}; + +struct TORCH_API clamp_min_ { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_min_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "clamp_min_(Tensor(a!) self, Scalar min) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & min); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & min); +}; + +struct TORCH_API clamp_min__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_min_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "clamp_min_.Tensor(Tensor(a!) self, Tensor min) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & min); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & min); +}; + +struct TORCH_API clamp_min_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clamp_min"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "clamp_min.out(Tensor self, Scalar min, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & min, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & min, at::Tensor & out); +}; + +struct TORCH_API clamp_min_Tensor_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 const char* name = "aten::clamp_min"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "clamp_min.Tensor_out(Tensor self, Tensor min, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & min, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & min, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/clip_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/clip_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b7fc1cea2f2b05eb1672ee6e53e8c96d684cb8fe --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/clip_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API clip { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clip"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "clip(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max); +}; + +struct TORCH_API clip_Tensor { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clip"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "clip.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max); +}; + +struct TORCH_API clip_ { + using schema = at::Tensor & (at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clip_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "clip_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const ::std::optional & min, const ::std::optional & max); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const ::std::optional & min, const ::std::optional & max); +}; + +struct TORCH_API clip__Tensor { + using schema = at::Tensor & (at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clip_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "clip_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const ::std::optional & min, const ::std::optional & max); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const ::std::optional & min, const ::std::optional & max); +}; + +struct TORCH_API clip_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clip"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "clip.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); +}; + +struct TORCH_API clip_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::clip"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "clip.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/conj_physical_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/conj_physical_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..da612acb00c1ea07c85ea50a95777908add07caf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/conj_physical_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & conj_physical_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & conj_physical_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/constant_pad_nd_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/constant_pad_nd_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1a899b97eafb74f3db4209afdf6bed12518fc01c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/constant_pad_nd_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 constant_pad_nd { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::constant_pad_nd"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value); +}; + +struct TORCH_API constant_pad_nd_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::constant_pad_nd"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/contiguous.h b/lib/python3.12/site-packages/torch/include/ATen/ops/contiguous.h new file mode 100644 index 0000000000000000000000000000000000000000..a341433f1fb93c2381925b7714ef70c9f6795c63 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/contiguous.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/conv_depthwise3d_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/conv_depthwise3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bd3efa5214cc1a408034cb87147a3f13aaee3d8c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/conv_depthwise3d_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 conv_depthwise3d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conv_depthwise3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "conv_depthwise3d(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias, SymInt[3] stride, SymInt[3] padding, SymInt[3] dilation) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation); +}; + +struct TORCH_API conv_depthwise3d_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conv_depthwise3d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "conv_depthwise3d.out(Tensor self, Tensor weight, SymInt[3] kernel_size, Tensor? bias, SymInt[3] stride, SymInt[3] padding, SymInt[3] dilation, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose3d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose3d.h new file mode 100644 index 0000000000000000000000000000000000000000..8142d3d3853e125f40f3fe7680967277899b429c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose3d.h @@ -0,0 +1,47 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::conv_transpose3d.input(Tensor input, Tensor weight, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, SymInt groups=1, SymInt[3] dilation=1) -> Tensor +inline at::Tensor conv_transpose3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, int64_t groups=1, at::IntArrayRef dilation=1) { + return at::_ops::conv_transpose3d_input::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), groups, c10::fromIntArrayRefSlow(dilation)); +} +namespace symint { + template >> + at::Tensor conv_transpose3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, int64_t groups=1, at::IntArrayRef dilation=1) { + return at::_ops::conv_transpose3d_input::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), groups, c10::fromIntArrayRefSlow(dilation)); + } +} + +// aten::conv_transpose3d.input(Tensor input, Tensor weight, Tensor? bias=None, SymInt[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, SymInt groups=1, SymInt[3] dilation=1) -> Tensor +inline at::Tensor conv_transpose3d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymInt groups=1, c10::SymIntArrayRef dilation=c10::SymInt(1)) { + return at::_ops::conv_transpose3d_input::call(input, weight, bias, stride, padding, output_padding, groups, dilation); +} +namespace symint { + template >> + at::Tensor conv_transpose3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymInt groups=1, c10::SymIntArrayRef dilation=c10::SymInt(1)) { + return at::_ops::conv_transpose3d_input::call(input, weight, bias, stride, padding, output_padding, groups, dilation); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..22162d211ab101ca8358940bff0e40b88dc4303d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor copysign(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & copysign_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & copysign_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & copysign_(at::Tensor & self, const at::Scalar & other); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b42e95594833fecf54993c55754f14eced414d26 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/copysign_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor copysign(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & copysign_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & copysign_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & copysign_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cross.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cross.h new file mode 100644 index 0000000000000000000000000000000000000000..186535074c19e8d1b4d2523a7cc00f9ea5b82461 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cross.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::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cross_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, ::std::optional dim=::std::nullopt) { + return at::_ops::cross_out::call(self, other, dim, out); +} +// aten::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cross_outf(const at::Tensor & self, const at::Tensor & other, ::std::optional dim, at::Tensor & out) { + return at::_ops::cross_out::call(self, other, dim, out); +} + +// aten::cross(Tensor self, Tensor other, int? dim=None) -> Tensor +inline at::Tensor cross(const at::Tensor & self, const at::Tensor & other, ::std::optional dim=::std::nullopt) { + return at::_ops::cross::call(self, other, dim); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cross_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cross_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..36720925fa38b01ba632243478d8080ce7d6f52b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cross_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 cross(const at::Tensor & self, const at::Tensor & other, ::std::optional dim=::std::nullopt); +TORCH_API at::Tensor & cross_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, ::std::optional dim=::std::nullopt); +TORCH_API at::Tensor & cross_outf(const at::Tensor & self, const at::Tensor & other, ::std::optional dim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_copy.h b/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..85ae31472d3ac6db041c2fdb5d12ecd2fee02a0d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::crow_indices_copy(Tensor self) -> Tensor +inline at::Tensor crow_indices_copy(const at::Tensor & self) { + return at::_ops::crow_indices_copy::call(self); +} + +// aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & crow_indices_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::crow_indices_copy_out::call(self, out); +} +// aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & crow_indices_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::crow_indices_copy_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/ctc_loss_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/ctc_loss_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6870f6a52f111f1135886c433e55c52c58450119 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/ctc_loss_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 ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, int64_t reduction=at::Reduction::Mean, bool zero_infinity=false); +TORCH_API at::Tensor ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, int64_t reduction=at::Reduction::Mean, bool zero_infinity=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_transpose.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_transpose.h new file mode 100644 index 0000000000000000000000000000000000000000..1761b624f15bca5d18468c8a296b3376f638aa2c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_transpose.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::cudnn_convolution_transpose(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor +inline at::Tensor cudnn_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_transpose::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32); +} +namespace symint { + template >> + at::Tensor cudnn_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_transpose::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32); + } +} + +// aten::cudnn_convolution_transpose(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor +inline at::Tensor cudnn_convolution_transpose_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_transpose::call(self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32); +} +namespace symint { + template >> + at::Tensor cudnn_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_transpose::call(self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32); + } +} + +// aten::cudnn_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32, out); +} +namespace symint { + template >> + at::Tensor & cudnn_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32, out); + } +} + +// aten::cudnn_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { + return at::_ops::cudnn_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32, out); +} +namespace symint { + template >> + at::Tensor & cudnn_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { + return at::_ops::cudnn_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32, out); + } +} + +// aten::cudnn_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_transpose_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); +} +namespace symint { + template >> + at::Tensor & cudnn_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); + } +} + +// aten::cudnn_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_transpose_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { + return at::_ops::cudnn_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); +} +namespace symint { + template >> + at::Tensor & cudnn_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { + return at::_ops::cudnn_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cummaxmin_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cummaxmin_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2bf7388e6b2a38cc5eaa0f7f734d5e4c7d156a0b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cummaxmin_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 cummaxmin_backward(const at::Tensor & grad, const at::Tensor & input, const at::Tensor & indices, int64_t dim); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cummin_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cummin_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0b522404cf7975c19a5f2cbdb1ff504a5dd83b43 --- /dev/null +++ b/lib/python3.12/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/lib/python3.12/site-packages/torch/include/ATen/ops/dequantize_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/dequantize_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..91d8e559c9d85862d9bb3343cebf53998ef619df --- /dev/null +++ b/lib/python3.12/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/lib/python3.12/site-packages/torch/include/ATen/ops/det.h b/lib/python3.12/site-packages/torch/include/ATen/ops/det.h new file mode 100644 index 0000000000000000000000000000000000000000..44a93668d22086cfb8a9dbd3f128b575f9be396c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/det.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::det(Tensor self) -> Tensor +inline at::Tensor det(const at::Tensor & self) { + return at::_ops::det::call(self); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3c9b97bad978cc8c91ec9cc5266fc6ab320e4b9b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_backward_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor diagonal_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); +TORCH_API at::Tensor & diagonal_backward_out_symint(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_copy_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..46489889de9e731e487078f8ea0742bc58d12a24 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & diagonal_copy_out(at::Tensor & out, const at::Tensor & self, int64_t offset=0, int64_t dim1=0, int64_t dim2=1); +TORCH_API at::Tensor & diagonal_copy_outf(const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_copy_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..25773cf8e5bc28df0e7f8e4bd19245597ae40a22 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_copy_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 & diagonal_copy_out(const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); +TORCH_API at::Tensor diagonal_copy(const at::Tensor & self, int64_t offset=0, int64_t dim1=0, int64_t dim2=1); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter_native.h new file mode 100644 index 0000000000000000000000000000000000000000..695380a10a49f0f1b7426068437649a8e91969c6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & diagonal_scatter_out(const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); +TORCH_API at::Tensor diagonal_scatter(const at::Tensor & self, const at::Tensor & src, int64_t offset=0, int64_t dim1=0, int64_t dim2=1); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..69688ec579735c80987e9001b6cd3037b7706358 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_scatter_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API diagonal_scatter { + using schema = at::Tensor (const 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 const char* name = "aten::diagonal_scatter"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "diagonal_scatter(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2); +}; + +struct TORCH_API diagonal_scatter_out { + using schema = at::Tensor & (const 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 const char* name = "aten::diagonal_scatter"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "diagonal_scatter.out(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/div_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/div_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..13db9d5ccb3f46763862684eb1fb43a1e2897896 --- /dev/null +++ b/lib/python3.12/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, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/div_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/div_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e4e34a5221d2ce9fd6450273996fbf396f853d78 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/div_ops.h @@ -0,0 +1,149 @@ +#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 div_Tensor { + 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 const char* name = "aten::div"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "div.Tensor(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 div__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "div_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API div_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 const char* name = "aten::div"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "div.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API div_Tensor_mode { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div"; + static constexpr const char* overload_name = "Tensor_mode"; + static constexpr const char* schema_str = "div.Tensor_mode(Tensor self, Tensor other, *, str? rounding_mode) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +}; + +struct TORCH_API div__Tensor_mode { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div_"; + static constexpr const char* overload_name = "Tensor_mode"; + static constexpr const char* schema_str = "div_.Tensor_mode(Tensor(a!) self, Tensor other, *, str? rounding_mode) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +}; + +struct TORCH_API div_out_mode { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div"; + static constexpr const char* overload_name = "out_mode"; + static constexpr const char* schema_str = "div.out_mode(Tensor self, Tensor other, *, str? rounding_mode, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out); +}; + +struct TORCH_API div_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "div.Scalar(Tensor self, Scalar other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API div__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "div_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API div_Scalar_mode { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div"; + static constexpr const char* overload_name = "Scalar_mode"; + static constexpr const char* schema_str = "div.Scalar_mode(Tensor self, Scalar other, *, str? rounding_mode) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); +}; + +struct TORCH_API div__Scalar_mode { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div_"; + static constexpr const char* overload_name = "Scalar_mode"; + static constexpr const char* schema_str = "div_.Scalar_mode(Tensor(a!) self, Scalar other, *, str? rounding_mode) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); +}; + +struct TORCH_API div_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "div.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +struct TORCH_API div_Scalar_mode_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::div"; + static constexpr const char* overload_name = "Scalar_mode_out"; + static constexpr const char* schema_str = "div.Scalar_mode_out(Tensor self, Scalar other, *, str? rounding_mode, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/divide.h b/lib/python3.12/site-packages/torch/include/ATen/ops/divide.h new file mode 100644 index 0000000000000000000000000000000000000000..964479e4f6a875f006a9ba062eb1b42ebb5d4851 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/divide.h @@ -0,0 +1,63 @@ +#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::divide.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor divide(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::divide_Tensor::call(self, other); +} + +// aten::divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::divide_out::call(self, other, out); +} +// aten::divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::divide_out::call(self, other, out); +} + +// aten::divide.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor divide(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::divide_Scalar::call(self, other); +} + +// aten::divide.Tensor_mode(Tensor self, Tensor other, *, str? rounding_mode) -> Tensor +inline at::Tensor divide(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode) { + return at::_ops::divide_Tensor_mode::call(self, other, rounding_mode); +} + +// aten::divide.out_mode(Tensor self, Tensor other, *, str? rounding_mode, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode) { + return at::_ops::divide_out_mode::call(self, other, rounding_mode, out); +} +// aten::divide.out_mode(Tensor self, Tensor other, *, str? rounding_mode, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & divide_outf(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out) { + return at::_ops::divide_out_mode::call(self, other, rounding_mode, out); +} + +// aten::divide.Scalar_mode(Tensor self, Scalar other, *, str? rounding_mode) -> Tensor +inline at::Tensor divide(const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode) { + return at::_ops::divide_Scalar_mode::call(self, other, rounding_mode); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/dropout.h b/lib/python3.12/site-packages/torch/include/ATen/ops/dropout.h new file mode 100644 index 0000000000000000000000000000000000000000..aa535fa9e3e77fc1f5d3b657d70d1bf89ba6a16c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/dropout.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::dropout(Tensor input, float p, bool train) -> Tensor +inline at::Tensor dropout(const at::Tensor & input, double p, bool train) { + return at::_ops::dropout::call(input, p, train); +} + +// aten::dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) +inline at::Tensor & dropout_(at::Tensor & self, double p, bool train) { + return at::_ops::dropout_::call(self, p, train); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/dstack_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/dstack_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2e5f4cedf9c1a38334a21d6740503fd0372476a8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/dstack_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 dstack(at::TensorList tensors); +TORCH_API at::Tensor & dstack_out(at::Tensor & out, at::TensorList tensors); +TORCH_API at::Tensor & dstack_outf(at::TensorList tensors, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_bag_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_bag_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2ea5b25febb839c271efbf93be21431be2c53051 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_bag_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false); +TORCH_API ::std::tuple embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, ::std::optional padding_idx); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_dense_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_dense_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..874bfda1d3eee42c0116991fabe729013151ab8b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_dense_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 embedding_dense_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymInt, c10::SymInt, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::embedding_dense_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq); +}; + +struct TORCH_API embedding_dense_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymInt, c10::SymInt, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::embedding_dense_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7af0ff4477aa3ae9e08d0b200115fa6217872ee7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/embedding_renorm_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & embedding_renorm_(at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/empty_strided_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/empty_strided_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5c1c769e11af4f7b38708c39424cc1128072a6e5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/empty_strided_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, at::TensorOptions options={}); +TORCH_API at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor empty_strided_symint(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::TensorOptions options={}); +TORCH_API at::Tensor empty_strided_symint(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/erf_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/erf_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cba2c9a5a21dd1c328e8926de85d6d8436c449af --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/erf_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_erf : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv.h b/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv.h new file mode 100644 index 0000000000000000000000000000000000000000..2101cf16db06f018ebeec0f88b8278f3c2db55d5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv.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::erfinv(Tensor self) -> Tensor +inline at::Tensor erfinv(const at::Tensor & self) { + return at::_ops::erfinv::call(self); +} + +// aten::erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & erfinv_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::erfinv_out::call(self, out); +} +// aten::erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & erfinv_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::erfinv_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..61d9d6579f355db68aa6b82c644006fe22af8bb9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor erfinv(const at::Tensor & self); +TORCH_API at::Tensor & erfinv_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & erfinv_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & erfinv_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/exp2.h b/lib/python3.12/site-packages/torch/include/ATen/ops/exp2.h new file mode 100644 index 0000000000000000000000000000000000000000..69fc615bc22b9cb64dde19b57fcd300c6c088ff3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/exp2.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::exp2(Tensor self) -> Tensor +inline at::Tensor exp2(const at::Tensor & self) { + return at::_ops::exp2::call(self); +} + +// aten::exp2_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & exp2_(at::Tensor & self) { + return at::_ops::exp2_::call(self); +} + +// aten::exp2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & exp2_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::exp2_out::call(self, out); +} +// aten::exp2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & exp2_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::exp2_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/expand_as_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/expand_as_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2198ce01f90ba6fa51f1c4c601e619c2b465870c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/expand_as_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor expand_as(const at::Tensor & self, const at::Tensor & other); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/expand_copy_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/expand_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bd10495bdf7e632272bff747a66eb0284da2c9a3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/expand_copy_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 expand_copy(const at::Tensor & self, at::IntArrayRef size, bool implicit=false); +TORCH_API at::Tensor expand_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size, bool implicit=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/expand_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/expand_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b831cdd26ac8edf4fc2c2be85c5359417443235d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/expand_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 expand { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::expand"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "expand(Tensor(a) self, SymInt[] size, *, bool implicit=False) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, bool implicit); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, bool implicit); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..219a9d3fc285372f5ab405af16c0e4befe95220a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/exponential_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 exponential(const at::Tensor & self, double lambd=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & exponential_out(at::Tensor & out, const at::Tensor & self, double lambd=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & exponential_outf(const at::Tensor & self, double lambd, ::std::optional generator, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine.h new file mode 100644 index 0000000000000000000000000000000000000000..090b3728f9ae0f487a59ddf948161f462713f2be --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine.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::fake_quantize_per_tensor_affine(Tensor self, float scale, int zero_point, int quant_min, int quant_max) -> Tensor +inline at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max) { + return at::_ops::fake_quantize_per_tensor_affine::call(self, scale, zero_point, quant_min, quant_max); +} + +// aten::fake_quantize_per_tensor_affine.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max) -> Tensor +inline at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max) { + return at::_ops::fake_quantize_per_tensor_affine_tensor_qparams::call(self, scale, zero_point, quant_min, quant_max); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..488472a741ee6059b47f6e092c27d01135e85322 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_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 fake_quantize_per_tensor_affine_cachemask_backward(const at::Tensor & grad, const at::Tensor & mask); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2d66e8b04e5db132e860f74d59aad7a4b8ff4106 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor fbgemm_linear_int8_weight_fp32_activation(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ifftshift_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ifftshift_native.h new file mode 100644 index 0000000000000000000000000000000000000000..15b13d3c8be92b81481e88fb09c39d31d749ea9e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ifftshift_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 fft_ifftshift(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfftn.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfftn.h new file mode 100644 index 0000000000000000000000000000000000000000..f8eb3fbbbc8cc01a8b3b891072c44e95b6b4eae4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ihfftn.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fft_ihfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_ihfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_ihfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_ihfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_ihfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_ihfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_ihfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_ihfftn::call(self, s, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_ihfftn(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_ihfftn::call(self, s, dim, norm); + } +} + +// aten::fft_ihfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_ihfftn_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_ihfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + const at::Tensor & fft_ihfftn_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_ihfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_ihfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_ihfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_ihfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + const at::Tensor & fft_ihfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_ihfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_ihfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_ihfftn_symint_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_ihfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + const at::Tensor & fft_ihfftn_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_ihfftn_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_ihfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_ihfftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_ihfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + const at::Tensor & fft_ihfftn_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_ihfftn_out::call(self, s, dim, norm, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft2_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..48c801a338c3fb52d08076c0747212b53dd530b1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfft2_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fft_rfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_rfft2_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftn.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftn.h new file mode 100644 index 0000000000000000000000000000000000000000..16d99a7e1996c490c79aa011540b2d4fa86c7f2b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_rfftn.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fft_rfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_rfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_rfftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_rfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor +inline at::Tensor fft_rfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfftn::call(self, s, dim, norm); +} +namespace symint { + template >> + at::Tensor fft_rfftn(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfftn::call(self, s, dim, norm); + } +} + +// aten::fft_rfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_rfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_rfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfftn_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_rfftn_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_rfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_rfftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfftn_out::call(self, s, dim, norm, out); +} +namespace symint { + template >> + at::Tensor & fft_rfftn_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out) { + return at::_ops::fft_rfftn_out::call(self, s, dim, norm, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/float_power_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/float_power_native.h new file mode 100644 index 0000000000000000000000000000000000000000..29a1c06adcc33aebf4db26db42d43e179b4a4d24 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/float_power_native.h @@ -0,0 +1,28 @@ +#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 float_power(const at::Tensor & self, const at::Tensor & exponent); +TORCH_API at::Tensor & float_power_out(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out); +TORCH_API at::Tensor & float_power_(at::Tensor & self, const at::Tensor & exponent); +TORCH_API at::Tensor float_power(const at::Scalar & self, const at::Tensor & exponent); +TORCH_API at::Tensor & float_power_out(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out); +TORCH_API at::Tensor float_power(const at::Tensor & self, const at::Scalar & exponent); +TORCH_API at::Tensor & float_power_out(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out); +TORCH_API at::Tensor & float_power_(at::Tensor & self, const at::Scalar & exponent); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_native.h new file mode 100644 index 0000000000000000000000000000000000000000..692e1180d04ebd4c7be7a89bc26e823a1d656ccc --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_native.h @@ -0,0 +1,29 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & floor_divide_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor floor_divide_sparse(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & floor_divide_out_sparse_zerodim(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & floor_divide_sparse_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & floor_divide_Scalar_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Scalar & other); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fmax.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fmax.h new file mode 100644 index 0000000000000000000000000000000000000000..6a6cbd71a01126c467a667d2d845c9a01751e164 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fmax.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::fmax(Tensor self, Tensor other) -> Tensor +inline at::Tensor fmax(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::fmax::call(self, other); +} + +// aten::fmax.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::fmax_out::call(self, other, out); +} +// aten::fmax.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fmax_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::fmax_out::call(self, other, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a93af795ba6130deb5c016110ec8d823fe028b72 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_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 fmod(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/frac_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/frac_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1145715947f92322b84af159b27065a9398f89b8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/frac_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 frac(const at::Tensor & self); +TORCH_API at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & frac_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e58635d893b27a96dd5cdbacb712f2175ead1f2e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_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 ::std::tuple fractional_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); +TORCH_API ::std::tuple fractional_max_pool2d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); +TORCH_API ::std::tuple fractional_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..02a82c860f24c22aadf10f242d172fdd9bfc2b37 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_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 fractional_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); +TORCH_API ::std::tuple fractional_max_pool3d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); +TORCH_API ::std::tuple fractional_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b829bf1822eae203d97ca5e30377813b596d9e12 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_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 from_file { + using schema = at::Tensor (c10::string_view, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::from_file"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "from_file(str filename, bool? shared=None, int? size=0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor"; + static at::Tensor call(c10::string_view filename, ::std::optional shared, ::std::optional size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view filename, ::std::optional shared, ::std::optional size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API from_file_out { + using schema = at::Tensor & (c10::string_view, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::from_file"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "from_file.out(str filename, bool? shared=None, int? size=0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(c10::string_view filename, ::std::optional shared, ::std::optional size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view filename, ::std::optional shared, ::std::optional size, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d72131e5182de5ff8c56b88c577a6d670c597493 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor full_like(const at::Tensor & self, const at::Scalar & fill_value, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor full_like(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +TORCH_API at::Tensor & full_like_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & fill_value, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & full_like_outf(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional memory_format, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..25f56bfe344862446eb769fb6aec1af1aac951b5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API gelu_out { + using schema = at::Tensor & (const at::Tensor &, c10::string_view, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gelu"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "gelu.out(Tensor self, *, str approximate='none', Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::string_view approximate, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view approximate, at::Tensor & out); +}; + +struct TORCH_API gelu_ { + using schema = at::Tensor & (at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gelu_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "gelu_(Tensor(a!) self, *, str approximate='none') -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, c10::string_view approximate); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, c10::string_view approximate); +}; + +struct TORCH_API gelu { + using schema = at::Tensor (const at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gelu"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "gelu(Tensor self, *, str approximate='none') -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::string_view approximate); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view approximate); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9a95ffc2d2583aa3e6221cf2a7ecfecccf45d2e0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_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 & glu_backward_jvp_out(at::Tensor & out, const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim); +TORCH_API at::Tensor & glu_backward_jvp_outf(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/glu_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..52e332cbfc5cc9156688923d780644a304475dda --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_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 glu(const at::Tensor & self, int64_t dim=-1); +TORCH_API at::Tensor & glu_out(at::Tensor & out, const at::Tensor & self, int64_t dim=-1); +TORCH_API at::Tensor & glu_outf(const at::Tensor & self, int64_t dim, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/glu_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fd03fc6aef73edc0757fcb026f32d3aa116cfb09 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_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_glu_out : public at::meta::structured_glu { +void impl(const at::Tensor & self, int64_t dim, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c8e065ba16645a2adbfaf5fdacc11a80d9dec72e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_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 grid_sampler_3d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fa91ceddc47270f02ff2ceff9da720097c7d1d3c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor hann_window(int64_t window_length, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & hann_window_out(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor hann_window(int64_t window_length, bool periodic, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & hann_window_periodic_out(int64_t window_length, bool periodic, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink.h new file mode 100644 index 0000000000000000000000000000000000000000..037c6b0831737b153e936e83a66bd1ff3295db85 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink.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::hardshrink.out(Tensor self, Scalar lambd=0.5, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hardshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5) { + return at::_ops::hardshrink_out::call(self, lambd, out); +} +// aten::hardshrink.out(Tensor self, Scalar lambd=0.5, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hardshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out) { + return at::_ops::hardshrink_out::call(self, lambd, out); +} + +// aten::hardshrink(Tensor self, Scalar lambd=0.5) -> Tensor +inline at::Tensor hardshrink(const at::Tensor & self, const at::Scalar & lambd=0.5) { + return at::_ops::hardshrink::call(self, lambd); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64ce3072ecbb371c1c166e61fb11567872f6913e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor hardshrink(const at::Tensor & self, const at::Scalar & lambd=0.5); +TORCH_API at::Tensor & hardshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5); +TORCH_API at::Tensor & hardshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d3e9826d018543e909dd3d33623f6f8e51fec9a5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_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 hardswish_backward { + 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 const char* name = "aten::hardswish_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hardswish_backward(Tensor grad_output, Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self); +}; + +struct TORCH_API hardswish_backward_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 const char* name = "aten::hardswish_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "hardswish_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh.h new file mode 100644 index 0000000000000000000000000000000000000000..8c9971767b87d5cc8672885b78358f1d8ad51715 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh.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::hardtanh.out(Tensor self, Scalar min_val=-1, Scalar max_val=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hardtanh_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1) { + return at::_ops::hardtanh_out::call(self, min_val, max_val, out); +} +// aten::hardtanh.out(Tensor self, Scalar min_val=-1, Scalar max_val=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hardtanh_outf(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out) { + return at::_ops::hardtanh_out::call(self, min_val, max_val, out); +} + +// aten::hardtanh(Tensor self, Scalar min_val=-1, Scalar max_val=1) -> Tensor +inline at::Tensor hardtanh(const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1) { + return at::_ops::hardtanh::call(self, min_val, max_val); +} + +// aten::hardtanh_(Tensor(a!) self, Scalar min_val=-1, Scalar max_val=1) -> Tensor(a!) +inline at::Tensor & hardtanh_(at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1) { + return at::_ops::hardtanh_::call(self, min_val, max_val); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/histc_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/histc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ca4c5490e5f10a009cdaabb46c5a246b9d4385e7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/histc_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor histogram_histc(const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0); +TORCH_API at::Tensor & histogram_histc_out(const at::Tensor & self, int64_t bins, const at::Scalar & min, const at::Scalar & max, at::Tensor & out); +TORCH_API at::Tensor _histc_cuda(const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0); +TORCH_API at::Tensor & _histc_out_cuda(const at::Tensor & self, int64_t bins, const at::Scalar & min, const at::Scalar & max, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hsplit_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hsplit_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e5bb8049724285cc8faf8b1143b840d41ee9d09 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hsplit_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::vector hsplit(const at::Tensor & self, int64_t sections); +TORCH_API ::std::vector hsplit(const at::Tensor & self, at::IntArrayRef indices); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hstack_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hstack_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ed437f2532da01d8a71f386449f2102a61fbd550 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hstack_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 hstack { + using schema = at::Tensor (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hstack"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hstack(Tensor[] tensors) -> Tensor"; + static at::Tensor call(at::TensorList tensors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +struct TORCH_API hstack_out { + using schema = at::Tensor & (at::TensorList, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hstack"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "hstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(at::TensorList tensors, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hypot.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hypot.h new file mode 100644 index 0000000000000000000000000000000000000000..9728e49095ea04e000e9ea8f125faf5208de1e55 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hypot.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::hypot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hypot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::hypot_out::call(self, other, out); +} +// aten::hypot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hypot_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::hypot_out::call(self, other, out); +} + +// aten::hypot(Tensor self, Tensor other) -> Tensor +inline at::Tensor hypot(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::hypot::call(self, other); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a073bed34110233a9370f476e37ddadb51feb9f9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hypot_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 hypot(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & hypot_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/i0_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/i0_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f21daeb1bfe50734f5646f253d62d86a33406c04 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/i0_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor i0(const at::Tensor & self); +TORCH_API at::Tensor & i0_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & i0_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & i0_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/igammac_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/igammac_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b962279017f3946dfdd269b4b3b3a8879b36567c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/igammac_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API igammac_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::igammac"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "igammac.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API igammac { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::igammac"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "igammac(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API igammac_ { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::igammac_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "igammac_(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/im2col.h b/lib/python3.12/site-packages/torch/include/ATen/ops/im2col.h new file mode 100644 index 0000000000000000000000000000000000000000..d80c4072e88c644bf42f320ebe1307c3c1b834d4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/im2col.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::im2col.out(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & im2col_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride) { + return at::_ops::im2col_out::call(self, kernel_size, dilation, padding, stride, out); +} +// aten::im2col.out(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & im2col_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::im2col_out::call(self, kernel_size, dilation, padding, stride, out); +} + +// aten::im2col(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride) -> Tensor +inline at::Tensor im2col(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride) { + return at::_ops::im2col::call(self, kernel_size, dilation, padding, stride); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_add_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_add_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4080458b80553ba8663d14ea25b396020aac9d23 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_add_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor index_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); +TORCH_API at::Tensor & index_add_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); +TORCH_API at::Tensor & index_add_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & index_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ffc46538c69526890151db27afd927707c87d8d8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_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 index(const at::Tensor & self, const c10::List<::std::optional> & indices); +TORCH_API at::Tensor & index_out(at::Tensor & out, const at::Tensor & self, const c10::List<::std::optional> & indices); +TORCH_API at::Tensor & index_outf(const at::Tensor & self, const c10::List<::std::optional> & indices, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2b5629a5f920c731e3ed8cbcc703c83e630058c7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_index_out : public at::meta::structured_index_Tensor { +void impl(const at::Tensor & self, at::DimVector sizes, at::DimVector strides, const at::Tensor & out); +}; +TORCH_API at::Tensor quantized_index(const at::Tensor & self, const c10::List<::std::optional> & indices); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e1bdada37eeca0157e39485bc18b89259cd77452 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_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 index_reduce(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self=true); +TORCH_API at::Tensor & index_reduce_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self=true); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3a00a88d2ae924fec00dff4a255dd40aa4fe1912 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor index_reduce(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self=true); +TORCH_API at::Tensor & index_reduce_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self=true); +TORCH_API at::Tensor & index_reduce_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self, at::Tensor & out); +TORCH_API at::Tensor & index_reduce_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self=true); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0960b339c8b12aa7a45d75f574af7e521c7c0276 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API index_reduce_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, const at::Tensor &, const at::Tensor &, c10::string_view, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::index_reduce"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "index_reduce.out(Tensor self, int dim, Tensor index, Tensor source, str reduce, *, bool include_self=True, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self, at::Tensor & out); +}; + +struct TORCH_API index_reduce_ { + using schema = at::Tensor & (at::Tensor &, int64_t, const at::Tensor &, const at::Tensor &, c10::string_view, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::index_reduce_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "index_reduce_(Tensor(a!) self, int dim, Tensor index, Tensor source, str reduce, *, bool include_self=True) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self); +}; + +struct TORCH_API index_reduce { + using schema = at::Tensor (const at::Tensor &, int64_t, const at::Tensor &, const at::Tensor &, c10::string_view, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::index_reduce"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "index_reduce(Tensor self, int dim, Tensor index, Tensor source, str reduce, *, bool include_self=True) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, c10::string_view reduce, bool include_self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/inner_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/inner_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64a0abc863fd95e0dc9fb86d5db508d039c4d547 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/inner_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 inner(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & inner_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & inner_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/instance_norm_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/instance_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..426f3b785c90c6e24ed93f841bd2e81f050cab66 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/instance_norm_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 instance_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool use_input_stats, double momentum, double eps, bool cudnn_enabled); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/is_distributed.h b/lib/python3.12/site-packages/torch/include/ATen/ops/is_distributed.h new file mode 100644 index 0000000000000000000000000000000000000000..982b483160abf79df13dce6ba0e367f8f6b13486 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/is_distributed.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::is_distributed(Tensor self) -> bool +inline bool is_distributed(const at::Tensor & self) { + return at::_ops::is_distributed::call(self); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/is_same_size_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/is_same_size_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1c7b8206515af1375770ce99df6ac17821cc3dd7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/is_same_size_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API bool is_same_size(const at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/is_same_size_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/is_same_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c2becf3246989fc572364db0412388712e3c54de --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/is_same_size_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API is_same_size { + using schema = bool (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::is_same_size"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "is_same_size(Tensor self, Tensor other) -> bool"; + static bool call(const at::Tensor & self, const at::Tensor & other); + static bool redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/isclose.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isclose.h new file mode 100644 index 0000000000000000000000000000000000000000..452c37ccb7338c42e5b5c218fa54bec5c1dc33ac --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isclose.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::isclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> Tensor +inline at::Tensor isclose(const at::Tensor & self, const at::Tensor & other, double rtol=1e-05, double atol=1e-08, bool equal_nan=false) { + return at::_ops::isclose::call(self, other, rtol, atol, equal_nan); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/isclose_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isclose_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb7f4052ee537e17340b969829ddd20e3a4ab4c4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isclose_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 isclose(const at::Tensor & self, const at::Tensor & other, double rtol=1e-05, double atol=1e-08, bool equal_nan=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/isfinite_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isfinite_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..def73445aa606f253e255ab9ef8d1208835d20af --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isfinite_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 isfinite(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/isinf_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isinf_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a81e30ed68be2908324d846ea765009095ea1f72 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isinf_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 isinf { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::isinf"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "isinf(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 isinf_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 const char* name = "aten::isinf"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "isinf.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/lib/python3.12/site-packages/torch/include/ATen/ops/isreal_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isreal_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7d3de4e56e6e85bb25307be8a20a95c3062c524b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isreal_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 isreal(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/kaiser_window_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/kaiser_window_native.h new file mode 100644 index 0000000000000000000000000000000000000000..51d2108114bcb0ecfb4c173cbce6e8534817fce1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/kaiser_window_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor kaiser_window(int64_t window_length, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & kaiser_window_out(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & kaiser_window_periodic_out(int64_t window_length, bool periodic, at::Tensor & out); +TORCH_API at::Tensor kaiser_window(int64_t window_length, bool periodic, double beta, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & kaiser_window_beta_out(int64_t window_length, bool periodic, double beta, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/kron_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/kron_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0a7675c2860154b74817d55e3ecc269052e0c8f1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/kron_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 kron(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & kron_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & kron_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d601b61ad7a29c998b2c6e1a18a99c46af23c8f2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/leaky_relu_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_leaky_relu_out : public at::meta::structured_leaky_relu { +void impl(const at::Tensor & self, const at::Scalar & negative_slope, const at::Tensor & out); +}; +TORCH_API at::Tensor leaky_relu_quantized_cpu(const at::Tensor & self, const at::Scalar & negative_slope=0.01); +TORCH_API at::Tensor & leaky_relu_out_quantized_cpu(const at::Tensor & self, const at::Scalar & negative_slope, at::Tensor & out); +TORCH_API at::Tensor & leaky_relu_quantized_cpu_(at::Tensor & self, const at::Scalar & negative_slope=0.01); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/less_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/less_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1787471c9f44c97f73334aefb426695c30091f5d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/less_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor less(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & less_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & less_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & less_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor less(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & less_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & less_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & less_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e9233c0a783f38427c158b2a6377d9ea081edb29 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_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 lgamma(const at::Tensor & self); +TORCH_API at::Tensor & lgamma_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b04ec3c0675c7a40f966f5f0ab58f9ac19b833c5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cholesky_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_cholesky { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_cholesky"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_cholesky(Tensor self, *, bool upper=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, bool upper); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper); +}; + +struct TORCH_API linalg_cholesky_out { + using schema = at::Tensor & (const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_cholesky"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_cholesky.out(Tensor self, *, bool upper=False, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, bool upper, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7149e0c7e3711614e8157d2a6b14cd68671ce0e8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_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 linalg_cross(const at::Tensor & self, const at::Tensor & other, int64_t dim=-1); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigh_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigh_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..00ee1cf75f0bf9d2d4357eed26def19470dc8f38 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigh_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 linalg_eigh(const at::Tensor & self, c10::string_view UPLO="L"); +TORCH_API ::std::tuple linalg_eigh_out(at::Tensor & eigvals, at::Tensor & eigvecs, const at::Tensor & self, c10::string_view UPLO="L"); +TORCH_API ::std::tuple linalg_eigh_outf(const at::Tensor & self, c10::string_view UPLO, at::Tensor & eigvals, at::Tensor & eigvecs); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_ex_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_ex_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ca902f8f5b869ea54fc1e7a13324af3b4d779f7a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_inv_ex_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 ::std::tuple linalg_inv_ex(const at::Tensor & A, bool check_errors=false); +TORCH_API ::std::tuple linalg_inv_ex_out(at::Tensor & inverse, at::Tensor & info, const at::Tensor & A, bool check_errors=false); +TORCH_API ::std::tuple linalg_inv_ex_outf(const at::Tensor & A, bool check_errors, at::Tensor & inverse, at::Tensor & info); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..235e90e6557f8016e59481989862b927767639bb --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple linalg_ldl_factor_ex(const at::Tensor & self, bool hermitian=false, bool check_errors=false); +TORCH_API ::std::tuple linalg_ldl_factor_ex_out(at::Tensor & LD, at::Tensor & pivots, at::Tensor & info, const at::Tensor & self, bool hermitian=false, bool check_errors=false); +TORCH_API ::std::tuple linalg_ldl_factor_ex_outf(const at::Tensor & self, bool hermitian, bool check_errors, at::Tensor & LD, at::Tensor & pivots, at::Tensor & info); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d3066dba9409d29f7ff0b8de4b34106db368173e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_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_lu_out : public at::meta::structured_linalg_lu { +void impl(const at::Tensor & A, bool pivot, const at::Tensor & P, const at::Tensor & L, const at::Tensor & U); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_exp_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_exp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8193bc32084af6ab9b341f80ab5575840b536783 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_exp_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_matrix_exp { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_matrix_exp"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_matrix_exp(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 linalg_matrix_exp_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 const char* name = "aten::linalg_matrix_exp"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_matrix_exp.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/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_power_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_power_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9c2b0462e70d07b48c6c40e5c407e5de31cd6148 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_matrix_power_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_matrix_power(const at::Tensor & self, int64_t n); +TORCH_API at::Tensor & linalg_matrix_power_out(at::Tensor & out, const at::Tensor & self, int64_t n); +TORCH_API at::Tensor & linalg_matrix_power_outf(const at::Tensor & self, int64_t n, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linear.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linear.h new file mode 100644 index 0000000000000000000000000000000000000000..826d2f525008c8964923e7bd1ff12230493b79e0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linear.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::linear(Tensor input, Tensor weight, Tensor? bias=None) -> Tensor +inline at::Tensor linear(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}) { + return at::_ops::linear::call(input, weight, bias); +} + +// aten::linear.out(Tensor input, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linear_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}) { + return at::_ops::linear_out::call(input, weight, bias, out); +} +// aten::linear.out(Tensor input, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linear_outf(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::Tensor & out) { + return at::_ops::linear_out::call(input, weight, bias, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/log10_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/log10_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1731b779f5d1c4f550daefc6c9ca4c504ea4b408 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/log10_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 log10(const at::Tensor & self); +TORCH_API at::Tensor & log10_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b09beb78f64ae8bb391e6ff4e84e69244d3302fa --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp2_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 logaddexp2_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 const char* name = "aten::logaddexp2"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "logaddexp2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API logaddexp2 { + 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 const char* name = "aten::logaddexp2"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "logaddexp2(Tensor self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..24abd8d61c504e34ffe5a93a27ce3ab59b649b52 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & logical_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/logspace_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logspace_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f9a959ac8b96a9ddc55070a1d62f7fb3b9190243 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logspace_compositeexplicitautograd_dispatch.h @@ -0,0 +1,36 @@ +#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 logspace(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base=10.0, at::TensorOptions options={}); +TORCH_API at::Tensor logspace(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor logspace(const at::Tensor & start, const at::Tensor & end, int64_t steps, double base=10.0, at::TensorOptions options={}); +TORCH_API at::Tensor logspace(const at::Tensor & start, const at::Tensor & end, int64_t steps, double base, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & logspace_out(at::Tensor & out, const at::Tensor & start, const at::Tensor & end, int64_t steps, double base=10.0); +TORCH_API at::Tensor & logspace_outf(const at::Tensor & start, const at::Tensor & end, int64_t steps, double base, at::Tensor & out); +TORCH_API at::Tensor logspace(const at::Tensor & start, const at::Scalar & end, int64_t steps, double base=10.0, at::TensorOptions options={}); +TORCH_API at::Tensor logspace(const at::Tensor & start, const at::Scalar & end, int64_t steps, double base, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & logspace_out(at::Tensor & out, const at::Tensor & start, const at::Scalar & end, int64_t steps, double base=10.0); +TORCH_API at::Tensor & logspace_outf(const at::Tensor & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out); +TORCH_API at::Tensor logspace(const at::Scalar & start, const at::Tensor & end, int64_t steps, double base=10.0, at::TensorOptions options={}); +TORCH_API at::Tensor logspace(const at::Scalar & start, const at::Tensor & end, int64_t steps, double base, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & logspace_out(at::Tensor & out, const at::Scalar & start, const at::Tensor & end, int64_t steps, double base=10.0); +TORCH_API at::Tensor & logspace_outf(const at::Scalar & start, const at::Tensor & end, int64_t steps, double base, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/logspace_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logspace_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4784f6355fabc265d6c469efc4a1620a8af89303 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logspace_meta_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 meta { + +TORCH_API at::Tensor & logspace_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, int64_t steps, double base=10.0); +TORCH_API at::Tensor & logspace_outf(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/logsumexp_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logsumexp_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f8ec729a51449a1c18d5ba105937f5eef48d30f6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logsumexp_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor logsumexp(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/lshift_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/lshift_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4ea87895aa007bbcb84885e1f136c328c6de9442 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/lshift_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API __lshift___Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::__lshift__"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "__lshift__.Scalar(Tensor self, Scalar other) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API __lshift___Tensor { + 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 const char* name = "aten::__lshift__"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "__lshift__.Tensor(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 __ilshift___Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::__ilshift__"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "__ilshift__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API __ilshift___Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::__ilshift__"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "__ilshift__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API __lshift___Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::__lshift__"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "__lshift__.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +struct TORCH_API __lshift___Tensor_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 const char* name = "aten::__lshift__"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "__lshift__.Tensor_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/lib/python3.12/site-packages/torch/include/ATen/ops/mH.h b/lib/python3.12/site-packages/torch/include/ATen/ops/mH.h new file mode 100644 index 0000000000000000000000000000000000000000..4ace1de719bac0253aaa735b708900c6dc2905b5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/mH.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill.h b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill.h new file mode 100644 index 0000000000000000000000000000000000000000..7c13860d0582d86580f0ff4664f63ef9780d639f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::masked_fill.Scalar(Tensor self, Tensor mask, Scalar value) -> Tensor +inline at::Tensor masked_fill(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value) { + return at::_ops::masked_fill_Scalar::call(self, mask, value); +} + +// aten::masked_fill.Tensor(Tensor self, Tensor mask, Tensor value) -> Tensor +inline at::Tensor masked_fill(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value) { + return at::_ops::masked_fill_Tensor::call(self, mask, value); +} + +// aten::masked_fill.Scalar_out(Tensor self, Tensor mask, Scalar value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & masked_fill_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value) { + return at::_ops::masked_fill_Scalar_out::call(self, mask, value, out); +} +// aten::masked_fill.Scalar_out(Tensor self, Tensor mask, Scalar value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & masked_fill_outf(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value, at::Tensor & out) { + return at::_ops::masked_fill_Scalar_out::call(self, mask, value, out); +} + +// aten::masked_fill.Tensor_out(Tensor self, Tensor mask, Tensor value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & masked_fill_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value) { + return at::_ops::masked_fill_Tensor_out::call(self, mask, value, out); +} +// aten::masked_fill.Tensor_out(Tensor self, Tensor mask, Tensor value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & masked_fill_outf(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value, at::Tensor & out) { + return at::_ops::masked_fill_Tensor_out::call(self, mask, value, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a5a292b785ec9aa27e43901435418c6ff1f32643 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_backward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API masked_select_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::masked_select_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "masked_select_backward(Tensor grad, Tensor input, Tensor mask) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, const at::Tensor & input, const at::Tensor & mask); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & input, const at::Tensor & mask); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/max_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/max_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..773c588deda076c45abfaefd08924c8fd3525ac7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/max_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple max(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple max_out(at::Tensor & max, at::Tensor & max_values, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API ::std::tuple max_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & max, at::Tensor & max_values); +TORCH_API at::Tensor max(const at::Tensor & self); +TORCH_API at::Tensor & max_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & max_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1d80928e8e32b3eb7dfe4b478502a54371cc55b3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_backward_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor max_pool2d_with_indices_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); +TORCH_API at::Tensor & max_pool2d_with_indices_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); +TORCH_API at::Tensor & max_pool2d_with_indices_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..90cb462e80eb3c6fb0f53cd3da058af12e413546 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API ::std::tuple max_pool2d_with_indices(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool3d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..85b946fa1d9efd43e4699315d041a8bcb04bd9a9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool3d_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor max_unpooling3d_forward_cpu(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor & max_unpooling3d_forward_out_cpu(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor max_unpooling3d_forward_cuda(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor & max_unpooling3d_forward_out_cuda(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5f5d690fbef2c8ffc4b27e0dd37ebddda29766e9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_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 maximum(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & maximum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & maximum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_relu_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_relu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d845b5239444c4f7391b55af45d7fa1849737992 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_relu_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 miopen_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution.h b/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution.h new file mode 100644 index 0000000000000000000000000000000000000000..3b5f859d3126236686539534613701fbcf7081ad --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution.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::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); +} +namespace symint { + template >> + at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic); + } +} + +// aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor +inline at::Tensor miopen_depthwise_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic); +} +namespace symint { + template >> + at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic); + } +} + +// aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_depthwise_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_depthwise_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_depthwise_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_depthwise_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, out); + } +} + +// aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_depthwise_convolution_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_depthwise_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); + } +} + +// aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & miopen_depthwise_convolution_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); +} +namespace symint { + template >> + at::Tensor & miopen_depthwise_convolution_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out) { + return at::_ops::miopen_depthwise_convolution_out::call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/mish_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/mish_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6986cd4175566a61dbc891668933aedba814b30d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/mish_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 mish(const at::Tensor & self); +TORCH_API at::Tensor & mish_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & mish_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & mish_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..635c0ebec8a9fb68d72bd9a39207628f681978f9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_max_pool3d_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API mkldnn_max_pool3d { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode); +}; + +struct TORCH_API mkldnn_max_pool3d_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mkldnn_max_pool3d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mkldnn_max_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_native.h new file mode 100644 index 0000000000000000000000000000000000000000..04d127e182a84972c251abbdfacc1aab47c88877 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple mkldnn_rnn_layer_out(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +TORCH_API ::std::tuple mkldnn_rnn_layer(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bde301cc371ac8c109799990542656f18b6b3d98 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/mode_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3352a9f373be6eae8a3726a156a8d6b99f4872a8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/mse_loss_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & mse_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/multinomial_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/multinomial_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..46d6ac549638700ddf1b672afe2fc20f62c286e7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/multinomial_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor multinomial(const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_outf(const at::Tensor & self, int64_t num_samples, bool replacement, ::std::optional generator, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nanmedian_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nanmedian_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d333c663d6e66c359871ef41ad46cdcf6224a62c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nanmedian_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 & nanmedian_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & nanmedian_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API ::std::tuple nanmedian(const at::Tensor & self, int64_t dim, bool keepdim=false); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_copy_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2d8304d9d1eb9a7a3879a74e39488816971a56d9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/narrow_copy_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 narrow_copy(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_copy_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..84ddddb676649a67363e0f567d2831bee6c647b9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_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 ::std::tuple native_batch_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::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 ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple native_batch_norm_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9acc93e36a7bb4e031f6ebbc72eff0d4ce8df706 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/native_batch_norm_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple batch_norm_cpu(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple batch_norm_cpu_out(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); +TORCH_API ::std::tuple batch_norm_cuda(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple batch_norm_cuda_out(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); +TORCH_API ::std::tuple mkldnn_batch_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool training, double momentum, double eps); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/native_channel_shuffle_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/native_channel_shuffle_native.h new file mode 100644 index 0000000000000000000000000000000000000000..85490fa13dc684f3cc0a645f7f949ed4932a0a02 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/native_channel_shuffle_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 math_channel_shuffle(const at::Tensor & self, int64_t groups); +TORCH_API at::Tensor channel_shuffle_cpu(const at::Tensor & self, int64_t groups); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a525c8561321c00085445f2bcfca2f288f60b1c2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_backward_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor native_dropout_backward(const at::Tensor & grad_output, const at::Tensor & mask, double scale); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..541d8fba53d971aebec6e1d099b627d35abcddb9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/native_dropout_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 native_dropout { + using schema = ::std::tuple (const at::Tensor &, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_dropout"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "native_dropout(Tensor input, float p, bool? train) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & input, double p, ::std::optional train); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, double p, ::std::optional train); +}; + +struct TORCH_API native_dropout_out { + using schema = ::std::tuple (const at::Tensor &, double, ::std::optional, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::native_dropout"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "native_dropout.out(Tensor input, float p, bool? train, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & input, double p, ::std::optional train, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, double p, ::std::optional train, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..cd0bd5112c3829f47f8c45ede9d84aea73c349e5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_backward.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::native_layer_norm_backward(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple native_layer_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask) { + return at::_ops::native_layer_norm_backward::call(grad_out, input, c10::fromIntArrayRefSlow(normalized_shape), mean, rstd, weight, bias, output_mask); +} +namespace symint { + template >> + ::std::tuple native_layer_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask) { + return at::_ops::native_layer_norm_backward::call(grad_out, input, c10::fromIntArrayRefSlow(normalized_shape), mean, rstd, weight, bias, output_mask); + } +} + +// aten::native_layer_norm_backward(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple native_layer_norm_backward_symint(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask) { + return at::_ops::native_layer_norm_backward::call(grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask); +} +namespace symint { + template >> + ::std::tuple native_layer_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask) { + return at::_ops::native_layer_norm_backward::call(grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask); + } +} + +// aten::native_layer_norm_backward.out(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_layer_norm_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask) { + return at::_ops::native_layer_norm_backward_out::call(grad_out, input, c10::fromIntArrayRefSlow(normalized_shape), mean, rstd, weight, bias, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple native_layer_norm_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask) { + return at::_ops::native_layer_norm_backward_out::call(grad_out, input, c10::fromIntArrayRefSlow(normalized_shape), mean, rstd, weight, bias, output_mask, out0, out1, out2); + } +} + +// aten::native_layer_norm_backward.out(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_layer_norm_backward_outf(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_layer_norm_backward_out::call(grad_out, input, c10::fromIntArrayRefSlow(normalized_shape), mean, rstd, weight, bias, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple native_layer_norm_backward_outf(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_layer_norm_backward_out::call(grad_out, input, c10::fromIntArrayRefSlow(normalized_shape), mean, rstd, weight, bias, output_mask, out0, out1, out2); + } +} + +// aten::native_layer_norm_backward.out(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_layer_norm_backward_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask) { + return at::_ops::native_layer_norm_backward_out::call(grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple native_layer_norm_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask) { + return at::_ops::native_layer_norm_backward_out::call(grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask, out0, out1, out2); + } +} + +// aten::native_layer_norm_backward.out(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_layer_norm_backward_symint_outf(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_layer_norm_backward_out::call(grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask, out0, out1, out2); +} +namespace symint { + template >> + ::std::tuple native_layer_norm_backward_outf(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const ::std::optional & weight, const ::std::optional & bias, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_layer_norm_backward_out::call(grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask, out0, out1, out2); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..db9fb8ea53326e8b899b5744eb2df33aecb2dd9b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/native_layer_norm_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple native_layer_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); +TORCH_API ::std::tuple native_layer_norm_symint(const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); +TORCH_API ::std::tuple native_layer_norm_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); +TORCH_API ::std::tuple native_layer_norm_outf(const at::Tensor & input, at::IntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple native_layer_norm_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps); +TORCH_API ::std::tuple native_layer_norm_symint_outf(const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const ::std::optional & weight, const ::std::optional & bias, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/new_ones.h b/lib/python3.12/site-packages/torch/include/ATen/ops/new_ones.h new file mode 100644 index 0000000000000000000000000000000000000000..64fa4ad97a802e48dd5e306d6558709bd557d93c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/new_ones.h @@ -0,0 +1,97 @@ +#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 { + + +namespace symint { + template >> + at::Tensor new_ones(const at::Tensor & self, at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::new_ones::call(self, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +namespace symint { + template >> + at::Tensor new_ones(const at::Tensor & self, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::new_ones::call(self, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +namespace symint { + template >> + at::Tensor new_ones(const at::Tensor & self, c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::new_ones::call(self, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +namespace symint { + template >> + at::Tensor new_ones(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::new_ones::call(self, size, dtype, layout, device, pin_memory); + } +} + +// aten::new_ones.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_ones_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::new_ones_out::call(self, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & new_ones_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::new_ones_out::call(self, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::new_ones.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_ones_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::new_ones_out::call(self, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & new_ones_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::new_ones_out::call(self, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::new_ones.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_ones_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::new_ones_out::call(self, size, out); +} +namespace symint { + template >> + at::Tensor & new_ones_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::new_ones_out::call(self, size, out); + } +} + +// aten::new_ones.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_ones_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::new_ones_out::call(self, size, out); +} +namespace symint { + template >> + at::Tensor & new_ones_outf(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::new_ones_out::call(self, size, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..966a835e28805362dd75061f8074ce1cdec65ac1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_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 nextafter(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & nextafter_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f4887af32625ef272f2a52c8976a63319ed15556 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nextafter_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_nextafter : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b56f7cc8a949006bfdc38e2464777b24c8b8c07b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple nll_loss2d_forward(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index); +TORCH_API ::std::tuple nll_loss2d_forward_symint(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index); +TORCH_API ::std::tuple nll_loss2d_forward_out(at::Tensor & output, at::Tensor & total_weight, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index); +TORCH_API ::std::tuple nll_loss2d_forward_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index, at::Tensor & output, at::Tensor & total_weight); +TORCH_API ::std::tuple nll_loss2d_forward_symint_out(at::Tensor & output, at::Tensor & total_weight, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index); +TORCH_API ::std::tuple nll_loss2d_forward_symint_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & output, at::Tensor & total_weight); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_backward_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a903fae7c73351906323ac767fb939bfdb5652b9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_backward_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 nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::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 ::std::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 ::std::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 ::std::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 ::std::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 ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cb1648378d7eaaa47b433d539182e80343f5a384 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_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 ::std::tuple nll_loss_forward(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, int64_t ignore_index); +TORCH_API ::std::tuple nll_loss_forward_symint(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bfeb60ce37e7b5d808c126ecc6d1e17ee7fba447 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor nonzero(const at::Tensor & self); +TORCH_API at::Tensor & nonzero_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & nonzero_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_static_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_static_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9690c07494ae12e7afdad1cc7de61e9c09d1ec3b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_static_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor nonzero_static(const at::Tensor & self, int64_t size, int64_t fill_value=-1); +TORCH_API at::Tensor & nonzero_static_out(at::Tensor & out, const at::Tensor & self, int64_t size, int64_t fill_value=-1); +TORCH_API at::Tensor & nonzero_static_outf(const at::Tensor & self, int64_t size, int64_t fill_value, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/norm_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..233ec87b1ce1ffcdb19ab5d324dfa556304ca343 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/norm_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor norm(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); +TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); +TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype, at::Tensor & out); +TORCH_API at::Tensor norm(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const ::std::optional & p, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/not_equal_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/not_equal_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6b9a6f8e976d4659ebaa0ba68c74543cd0306cf1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/not_equal_compositeimplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor not_equal(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & not_equal_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & not_equal_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & not_equal_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor not_equal(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & not_equal_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & not_equal_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & not_equal_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/outer_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/outer_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f5ffdf44547c52c8b6c86b5acec37f47588bd5a9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/outer_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 outer(const at::Tensor & self, const at::Tensor & vec2); +TORCH_API at::Tensor & outer_out(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/output_nr.h b/lib/python3.12/site-packages/torch/include/ATen/ops/output_nr.h new file mode 100644 index 0000000000000000000000000000000000000000..4e83b3e7559d09edf7ea6d607fffdb49293f29eb --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/output_nr.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/pad_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/pad_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..897b56a727ad8e81631ceb4b2f9d270f37087a88 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/pad_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 pad(const at::Tensor & self, at::IntArrayRef pad, c10::string_view mode="constant", ::std::optional value=::std::nullopt); +TORCH_API at::Tensor pad_symint(const at::Tensor & self, c10::SymIntArrayRef pad, c10::string_view mode="constant", ::std::optional value=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/pairwise_distance_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/pairwise_distance_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cb5d0d1487c0babb782167f6ab08a691eac1e875 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/pairwise_distance_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 pairwise_distance(const at::Tensor & x1, const at::Tensor & x2, double p=2, double eps=1e-06, bool keepdim=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/permute_copy_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/permute_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2a144c8454ef80f54b0d9d1fb1e315c461ca76b8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/permute_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & permute_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dims); +TORCH_API at::Tensor & permute_copy_outf(const at::Tensor & self, at::IntArrayRef dims, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_shuffle_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_shuffle_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4d0558410fd90da9934958af21545e84d8524657 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_shuffle_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & pixel_shuffle_out(const at::Tensor & self, int64_t upscale_factor, at::Tensor & out); +TORCH_API at::Tensor pixel_shuffle_cpu(const at::Tensor & self, int64_t upscale_factor); +TORCH_API at::Tensor math_pixel_shuffle(const at::Tensor & self, int64_t upscale_factor); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..afa8e142702362de4ef26a8c0484561a20ea2ade --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/pixel_unshuffle_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 pixel_unshuffle(const at::Tensor & self, int64_t downscale_factor); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/polygamma_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/polygamma_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4262672a32d8925f7d4bcd3fe1f46815fb7ef464 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/polygamma_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_polygamma_out : public at::meta::structured_polygamma { +void impl(int64_t n, const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor & polygamma_(at::Tensor & self, int64_t n); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/pow_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/pow_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7eecf48fbdeed02fbd22e146fbd676dc1695379b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/pow_cuda_dispatch.h @@ -0,0 +1,33 @@ +#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 pow(const at::Tensor & self, const at::Tensor & exponent); +TORCH_API at::Tensor & pow_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & exponent); +TORCH_API at::Tensor & pow_outf(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out); +TORCH_API at::Tensor & pow_(at::Tensor & self, const at::Tensor & exponent); +TORCH_API at::Tensor pow(const at::Scalar & self, const at::Tensor & exponent); +TORCH_API at::Tensor & pow_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & exponent); +TORCH_API at::Tensor & pow_outf(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out); +TORCH_API at::Tensor pow(const at::Tensor & self, const at::Scalar & exponent); +TORCH_API at::Tensor & pow_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & exponent); +TORCH_API at::Tensor & pow_outf(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out); +TORCH_API at::Tensor & pow_(at::Tensor & self, const at::Scalar & exponent); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/prelu_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/prelu_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..15753a36ddb31bbf04ea3432d342f5bf3456c69b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/prelu_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor prelu(const at::Tensor & self, const at::Tensor & weight); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/promote_types.h b/lib/python3.12/site-packages/torch/include/ATen/ops/promote_types.h new file mode 100644 index 0000000000000000000000000000000000000000..537c9ca0fa63f38c586fd5a0eee4b7e34b5fa347 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/promote_types.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::promote_types(ScalarType type1, ScalarType type2) -> ScalarType +inline at::ScalarType promote_types(at::ScalarType type1, at::ScalarType type2) { + return at::_ops::promote_types::call(type1, type2); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/q_zero_point.h b/lib/python3.12/site-packages/torch/include/ATen/ops/q_zero_point.h new file mode 100644 index 0000000000000000000000000000000000000000..f5331581f7cad74c899607b374a8a19fcdd8a590 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/q_zero_point.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::q_zero_point(Tensor self) -> int +inline int64_t q_zero_point(const at::Tensor & self) { + return at::_ops::q_zero_point::call(self); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic_native.h new file mode 100644 index 0000000000000000000000000000000000000000..604bbc101948157785057bd722243983136fb5e8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic_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 & quantize_per_tensor_dynamic_out(const at::Tensor & self, at::ScalarType dtype, bool reduce_range, at::Tensor & out); +TORCH_API at::Tensor quantize_per_tensor_dynamic(const at::Tensor & self, at::ScalarType dtype, bool reduce_range); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool1d_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool1d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9ba69e90ecf528054d2f712d37f16dccfafd02cb --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool1d_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 & quantized_max_pool1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +TORCH_API at::Tensor & quantized_max_pool1d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_relu_cell_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_relu_cell_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0b8cc6c660d8c4a9c23fe20c0c75a77f559edeef --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_relu_cell_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 quantized_rnn_relu_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/rand.h b/lib/python3.12/site-packages/torch/include/ATen/ops/rand.h new file mode 100644 index 0000000000000000000000000000000000000000..31a35a1acab59da49b9e96dc84fdfb370894d8fd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/rand.h @@ -0,0 +1,377 @@ +#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::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand(at::IntArrayRef size, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::rand_names::call(c10::fromIntArrayRefSlow(size), names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor rand(at::IntArrayRef size, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::rand_names::call(c10::fromIntArrayRefSlow(size), names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand(at::IntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_names::call(c10::fromIntArrayRefSlow(size), names, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor rand(at::IntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_names::call(c10::fromIntArrayRefSlow(size), names, dtype, layout, device, pin_memory); + } +} + +// aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand_symint(c10::SymIntArrayRef size, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::rand_names::call(size, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor rand(c10::SymIntArrayRef size, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::rand_names::call(size, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand_symint(c10::SymIntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_names::call(size, names, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor rand(c10::SymIntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_names::call(size, names, dtype, layout, device, pin_memory); + } +} + +// aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::rand_generator_with_names::call(c10::fromIntArrayRefSlow(size), generator, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor rand(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::rand_generator_with_names::call(c10::fromIntArrayRefSlow(size), generator, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand(at::IntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_generator_with_names::call(c10::fromIntArrayRefSlow(size), generator, names, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor rand(at::IntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_generator_with_names::call(c10::fromIntArrayRefSlow(size), generator, names, dtype, layout, device, pin_memory); + } +} + +// aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand_symint(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::rand_generator_with_names::call(size, generator, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor rand(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::rand_generator_with_names::call(size, generator, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand_symint(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_generator_with_names::call(size, generator, names, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor rand(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_generator_with_names::call(size, generator, names, dtype, layout, device, pin_memory); + } +} + +// aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::rand::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor rand(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::rand::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor rand(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand_symint(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::rand::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor rand(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::rand::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand::call(size, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor rand(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand::call(size, dtype, layout, device, pin_memory); + } +} + +// aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand(at::IntArrayRef size, ::std::optional generator, at::TensorOptions options={}) { + return at::_ops::rand_generator::call(c10::fromIntArrayRefSlow(size), generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor rand(at::IntArrayRef size, ::std::optional generator, at::TensorOptions options={}) { + return at::_ops::rand_generator::call(c10::fromIntArrayRefSlow(size), generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand(at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_generator::call(c10::fromIntArrayRefSlow(size), generator, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor rand(at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_generator::call(c10::fromIntArrayRefSlow(size), generator, dtype, layout, device, pin_memory); + } +} + +// aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand_symint(c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options={}) { + return at::_ops::rand_generator::call(size, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor rand(c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options={}) { + return at::_ops::rand_generator::call(size, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor rand_symint(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_generator::call(size, generator, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor rand(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::rand_generator::call(size, generator, dtype, layout, device, pin_memory); + } +} + +// aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::rand_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::rand_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::rand_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & rand_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::rand_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::rand_out::call(size, out); +} +namespace symint { + template >> + at::Tensor & rand_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::rand_out::call(size, out); + } +} + +// aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::rand_out::call(size, out); +} +namespace symint { + template >> + at::Tensor & rand_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::rand_out::call(size, out); + } +} + +// aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator) { + return at::_ops::rand_generator_out::call(c10::fromIntArrayRefSlow(size), generator, out); +} +namespace symint { + template >> + at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator) { + return at::_ops::rand_generator_out::call(c10::fromIntArrayRefSlow(size), generator, out); + } +} + +// aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_outf(at::IntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::rand_generator_out::call(c10::fromIntArrayRefSlow(size), generator, out); +} +namespace symint { + template >> + at::Tensor & rand_outf(at::IntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::rand_generator_out::call(c10::fromIntArrayRefSlow(size), generator, out); + } +} + +// aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator) { + return at::_ops::rand_generator_out::call(size, generator, out); +} +namespace symint { + template >> + at::Tensor & rand_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator) { + return at::_ops::rand_generator_out::call(size, generator, out); + } +} + +// aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::rand_generator_out::call(size, generator, out); +} +namespace symint { + template >> + at::Tensor & rand_outf(c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::rand_generator_out::call(size, generator, out); + } +} + +// aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, ::std::optional names) { + return at::_ops::rand_names_out::call(c10::fromIntArrayRefSlow(size), names, out); +} +namespace symint { + template >> + at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, ::std::optional names) { + return at::_ops::rand_names_out::call(c10::fromIntArrayRefSlow(size), names, out); + } +} + +// aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_outf(at::IntArrayRef size, ::std::optional names, at::Tensor & out) { + return at::_ops::rand_names_out::call(c10::fromIntArrayRefSlow(size), names, out); +} +namespace symint { + template >> + at::Tensor & rand_outf(at::IntArrayRef size, ::std::optional names, at::Tensor & out) { + return at::_ops::rand_names_out::call(c10::fromIntArrayRefSlow(size), names, out); + } +} + +// aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional names) { + return at::_ops::rand_names_out::call(size, names, out); +} +namespace symint { + template >> + at::Tensor & rand_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional names) { + return at::_ops::rand_names_out::call(size, names, out); + } +} + +// aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, ::std::optional names, at::Tensor & out) { + return at::_ops::rand_names_out::call(size, names, out); +} +namespace symint { + template >> + at::Tensor & rand_outf(c10::SymIntArrayRef size, ::std::optional names, at::Tensor & out) { + return at::_ops::rand_names_out::call(size, names, out); + } +} + +// aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator, ::std::optional names) { + return at::_ops::rand_generator_with_names_out::call(c10::fromIntArrayRefSlow(size), generator, names, out); +} +namespace symint { + template >> + at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator, ::std::optional names) { + return at::_ops::rand_generator_with_names_out::call(c10::fromIntArrayRefSlow(size), generator, names, out); + } +} + +// aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_outf(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out) { + return at::_ops::rand_generator_with_names_out::call(c10::fromIntArrayRefSlow(size), generator, names, out); +} +namespace symint { + template >> + at::Tensor & rand_outf(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out) { + return at::_ops::rand_generator_with_names_out::call(c10::fromIntArrayRefSlow(size), generator, names, out); + } +} + +// aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names) { + return at::_ops::rand_generator_with_names_out::call(size, generator, names, out); +} +namespace symint { + template >> + at::Tensor & rand_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names) { + return at::_ops::rand_generator_with_names_out::call(size, generator, names, out); + } +} + +// aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out) { + return at::_ops::rand_generator_with_names_out::call(size, generator, names, out); +} +namespace symint { + template >> + at::Tensor & rand_outf(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out) { + return at::_ops::rand_generator_with_names_out::call(size, generator, names, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/randn_like_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/randn_like_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7f8c31c8bfb8a57ed15bc5aff2127bc4472b3879 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/randn_like_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor randn_like(const at::Tensor & self, at::TensorOptions options={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor randn_like(const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +TORCH_API at::Tensor & randn_like_out(at::Tensor & out, const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randn_like_outf(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/random_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/random_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..464eb3d20097e283c59e0c3a6e509fa79a4f0120 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/random_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & random_(at::Tensor & self, int64_t from, ::std::optional to, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & random_(at::Tensor & self, int64_t to, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & random_(at::Tensor & self, ::std::optional generator=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/range_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/range_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..77e98257def78cb0657b1ae6ede7e8c08b0a3c5c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/range_meta_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 meta { + +TORCH_API at::Tensor & range_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step); +TORCH_API at::Tensor & range_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..79d8909f413418dca188ec6089c4ad3221f0dc58 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor reflection_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad1d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); +TORCH_API at::Tensor & reflection_pad1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad1d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c255d498e537d3f927cd80307552b903c9301327 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad1d_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 reflection_pad1d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::reflection_pad1d_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); +}; + +struct TORCH_API reflection_pad1d_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::reflection_pad1d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "reflection_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d.h new file mode 100644 index 0000000000000000000000000000000000000000..b578e84414e69157edc6f6b4b7d45d72cefe5495 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d.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::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & reflection_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::reflection_pad2d_out::call(self, c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template >> + at::Tensor & reflection_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::reflection_pad2d_out::call(self, c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & reflection_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::reflection_pad2d_out::call(self, c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template >> + at::Tensor & reflection_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::reflection_pad2d_out::call(self, c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & reflection_pad2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::reflection_pad2d_out::call(self, padding, out); +} +namespace symint { + template >> + at::Tensor & reflection_pad2d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::reflection_pad2d_out::call(self, padding, out); + } +} + +// aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & reflection_pad2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::reflection_pad2d_out::call(self, padding, out); +} +namespace symint { + template >> + at::Tensor & reflection_pad2d_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::reflection_pad2d_out::call(self, padding, out); + } +} + +// aten::reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor +inline at::Tensor reflection_pad2d(const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::reflection_pad2d::call(self, c10::fromIntArrayRefSlow(padding)); +} +namespace symint { + template >> + at::Tensor reflection_pad2d(const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::reflection_pad2d::call(self, c10::fromIntArrayRefSlow(padding)); + } +} + +// aten::reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor +inline at::Tensor reflection_pad2d_symint(const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::reflection_pad2d::call(self, padding); +} +namespace symint { + template >> + at::Tensor reflection_pad2d(const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::reflection_pad2d::call(self, padding); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d5f582290f17b3f46e8512155c8aba81dedf533d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d_backward_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor reflection_pad2d_backward_cpu(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad2d_backward_out_cpu(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); +TORCH_API at::Tensor reflection_pad2d_backward_cuda(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad2d_backward_out_cuda(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/remainder_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/remainder_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7f2a43e8230cdaf3c79ae77207f60732bb46832a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/remainder_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 remainder(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & remainder_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9928d82de8b044338a101c79c33a94b5cd66bc31 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_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 replication_pad3d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::replication_pad3d_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); +}; + +struct TORCH_API replication_pad3d_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::replication_pad3d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_as.h b/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_as.h new file mode 100644 index 0000000000000000000000000000000000000000..0739ddd99303b8de1472ffbefab96f8d44051098 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_as.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/resize_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/resize_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..492b686a499c28f5d7e0a8e8ab8712159f08e546 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/resize_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API const at::Tensor & resize_(const at::Tensor & self, at::IntArrayRef size, ::std::optional memory_format=::std::nullopt); +TORCH_API const at::Tensor & resize__symint(const at::Tensor & self, c10::SymIntArrayRef size, ::std::optional memory_format=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_tanh_cell.h b/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_tanh_cell.h new file mode 100644 index 0000000000000000000000000000000000000000..bd090f10e27db9d498d520721f8fc1ca11f1ea53 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_tanh_cell.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::rnn_tanh_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor +inline at::Tensor rnn_tanh_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional & b_ih={}, const ::std::optional & b_hh={}) { + return at::_ops::rnn_tanh_cell::call(input, hx, w_ih, w_hh, b_ih, b_hh); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/round_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/round_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..ba5774eed6f55bcb32fdbb86242ca978e9d03f26 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/round_meta.h @@ -0,0 +1,32 @@ +#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_round : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; +struct TORCH_API structured_round_decimals : public TensorIteratorBase { + + + void meta(const at::Tensor & self, int64_t decimals); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c8ca18bbb3faa59670c89914618871d56e53b668 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor rsqrt(const at::Tensor & self); +TORCH_API at::Tensor & rsqrt_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & rsqrt_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & rsqrt_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/rsub.h b/lib/python3.12/site-packages/torch/include/ATen/ops/rsub.h new file mode 100644 index 0000000000000000000000000000000000000000..ed387075fa7ef7f0ff75e9379888c34b3ae673c7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/rsub.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::rsub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor +inline at::Tensor rsub(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1) { + return at::_ops::rsub_Tensor::call(self, other, alpha); +} + +// aten::rsub.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor +inline at::Tensor rsub(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1) { + return at::_ops::rsub_Scalar::call(self, other, alpha); +} + +// aten::rsub.Tensor_out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rsub_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1) { + return at::_ops::rsub_Tensor_out::call(self, other, alpha, out); +} +// aten::rsub.Tensor_out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rsub_outf(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out) { + return at::_ops::rsub_Tensor_out::call(self, other, alpha, out); +} + +// aten::rsub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rsub_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1) { + return at::_ops::rsub_Scalar_out::call(self, other, alpha, out); +} +// aten::rsub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rsub_outf(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out) { + return at::_ops::rsub_Scalar_out::call(self, other, alpha, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/scaled_dot_product_attention_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/scaled_dot_product_attention_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3b2d9c79905f3af85633acf05fdaddbea83faf3a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/scaled_dot_product_attention_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 scaled_dot_product_attention { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, double, bool, ::std::optional, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::scaled_dot_product_attention"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, *, float? scale=None, bool enable_gqa=False) -> Tensor"; + static at::Tensor call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask, double dropout_p, bool is_causal, ::std::optional scale, bool enable_gqa); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask, double dropout_p, bool is_causal, ::std::optional scale, bool enable_gqa); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9294ba854b56891a7c8e1361eca34bdc238896ee --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/scatter_meta_dispatch.h @@ -0,0 +1,38 @@ +#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 scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/searchsorted.h b/lib/python3.12/site-packages/torch/include/ATen/ops/searchsorted.h new file mode 100644 index 0000000000000000000000000000000000000000..0b474e86556afefd33ba04babeabc81ba8e60087 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/searchsorted.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::searchsorted.Tensor(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor +inline at::Tensor searchsorted(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}) { + return at::_ops::searchsorted_Tensor::call(sorted_sequence, self, out_int32, right, side, sorter); +} + +// aten::searchsorted.Tensor_out(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & searchsorted_out(at::Tensor & out, const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}) { + return at::_ops::searchsorted_Tensor_out::call(sorted_sequence, self, out_int32, right, side, sorter, out); +} +// aten::searchsorted.Tensor_out(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & searchsorted_outf(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter, at::Tensor & out) { + return at::_ops::searchsorted_Tensor_out::call(sorted_sequence, self, out_int32, right, side, sorter, out); +} + +// aten::searchsorted.Scalar(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor +inline at::Tensor searchsorted(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}) { + return at::_ops::searchsorted_Scalar::call(sorted_sequence, self, out_int32, right, side, sorter); +} + +// aten::searchsorted.Scalar_out(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & searchsorted_out(at::Tensor & out, const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}) { + return at::_ops::searchsorted_Scalar_out::call(sorted_sequence, self, out_int32, right, side, sorter, out); +} +// aten::searchsorted.Scalar_out(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & searchsorted_outf(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter, at::Tensor & out) { + return at::_ops::searchsorted_Scalar_out::call(sorted_sequence, self, out_int32, right, side, sorter, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/segment_reduce_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/segment_reduce_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ba8fc7217d5276d9e17416d17b0b6cf43b14b344 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/segment_reduce_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 segment_reduce(const at::Tensor & data, c10::string_view reduce, const ::std::optional & lengths={}, const ::std::optional & indices={}, const ::std::optional & offsets={}, int64_t axis=0, bool unsafe=false, const ::std::optional & initial=::std::nullopt); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sgn.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sgn.h new file mode 100644 index 0000000000000000000000000000000000000000..41b6b363903860e9525a392987b7d5b67fb0c610 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sgn.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::sgn(Tensor self) -> Tensor +inline at::Tensor sgn(const at::Tensor & self) { + return at::_ops::sgn::call(self); +} + +// aten::sgn.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sgn_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::sgn_out::call(self, out); +} +// aten::sgn.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sgn_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::sgn_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c2624683d77159ad9c00707f96f3b53a6f18bdd2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_sigmoid_out : public at::meta::structured_sigmoid { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor mkldnn_sigmoid(const at::Tensor & self); +TORCH_API at::Tensor & mkldnn_sigmoid_(at::Tensor & self); +TORCH_API at::Tensor sigmoid_quantized_cpu(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1c754fdf4d392204fd3b5da147ada2407b2d2846 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/signbit_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 signbit(const at::Tensor & self); +TORCH_API at::Tensor & signbit_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & signbit_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4add03076f24177f3151d7d7b1b59f7d1dbbe9c1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sinc_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor sinc(const at::Tensor & self); +TORCH_API at::Tensor & sinc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sinc_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinc_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sinh_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sinh_native.h new file mode 100644 index 0000000000000000000000000000000000000000..023577cb69bbe1c962addcad04632b479432e579 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sinh_native.h @@ -0,0 +1,29 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_sinh_out : public at::meta::structured_sinh { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor sinh_sparse(const at::Tensor & self); +TORCH_API at::Tensor & sinh_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinh_sparse_(at::Tensor & self); +TORCH_API at::Tensor sinh_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & sinh_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinh_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/size.h b/lib/python3.12/site-packages/torch/include/ATen/ops/size.h new file mode 100644 index 0000000000000000000000000000000000000000..6916fa2d8c4ad6a4ef5dcd0c8c10142ddf807b4f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/size.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::size.int(Tensor self, int dim) -> int +inline int64_t __dispatch_size(const at::Tensor & self, int64_t dim) { + return at::_ops::size_int::call(self, dim); +} + +// aten::size.Dimname(Tensor self, Dimname dim) -> int +inline int64_t size(const at::Tensor & self, at::Dimname dim) { + return at::_ops::size_Dimname::call(self, dim); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/size_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/size_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bef4eb0c4fdc79f221d2f2491cba6f2004415f49 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/size_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 int64_t size(const at::Tensor & self, int64_t dim); +TORCH_API int64_t size(const at::Tensor & self, at::Dimname dim); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/slice_copy_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/slice_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ac4b1a9bed6ff5fbfaa0aa467859a446b8db3da --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/slice_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & slice_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1); +TORCH_API at::Tensor & slice_copy_outf(const at::Tensor & self, int64_t dim, ::std::optional start, ::std::optional end, int64_t step, at::Tensor & out); +TORCH_API at::Tensor & slice_copy_symint_out(at::Tensor & out, const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=1); +TORCH_API at::Tensor & slice_copy_symint_outf(const at::Tensor & self, int64_t dim, ::std::optional start, ::std::optional end, c10::SymInt step, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dc475d4a216c7b9382077a77f3fdd1ef3018a3c8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/smooth_l1_loss_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor smooth_l1_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double beta=1.0); +TORCH_API at::Tensor & smooth_l1_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double beta=1.0); +TORCH_API at::Tensor & smooth_l1_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_bsr_tensor_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_bsr_tensor_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bfd0d3a1a72e0382d3838d546fda152a7eff29dd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_bsr_tensor_compositeimplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor sparse_bsr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options); +TORCH_API at::Tensor sparse_bsr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor sparse_bsr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::TensorOptions options); +TORCH_API at::Tensor sparse_bsr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_dim_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_dim_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e8d13415e4ad32aab25f9381af8c20a37320cf08 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_dim_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API int64_t sparse_dim(const at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_mask_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_mask_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a226610f30f62099bccd472e305b9c9734ff693a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_mask_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 & sparse_mask_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask); +TORCH_API at::Tensor & sparse_mask_outf(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f36e9ebf0618798a82c86059df9eb3480babf4fe --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_resize_and_clear_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 sparse_resize_and_clear(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); +TORCH_API const at::Tensor & sparse_resize_and_clear_out(const at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim); +TORCH_API const at::Tensor & sparse_resize_and_clear_outf(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim, const at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_airy_ai_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_airy_ai_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..52488422185aa6586a07a58e7fb1b82be3644221 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_airy_ai_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_airy_ai : public TensorIteratorBase { + + + void meta(const at::Tensor & x); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y1_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y1_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5d3dfa23d14597b21155b15f3f962addd085d9df --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_y1_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 special_bessel_y1(const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammainc_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammainc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..420827d6053e656f40c3a0d4d8c9f61aa9f9feb8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_gammainc_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 special_gammainc(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & special_gammainc_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e.h new file mode 100644 index 0000000000000000000000000000000000000000..ac9970207d431ceb9d1e7bd7f593bd76ddd6e465 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_i1e(Tensor self) -> Tensor +inline at::Tensor special_i1e(const at::Tensor & self) { + return at::_ops::special_i1e::call(self); +} + +// aten::special_i1e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_i1e_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_i1e_out::call(self, out); +} +// aten::special_i1e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_i1e_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_i1e_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..36049fb8c569d819488536ece367000a01480527 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_i1e(const at::Tensor & self); +TORCH_API at::Tensor & special_i1e_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_i1e_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..045b0a2377bc492ba1f95602afae88b003ad7aba --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_i1e_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_i1e : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..37eb5d53d7c05ed26a683676d6fe6aa4be741937 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_log_ndtr(const at::Tensor & self); +TORCH_API at::Tensor & special_log_ndtr_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_log_ndtr_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a05f392c9967892004f4725744b25d2f578aa79d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_log_ndtr(const at::Tensor & self); +TORCH_API at::Tensor & special_log_ndtr_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_log_ndtr_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_softmax_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_softmax_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..489ce4cd366b6236c64dfe5ab961b68bb11789be --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_softmax_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor special_log_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_native.h new file mode 100644 index 0000000000000000000000000000000000000000..16222ac056338af1da21074f85d2f65de6e2474b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_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_special_modified_bessel_i0_out : public at::meta::structured_special_modified_bessel_i0 { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..81b17f043ecac348a5cd16b177bb0070ea18eb8b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_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 special_modified_bessel_i0 { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_modified_bessel_i0"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_modified_bessel_i0(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 special_modified_bessel_i0_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 const char* name = "aten::special_modified_bessel_i0"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_modified_bessel_i0.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/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k0.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k0.h new file mode 100644 index 0000000000000000000000000000000000000000..b5828f057e1c24601aa59d9f22dbc25bfadff391 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k0.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_modified_bessel_k0(Tensor self) -> Tensor +inline at::Tensor special_modified_bessel_k0(const at::Tensor & self) { + return at::_ops::special_modified_bessel_k0::call(self); +} + +// aten::special_modified_bessel_k0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_modified_bessel_k0_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_modified_bessel_k0_out::call(self, out); +} +// aten::special_modified_bessel_k0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_modified_bessel_k0_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_modified_bessel_k0_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k1_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k1_native.h new file mode 100644 index 0000000000000000000000000000000000000000..811eae8371ba4759234811348af5edd3f4ecf019 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k1_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_special_modified_bessel_k1_out : public at::meta::structured_special_modified_bessel_k1 { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k1_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k1_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..406004fea05821d230b477c3ea40cf0ac02be05d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_k1_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 special_modified_bessel_k1 { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_modified_bessel_k1"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_modified_bessel_k1(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 special_modified_bessel_k1_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 const char* name = "aten::special_modified_bessel_k1"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_modified_bessel_k1.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/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..658d8fe795ab7d4315aa0bc0033cc3e6bf3798f1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_t(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_t(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e8ebbc1e66ecf2b94b3af21df2f9021c83311fd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_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 special_shifted_chebyshev_polynomial_t(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3b4087098a823476de3503975f139f50c378f83d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_u_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_u(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_u_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_u_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0bc3f407efcf69673f28ccddaea2508630c41c11 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_v_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_shifted_chebyshev_polynomial_v { + 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 const char* name = "aten::special_shifted_chebyshev_polynomial_v"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_v(Tensor x, Tensor n) -> Tensor"; + static at::Tensor call(const at::Tensor & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_v_x_scalar { + using schema = at::Tensor (const at::Scalar &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_v"; + static constexpr const char* overload_name = "x_scalar"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_v.x_scalar(Scalar x, Tensor n) -> Tensor"; + static at::Tensor call(const at::Scalar & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_v_n_scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_v"; + static constexpr const char* overload_name = "n_scalar"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_v.n_scalar(Tensor x, Scalar n) -> Tensor"; + static at::Tensor call(const at::Tensor & x, const at::Scalar & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_v_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 const char* name = "aten::special_shifted_chebyshev_polynomial_v"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_v.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_v_x_scalar_out { + using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_v"; + static constexpr const char* overload_name = "x_scalar_out"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_v.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_v_n_scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_shifted_chebyshev_polynomial_v"; + static constexpr const char* overload_name = "n_scalar_out"; + static constexpr const char* schema_str = "special_shifted_chebyshev_polynomial_v.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_softmax.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_softmax.h new file mode 100644 index 0000000000000000000000000000000000000000..b7432b3c364c4f78ba2a13aec47b671b1510526c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_softmax.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::special_softmax(Tensor self, int dim, ScalarType? dtype=None) -> Tensor +inline at::Tensor special_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::special_softmax::call(self, dim, dtype); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_softmax_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_softmax_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e0e0ad73a6b3d85e103fc7089b8caec3e0c1ba6c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_softmax_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 special_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_native.h new file mode 100644 index 0000000000000000000000000000000000000000..59afb3c010e4c88649765fab454f1d8776f82e0a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/split_with_sizes_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector split_with_sizes(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0); +TORCH_API ::std::vector split_with_sizes_nested(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt.h new file mode 100644 index 0000000000000000000000000000000000000000..432568ef4f494f6ad132e4bafbfbea43c6c5bc28 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt.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::sqrt(Tensor self) -> Tensor +inline at::Tensor sqrt(const at::Tensor & self) { + return at::_ops::sqrt::call(self); +} + +// aten::sqrt_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & sqrt_(at::Tensor & self) { + return at::_ops::sqrt_::call(self); +} + +// aten::sqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sqrt_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::sqrt_out::call(self, out); +} +// aten::sqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sqrt_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::sqrt_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sspaddmm_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sspaddmm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..04c4c6418496d52d6f15a6ed15b521c2701ec04c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sspaddmm_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor sspaddmm(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & _sspaddmm_out_only_sparse(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & _sspaddmm_out_only_sparse_cuda(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & _sspaddmm_out_cpu(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & _sspaddmm_out_cuda(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sub_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sub_native.h new file mode 100644 index 0000000000000000000000000000000000000000..577056bd84523b19e5621885928e12a59c170a33 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sub_native.h @@ -0,0 +1,31 @@ +#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_sub_out : public at::meta::structured_sub_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_sub_Tensor(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor sub_sparse(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & sub_out_sparse(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & sub_sparse_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor sub_zerotensor(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor sub(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & sub_Scalar_out(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & sub_(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sum_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sum_native.h new file mode 100644 index 0000000000000000000000000000000000000000..168e9d94eb7d26c80a1c18a25e77ec9d141d4a0a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sum_native.h @@ -0,0 +1,32 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +TORCH_API at::Tensor sum(const at::Tensor & self, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & sum_out(const at::Tensor & self, ::std::optional dtype, at::Tensor & out); +TORCH_API at::Tensor sum_coo(const at::Tensor & self, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor sum_csr(const at::Tensor & self, ::std::optional dtype=::std::nullopt); +struct TORCH_API structured_sum_out : public at::meta::structured_sum_dim_IntList { +void impl(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_sum_dim_CPU(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor sum_sparse_coo(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor sum_sparse_compressed(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor sum(const at::Tensor & self, at::DimnameList dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & sum_out(const at::Tensor & self, at::DimnameList dim, bool keepdim, ::std::optional dtype, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sum_to_size_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sum_to_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fe1a50bad0646c1b36a54ce2e4f630b32ab5deb9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sum_to_size_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 sum_to_size(const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor sum_to_size_symint(const at::Tensor & self, c10::SymIntArrayRef size); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/svd.h b/lib/python3.12/site-packages/torch/include/ATen/ops/svd.h new file mode 100644 index 0000000000000000000000000000000000000000..cd066913b1c40a2982afe7a5c60a41452e912512 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/svd.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::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) +inline ::std::tuple svd_out(at::Tensor & U, at::Tensor & S, at::Tensor & V, const at::Tensor & self, bool some=true, bool compute_uv=true) { + return at::_ops::svd_U::call(self, some, compute_uv, U, S, V); +} +// aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) +inline ::std::tuple svd_outf(const at::Tensor & self, bool some, bool compute_uv, at::Tensor & U, at::Tensor & S, at::Tensor & V) { + return at::_ops::svd_U::call(self, some, compute_uv, U, S, V); +} + +// aten::svd(Tensor self, bool some=True, bool compute_uv=True) -> (Tensor U, Tensor S, Tensor V) +inline ::std::tuple svd(const at::Tensor & self, bool some=true, bool compute_uv=true) { + return at::_ops::svd::call(self, some, compute_uv); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f28095cff8865335712fdbfcdd4c06dfc57e5543 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor swapdims(const at::Tensor & self, int64_t dim0, int64_t dim1); +TORCH_API at::Tensor & swapdims_(at::Tensor & self, int64_t dim0, int64_t dim1); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sym_stride_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sym_stride_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a2b672c3098e00cff077ec57b7797a743d458c91 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sym_stride_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sym_stride_int { + using schema = c10::SymInt (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::sym_stride"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "sym_stride.int(Tensor self, int dim) -> SymInt"; + static c10::SymInt call(const at::Tensor & self, int64_t dim); + static c10::SymInt redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/t_copy.h b/lib/python3.12/site-packages/torch/include/ATen/ops/t_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..e562aef2b818e8418664c6e06031a3f2f76acf46 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/t_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::t_copy(Tensor self) -> Tensor +inline at::Tensor t_copy(const at::Tensor & self) { + return at::_ops::t_copy::call(self); +} + +// aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & t_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::t_copy_out::call(self, out); +} +// aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & t_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::t_copy_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/thnn_conv2d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/thnn_conv2d.h new file mode 100644 index 0000000000000000000000000000000000000000..7dc681bc3ed1f02be3c68274c06eabbe2cae8065 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/thnn_conv2d.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::thnn_conv2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & thnn_conv2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0) { + return at::_ops::thnn_conv2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template >> + at::Tensor & thnn_conv2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0) { + return at::_ops::thnn_conv2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::thnn_conv2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & thnn_conv2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::thnn_conv2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template >> + at::Tensor & thnn_conv2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::thnn_conv2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::thnn_conv2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & thnn_conv2d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0)) { + return at::_ops::thnn_conv2d_out::call(self, weight, kernel_size, bias, stride, padding, out); +} +namespace symint { + template >> + at::Tensor & thnn_conv2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0)) { + return at::_ops::thnn_conv2d_out::call(self, weight, kernel_size, bias, stride, padding, out); + } +} + +// aten::thnn_conv2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & thnn_conv2d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::thnn_conv2d_out::call(self, weight, kernel_size, bias, stride, padding, out); +} +namespace symint { + template >> + at::Tensor & thnn_conv2d_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::thnn_conv2d_out::call(self, weight, kernel_size, bias, stride, padding, out); + } +} + +// aten::thnn_conv2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0) -> Tensor +inline at::Tensor thnn_conv2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0) { + return at::_ops::thnn_conv2d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding)); +} +namespace symint { + template >> + at::Tensor thnn_conv2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0) { + return at::_ops::thnn_conv2d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding)); + } +} + +// aten::thnn_conv2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0) -> Tensor +inline at::Tensor thnn_conv2d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0)) { + return at::_ops::thnn_conv2d::call(self, weight, kernel_size, bias, stride, padding); +} +namespace symint { + template >> + at::Tensor thnn_conv2d(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0)) { + return at::_ops::thnn_conv2d::call(self, weight, kernel_size, bias, stride, padding); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/to_dense_backward_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/to_dense_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..42448f7a26d87b603faae30cc23a54da014f21e0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/to_dense_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor to_dense_backward(const at::Tensor & grad, const at::Tensor & input, ::std::optional masked_grad=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/to_dense_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/to_dense_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7df4f394d49c76892999d84785404490f3a1e907 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/to_dense_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 to_dense(const at::Tensor & self, ::std::optional dtype=::std::nullopt, ::std::optional masked_grad=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csc.h b/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csc.h new file mode 100644 index 0000000000000000000000000000000000000000..ba185f299ceb066ca3e34958f32cc8f6363d5e56 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csc.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csc_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4d70f49333a0dbc3c0caadb0dbee43b8d2104e73 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_csc_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor to_sparse_csc(const at::Tensor & self, ::std::optional dense_dim=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ae45fb4d72460b100e16be3a71c8a0de830bcd13 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/to_sparse_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 to_sparse(const at::Tensor & self, int64_t sparse_dim); +TORCH_API at::Tensor to_sparse(const at::Tensor & self, ::std::optional layout=::std::nullopt, at::OptionalIntArrayRef blocksize=::std::nullopt, ::std::optional dense_dim=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/trace.h b/lib/python3.12/site-packages/torch/include/ATen/ops/trace.h new file mode 100644 index 0000000000000000000000000000000000000000..07ba52f86ead41ea07032dc0968b1cf649e30f36 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/trace.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::trace(Tensor self) -> Tensor +inline at::Tensor trace(const at::Tensor & self) { + return at::_ops::trace::call(self); +} + +// aten::trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & trace_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::trace_out::call(self, out); +} +// aten::trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & trace_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::trace_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/trapz_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/trapz_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9dc40b45cecc91a6bef3bc064a6c6ed7f482829d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/trapz_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 trapz(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1); +TORCH_API at::Tensor trapz(const at::Tensor & y, double dx=1, int64_t dim=-1); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_solve_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_solve_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f37d60a8886ec32e503da18afb0626dcbf9e2339 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_solve_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_triangular_solve : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/tril.h b/lib/python3.12/site-packages/torch/include/ATen/ops/tril.h new file mode 100644 index 0000000000000000000000000000000000000000..6d63fcb9febacd7c05f4a56c6b10e4df8ea4feec --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/tril.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::tril.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & tril_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0) { + return at::_ops::tril_out::call(self, diagonal, out); +} +// aten::tril.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & tril_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out) { + return at::_ops::tril_out::call(self, diagonal, out); +} + +// aten::tril(Tensor self, int diagonal=0) -> Tensor +inline at::Tensor tril(const at::Tensor & self, int64_t diagonal=0) { + return at::_ops::tril::call(self, diagonal); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/tril_indices_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/tril_indices_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..72827b1e7a2cc9c1c4d695035fb622f310f29cdf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/tril_indices_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 & tril_indices_out(at::Tensor & out, int64_t row, int64_t col, int64_t offset=0); +TORCH_API at::Tensor & tril_indices_outf(int64_t row, int64_t col, int64_t offset, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5086cc91f95039dfda0ea4f8a02db62176a33fee --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & triu_indices_out(int64_t row, int64_t col, int64_t offset, at::Tensor & out); +TORCH_API at::Tensor triu_indices_cpu(int64_t row, int64_t col, int64_t offset=0, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor triu_indices_cuda(int64_t row, int64_t col, int64_t offset=0, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_copy_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3c0668551664fab77506a4e89fcf45a8a55fecd6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_copy_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 void unbind_copy_int_out(const at::Tensor & self, int64_t dim, at::TensorList out); +TORCH_API ::std::vector unbind_copy_int(const at::Tensor & self, int64_t dim=0); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c5ce341fc81c5cdca9b837f6fb04ce5b204e30c0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/unbind_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 unbind_int { + using schema = ::std::vector (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::unbind"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "unbind.int(Tensor(a -> *) self, int dim=0) -> Tensor(a)[]"; + static ::std::vector call(const at::Tensor & self, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +struct TORCH_API unbind_Dimname { + using schema = ::std::vector (const at::Tensor &, at::Dimname); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::unbind"; + static constexpr const char* overload_name = "Dimname"; + static constexpr const char* schema_str = "unbind.Dimname(Tensor(a -> *) self, Dimname dim) -> Tensor(a)[]"; + static ::std::vector call(const at::Tensor & self, at::Dimname dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/uniform.h b/lib/python3.12/site-packages/torch/include/ATen/ops/uniform.h new file mode 100644 index 0000000000000000000000000000000000000000..2e4d020e693d8462a3a923f8ff74992b8c3efa2a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/uniform.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & uniform_out(at::Tensor & out, const at::Tensor & self, double from=0, double to=1, ::std::optional generator=::std::nullopt) { + return at::_ops::uniform_out::call(self, from, to, generator, out); +} +// aten::uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & uniform_outf(const at::Tensor & self, double from, double to, ::std::optional generator, at::Tensor & out) { + return at::_ops::uniform_out::call(self, from, to, generator, out); +} + +// aten::uniform(Tensor self, float from=0, float to=1, *, Generator? generator=None) -> Tensor +inline at::Tensor uniform(const at::Tensor & self, double from=0, double to=1, ::std::optional generator=::std::nullopt) { + return at::_ops::uniform::call(self, from, to, generator); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_chunk_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_chunk_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..59237640b52df89817c081764bb55de4d56b98ec --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/unsafe_chunk_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 unsafe_chunk { + using schema = ::std::vector (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::unsafe_chunk"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "unsafe_chunk(Tensor self, int chunks, int dim=0) -> Tensor[]"; + static ::std::vector call(const at::Tensor & self, int64_t chunks, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t chunks, int64_t dim); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..16da4dddacebefb525c6b5e397cb0c679348e2bc --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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 upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_bicubic2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b242af63eaae01fc3272a3eb66cc0acf5c85b532 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d_native.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +TORCH_API at::Tensor upsample_bicubic2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); +struct TORCH_API structured_upsample_bicubic2d_out_cpu : public at::meta::structured_upsample_bicubic2d { +void impl(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +struct TORCH_API structured_upsample_bicubic2d_out_cuda : public at::meta::structured_upsample_bicubic2d { +void impl(const at::Tensor & self, at::ArrayRef output_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b640a9cf261836ae173e26b47644e99447c6350c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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 upsample_bilinear2d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_bilinear2d_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +}; + +struct TORCH_API upsample_bilinear2d_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_bilinear2d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "upsample_bilinear2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d66a08147b49855c31afa9b5e6663dd80b11d2e2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_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 upsample_nearest2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_nearest2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_nearest2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8209f126762c372885d3c95520ed098f1c05e3fd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_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 upsample_nearest2d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_nearest2d_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "upsample_nearest2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +}; + +struct TORCH_API upsample_nearest2d_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_nearest2d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "upsample_nearest2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_h, ::std::optional scales_w); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..51416813354bd070c952bb3683971216044b6746 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors); +TORCH_API at::Tensor & upsample_nearest2d_outf(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest2d_symint_out(at::Tensor & out, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors); +TORCH_API at::Tensor & upsample_nearest2d_symint_outf(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0620718f04f000daabe0aaa8f92c279394c9d838 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_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 upsample_trilinear3d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_trilinear3d_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "upsample_trilinear3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +}; + +struct TORCH_API upsample_trilinear3d_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_trilinear3d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "upsample_trilinear3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/values_copy_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/values_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c27111f8c7dc8d214a2e52524a35953bae6defaf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/values_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor values_copy(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/var_mean_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/var_mean_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f730dfac0d0100a9ab16b7d7aa3ff2984051bbdc --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/var_mean_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API var_mean { + using schema = ::std::tuple (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::var_mean"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "var_mean(Tensor self, bool unbiased=True) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, bool unbiased); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool unbiased); +}; + +struct TORCH_API var_mean_dim { + using schema = ::std::tuple (const at::Tensor &, at::OptionalIntArrayRef, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::var_mean"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "var_mean.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim); +}; + +struct TORCH_API var_mean_correction { + using schema = ::std::tuple (const at::Tensor &, at::OptionalIntArrayRef, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::var_mean"; + static constexpr const char* overload_name = "correction"; + static constexpr const char* schema_str = "var_mean.correction(Tensor self, int[1]? dim=None, *, Scalar? correction=None, bool keepdim=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim); +}; + +struct TORCH_API var_mean_names_dim { + using schema = ::std::tuple (const at::Tensor &, at::DimnameList, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::var_mean"; + static constexpr const char* overload_name = "names_dim"; + static constexpr const char* schema_str = "var_mean.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim); +}; + +struct TORCH_API var_mean_correction_names { + using schema = ::std::tuple (const at::Tensor &, at::DimnameList, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::var_mean"; + static constexpr const char* overload_name = "correction_names"; + static constexpr const char* schema_str = "var_mean.correction_names(Tensor self, Dimname[1] dim, *, Scalar? correction=None, bool keepdim=False) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction, bool keepdim); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction, bool keepdim); +}; + +struct TORCH_API var_mean_correction_out { + using schema = ::std::tuple (const at::Tensor &, at::OptionalIntArrayRef, const ::std::optional &, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::var_mean"; + static constexpr const char* overload_name = "correction_out"; + static constexpr const char* schema_str = "var_mean.correction_out(Tensor self, int[1]? dim=None, *, Scalar? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))"; + static ::std::tuple call(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f73e2a9b5f1aede026ad7cd32488f728cd2eb2d6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/view_as_real_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor view_as_real(const at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4562eae9c6a573beab9094821321a898a6a6f7da --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/view_copy_ops.h @@ -0,0 +1,61 @@ +#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 view_copy { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::view_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "view_copy(Tensor self, SymInt[] size) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size); +}; + +struct TORCH_API view_copy_dtype { + using schema = at::Tensor (const at::Tensor &, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::view_copy"; + static constexpr const char* overload_name = "dtype"; + static constexpr const char* schema_str = "view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ScalarType dtype); +}; + +struct TORCH_API view_copy_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::view_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out); +}; + +struct TORCH_API view_copy_dtype_out { + using schema = at::Tensor & (const at::Tensor &, at::ScalarType, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::view_copy"; + static constexpr const char* overload_name = "dtype_out"; + static constexpr const char* schema_str = "view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::ScalarType dtype, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ScalarType dtype, at::Tensor & out); +}; + +}} // namespace at::_ops