diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..86bc5438283460e0e7a31bf96b75cae2f035b88a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_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_pool3d_out_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out); +TORCH_API at::Tensor adaptive_avg_pool3d_cpu(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor adaptive_avg_pool3d_cuda(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor adaptive_avg_pool3d_quantized_cpu(const at::Tensor & self, at::IntArrayRef output_size); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_aminmax_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_aminmax_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..993d09a14b3252cfb2c17e1577ef807b2c668353 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_aminmax_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple _aminmax(const at::Tensor & self); +TORCH_API ::std::tuple _aminmax(const at::Tensor & self, int64_t dim, bool keepdim=false); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_scalar.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_scalar.h new file mode 100644 index 0000000000000000000000000000000000000000..f6f86ffd46d76e6241e044191e528c1f25521851 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_assert_scalar.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::_assert_scalar(Scalar self, str assert_msg) -> () +inline void _assert_scalar(const at::Scalar & self, c10::string_view assert_msg) { + return at::_ops::_assert_scalar::call(self, assert_msg); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Double.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Double.h new file mode 100644 index 0000000000000000000000000000000000000000..8ee6bbdd8a46f1b7cad2257b6ef94c4d57ba1449 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cast_Double.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_Double(Tensor self, bool non_blocking=False) -> Tensor +inline at::Tensor _cast_Double(const at::Tensor & self, bool non_blocking=false) { + return at::_ops::_cast_Double::call(self, non_blocking); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..03d62945c79f248c6cdc8718eceb73cdf110ee38 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cdist_forward_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 & _cdist_forward_out(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode, at::Tensor & out); +TORCH_API at::Tensor _cdist_forward(const at::Tensor & x1, const at::Tensor & x2, double p, ::std::optional compute_mode); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cholesky_solve_helper_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cholesky_solve_helper_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc9099cb356e4911015355a8b6b7ed3dbe67e0b8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cholesky_solve_helper_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 _cholesky_solve_helper(const at::Tensor & self, const at::Tensor & A, bool upper); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesce_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesce_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f23343092e8e64779628025405e2b40b33b41f86 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesce_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 & _coalesce_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _coalesce_sparse_cpu(const at::Tensor & self); +TORCH_API at::Tensor _coalesce_sparse_cuda(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eddef49ceb921a59f26806a645dbc09e12237dc3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_coalesced_meta_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & _coalesced_(at::Tensor & self, bool coalesced); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_conj.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_conj.h new file mode 100644 index 0000000000000000000000000000000000000000..c28ff96b85fe2c100874d2d76896290e72485d8a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_conj.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::_conj(Tensor(a) self) -> Tensor(a) +inline at::Tensor _conj(const at::Tensor & self) { + return at::_ops::_conj::call(self); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9d92c548e3cdef8ddb0db51b3875236070c9a3c3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_conj_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 _conj(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_for_cpu_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_for_cpu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a3053421d6abad1f2ea5d57c470922bea94823e3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_convert_weight_to_int4pack_for_cpu_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 _convert_weight_to_int4pack_cpu(const at::Tensor & self, int64_t innerKTiles); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_double_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_double_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d666e1af4bf48c7ca062e8c196e367537635d4e7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_double_backward_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _convolution_double_backward(const ::std::optional & ggI, const ::std::optional & ggW, const ::std::optional & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..07263dab231b19e036b63f1e5b6367730e4578aa --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_convolution_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 _convolution(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32); +TORCH_API at::Tensor & _convolution_out_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, at::Tensor & out); +TORCH_API at::Tensor _convolution(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_compress_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_compress_native.h new file mode 100644 index 0000000000000000000000000000000000000000..45a1c2e4438dcbe1d2a14132c8e0ee99a35628e2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_compress_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 _cslt_compress(const at::Tensor & input); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm.h new file mode 100644 index 0000000000000000000000000000000000000000..4c9531cba68b8950b1ad9017404968416a961790 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm.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::_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 +inline at::Tensor _cslt_sparse_mm(const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias={}, const ::std::optional & alpha={}, ::std::optional out_dtype=::std::nullopt, bool transpose_result=false, int64_t alg_id=0, int64_t split_k=1, bool split_k_one_kernel=true) { + return at::_ops::_cslt_sparse_mm::call(compressed_A, dense_B, bias, alpha, out_dtype, transpose_result, alg_id, split_k, split_k_one_kernel); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search.h new file mode 100644 index 0000000000000000000000000000000000000000..311898b6a5f0601ebe6d0d688dda96724f138b34 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search.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::_cslt_sparse_mm_search(Tensor compressed_A, Tensor dense_B, Tensor? bias=None, Tensor? alpha=None, ScalarType? out_dtype=None, bool transpose_result=False) -> int +inline int64_t _cslt_sparse_mm_search(const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias={}, const ::std::optional & alpha={}, ::std::optional out_dtype=::std::nullopt, bool transpose_result=false) { + return at::_ops::_cslt_sparse_mm_search::call(compressed_A, dense_B, bias, alpha, out_dtype, transpose_result); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..13794a49fb9aeec975f9ff6a3a07d9f38355dc88 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_ctc_loss_backward_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); +TORCH_API at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d82246bf2894f7a4638ce7bd988f5c6e77f34704 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_cudnn_init_dropout_state_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 & _cudnn_init_dropout_state_out(at::Tensor & out, double dropout, bool train, int64_t dropout_seed); +TORCH_API at::Tensor & _cudnn_init_dropout_state_outf(double dropout, bool train, int64_t dropout_seed, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_dimI.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_dimI.h new file mode 100644 index 0000000000000000000000000000000000000000..debf7569d95bf4b9664c6fe1c65d65f08bb4230b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_dimI.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/_dimV.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_dimV.h new file mode 100644 index 0000000000000000000000000000000000000000..971eb450d8528637ee4a3199e5d2a56bd8a0454f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_dimV.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/_dim_arange_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_dim_arange_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..86b2129dd6925056bff05b06bb90e366b3ea5811 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_dim_arange_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 _dim_arange(const at::Tensor & like, int64_t dim); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_dirichlet_grad_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_dirichlet_grad_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9f05512971df68029c6819e0c7aa2063b1691882 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_dirichlet_grad_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 & _dirichlet_grad_out(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total, at::Tensor & out); +TORCH_API at::Tensor _dirichlet_grad_cpu(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); +TORCH_API at::Tensor _dirichlet_grad_cuda(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_efficient_attention_forward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_efficient_attention_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7522d8baa78c9b734fcd1b71a9d21ab89e8424f9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_efficient_attention_forward_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 _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp=false, ::std::optional scale=::std::nullopt, const ::std::optional & seqlen_k={}, ::std::optional window_size=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_efficient_attention_forward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_efficient_attention_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c8b83e78129f18bcf7b7dd2c3505b3cba5389377 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_efficient_attention_forward_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 _efficient_attention_forward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, ::std::optional, ::std::optional, double, int64_t, bool, ::std::optional, const ::std::optional &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_efficient_attention_forward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? bias, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, SymInt? max_seqlen_q, SymInt? max_seqlen_k, float dropout_p, int custom_mask_type, bool compute_log_sumexp=False, *, float? scale=None, Tensor? seqlen_k=None, int? window_size=None) -> (Tensor output, Tensor logsumexp, Tensor philox_seed, Tensor philox_offset, SymInt max_seqlen_batch_q, SymInt max_seqlen_batch_k)"; + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp, ::std::optional scale, const ::std::optional & seqlen_k, ::std::optional window_size); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & bias, const ::std::optional & cu_seqlens_q, const ::std::optional & cu_seqlens_k, ::std::optional max_seqlen_q, ::std::optional max_seqlen_k, double dropout_p, int64_t custom_mask_type, bool compute_log_sumexp, ::std::optional scale, const ::std::optional & seqlen_k, ::std::optional window_size); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_efficientzerotensor_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_efficientzerotensor_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..21527e2a892e49c756b3f77d94d9d17a6e36a5d9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_efficientzerotensor_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 _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, ::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/_embedding_bag.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag.h new file mode 100644 index 0000000000000000000000000000000000000000..6bebf4f4c875e2f97d78c438f4dba4aa3779117f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag.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::_embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1) -> (Tensor, Tensor, Tensor, Tensor) +inline ::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, int64_t padding_idx=-1) { + return at::_ops::_embedding_bag::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx); +} + +// aten::_embedding_bag.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple _embedding_bag_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, 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) { + return at::_ops::_embedding_bag_out::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx, out0, out1, out2, out3); +} +// aten::_embedding_bag.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) +inline ::std::tuple _embedding_bag_outf(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, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { + return at::_ops::_embedding_bag_out::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx, out0, out1, out2, out3); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ef5905ad4b059155f5acde936731182e397fcb6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_embedding_bag_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(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/_fft_c2c_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1fda6b7c22e95e0d8bacc041eb0336804f88e645 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fft_c2c_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fft_c2c { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_c2c"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward); +}; + +struct TORCH_API _fft_c2c_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_fft_c2c"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foobar_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foobar_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cc90a22df20302e07b540d5a0561b4a5aa3c8c6a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foobar_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 _foobar(const at::Tensor & self, bool arg1=true, bool arg2=true, bool arg3=true); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_acos_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_acos_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4d04807b6c6720a46234e2e2da8c965fd79a6acd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_acos_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::vector foreach_tensor_acos_slow(at::TensorList self); +TORCH_API void _foreach_acos_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_acos_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_acos_cuda(at::TensorList self); +TORCH_API void foreach_tensor_acos_cuda_(at::TensorList self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcdiv_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcdiv_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f8c313caf0df2af155ab3a31a2e1914efd4cedb5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_addcdiv_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_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +TORCH_API void _foreach_addcdiv_(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_atan.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_atan.h new file mode 100644 index 0000000000000000000000000000000000000000..34e9132247e0864a678d161fab633a458b0d4b0e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_atan.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_atan(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_atan(at::TensorList self) { + return at::_ops::_foreach_atan::call(self); +} + +// aten::_foreach_atan_(Tensor(a!)[] self) -> () +inline void _foreach_atan_(at::TensorList self) { + return at::_ops::_foreach_atan_::call(self); +} + +// aten::_foreach_atan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_atan_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_atan_out::call(self, out); +} +// aten::_foreach_atan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_atan_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_atan_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_ceil_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_ceil_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5ceff068c8441d56e4b97894a1f377b343dcf644 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_ceil_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_ceil(at::TensorList self); +TORCH_API void _foreach_ceil_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_ceil_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_ceil_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_max_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_max_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a542787756d1669e5a33bd5c3e8d5f94c72f7ad3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_clamp_max_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_clamp_max_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_clamp_max"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_clamp_max__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_clamp_max_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_clamp_max_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_clamp_max"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_clamp_max__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_clamp_max_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> ()"; + static void call(at::TensorList self, at::TensorList other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_clamp_max_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_clamp_max"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_clamp_max__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_clamp_max_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_clamp_max_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_clamp_max"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_clamp_max_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_clamp_max"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out); +}; + +struct TORCH_API _foreach_clamp_max_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_clamp_max"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cos_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cos_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4181f0938a687c10e57ec3df94cea2303a952389 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_cos_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_cos(at::TensorList self); +TORCH_API void _foreach_cos_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_cos_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_cos_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erfc_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erfc_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..465ad846dc588c3e1a823e33fbbdc4f5f18391cb --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erfc_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_erfc(at::TensorList self); +TORCH_API void _foreach_erfc_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_erfc_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_erfc_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erfc_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erfc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..48421cf75a35f576bcc5e49f9e7f3846e75647c6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_erfc_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_erfc { + 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_erfc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_erfc(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_erfc_ { + 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_erfc_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_erfc_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_erfc_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_erfc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_erfc.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_floor_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_floor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ff3ee952224c747b70a22d6aa1422d6b364a8840 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_floor_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_floor { + 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_floor"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_floor(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_floor_ { + 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_floor_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_floor_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_floor_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_floor"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_floor.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_lerp_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_lerp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3e29fa4b2abf85e76db1b36c2dcbd0914a13a27f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_lerp_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_lerp_List { + using schema = ::std::vector (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_lerp"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensors1, at::TensorList weights); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights); +}; + +struct TORCH_API _foreach_lerp__List { + 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_lerp_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, at::TensorList weights); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights); +}; + +struct TORCH_API _foreach_lerp_Scalar { + using schema = ::std::vector (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_lerp"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +}; + +struct TORCH_API _foreach_lerp__Scalar { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_lerp_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight); +}; + +struct TORCH_API _foreach_lerp_ScalarList { + using schema = ::std::vector (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_lerp"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_lerp.ScalarList(Tensor[] self, Tensor[] tensors1, Scalar[] weight) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +}; + +struct TORCH_API _foreach_lerp__ScalarList { + using schema = void (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_lerp_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_lerp_.ScalarList(Tensor(a!)[] self, Tensor[] tensors1, Scalar[] weight) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::ArrayRef weight); +}; + +struct TORCH_API _foreach_lerp_List_out { + using schema = void (at::TensorList, 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_lerp"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out); +}; + +struct TORCH_API _foreach_lerp_Scalar_out { + using schema = void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_lerp"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out); +}; + +struct TORCH_API _foreach_lerp_ScalarList_out { + using schema = void (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_lerp"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_lerp.ScalarList_out(Tensor[] self, Tensor[] tensors1, Scalar[] weight, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList tensors1, at::ArrayRef weight, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::ArrayRef weight, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_minimum_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_minimum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7722edfdd3ba5d0a2a8ff6a67e5024391a637822 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_minimum_ops.h @@ -0,0 +1,116 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_minimum_Scalar { + using schema = ::std::vector (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_minimum"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]"; + static ::std::vector call(at::TensorList self, const at::Scalar & scalar); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_minimum__Scalar { + using schema = void (at::TensorList, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_minimum_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar); +}; + +struct TORCH_API _foreach_minimum_List { + using schema = ::std::vector (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_minimum"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::TensorList other); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_minimum__List { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_minimum_"; + static constexpr const char* overload_name = "List"; + static constexpr const char* schema_str = "_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> ()"; + static void call(at::TensorList self, at::TensorList other); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other); +}; + +struct TORCH_API _foreach_minimum_ScalarList { + using schema = ::std::vector (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_minimum"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]"; + static ::std::vector call(at::TensorList self, at::ArrayRef scalars); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_minimum__ScalarList { + using schema = void (at::TensorList, at::ArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_minimum_"; + static constexpr const char* overload_name = "ScalarList"; + static constexpr const char* schema_str = "_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars); +}; + +struct TORCH_API _foreach_minimum_Scalar_out { + using schema = void (at::TensorList, const at::Scalar &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_minimum"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, const at::Scalar & scalar, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out); +}; + +struct TORCH_API _foreach_minimum_List_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_minimum"; + static constexpr const char* overload_name = "List_out"; + static constexpr const char* schema_str = "_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::TensorList other, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out); +}; + +struct TORCH_API _foreach_minimum_ScalarList_out { + using schema = void (at::TensorList, at::ArrayRef, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_foreach_minimum"; + static constexpr const char* overload_name = "ScalarList_out"; + static constexpr const char* schema_str = "_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()"; + static void call(at::TensorList self, at::ArrayRef scalars, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef scalars, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_neg.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_neg.h new file mode 100644 index 0000000000000000000000000000000000000000..34d29a89929d0ca0721302376ba0ee5811d288c8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_neg.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_neg(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_neg(at::TensorList self) { + return at::_ops::_foreach_neg::call(self); +} + +// aten::_foreach_neg_(Tensor(a!)[] self) -> () +inline void _foreach_neg_(at::TensorList self) { + return at::_ops::_foreach_neg_::call(self); +} + +// aten::_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_neg_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_neg_out::call(self, out); +} +// aten::_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_neg_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_neg_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_native.h new file mode 100644 index 0000000000000000000000000000000000000000..93e4ba5d3fdf0e59d4096298a70e3bbfcc82d6ca --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_round_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::vector foreach_tensor_round_slow(at::TensorList self); +TORCH_API void _foreach_round_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_round_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_round_cuda(at::TensorList self); +TORCH_API void foreach_tensor_round_cuda_(at::TensorList self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sin_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sin_native.h new file mode 100644 index 0000000000000000000000000000000000000000..64aa524977977f634031e42ee22f0bf11c637d78 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sin_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::vector foreach_tensor_sin_slow(at::TensorList self); +TORCH_API void _foreach_sin_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_sin_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_sin_cuda(at::TensorList self); +TORCH_API void foreach_tensor_sin_cuda_(at::TensorList self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sin_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sin_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1713dae7670e53a99d2dde0271ab3ea8801936b6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_sin_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_sin { + 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_sin"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sin(Tensor[] self) -> Tensor[]"; + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sin_ { + 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_sin_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_foreach_sin_(Tensor(a!)[] self) -> ()"; + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sin_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_sin"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_foreach_sin.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_trunc_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_trunc_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..985f9d6c80a00456aed5099b442fd74366e79767 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_foreach_trunc_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_trunc(at::TensorList self); +TORCH_API void _foreach_trunc_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_trunc_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_trunc_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_assert_async_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_assert_async_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2046afc81a532dc0345cee165411ff7a5000181c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_functional_assert_async_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 _functional_assert_async_msg_cpu(const at::Tensor & self, c10::string_view assert_msg, const at::Tensor & dep_token); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..86e4ec3919ec2e7079b399cf210378daa19acb05 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_adagrad_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<::std::vector,::std::vector,::std::vector,::std::vector> _fused_adagrad(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_out(at::TensorList out, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_adagrad_outf(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sgd_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sgd_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0aa0aca3e820e99d792e8d8e49fc9fe417c700f9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fused_sgd_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 void _fused_sgd_(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, double lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); +TORCH_API void _fused_sgd_(at::TensorList self, at::TensorList grads, at::TensorList momentum_buffer_list, double weight_decay, double momentum, const at::Tensor & lr, double dampening, bool nesterov, bool maximize, bool is_first_step, const ::std::optional & grad_scale={}, const ::std::optional & found_inf={}); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..837cbdb157ace79160d6103c1730e8fffb7dbaa7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_fw_primal_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _fw_primal_copy(const at::Tensor & self, int64_t level); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_gather_sparse_backward_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_gather_sparse_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..432ed1ae5599fd1890ec139ee8e5a3960da38781 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_gather_sparse_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 _gather_sparse_backward(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & grad); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e20cd6440af2053952a19446ae85b6e20617d887 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_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 _grid_sampler_2d_cpu_fallback { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_grid_sampler_2d_cpu_fallback"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_grid_sampler_2d_cpu_fallback(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +}; + +struct TORCH_API _grid_sampler_2d_cpu_fallback_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_grid_sampler_2d_cpu_fallback"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_grid_sampler_2d_cpu_fallback.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4a4777c6c3a4c449916f4e351662f87c626a02df --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_has_compatible_shallow_copy_type_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool _has_compatible_shallow_copy_type(const at::Tensor & self, const at::Tensor & from); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3908b8975d54eb4a55b13bfd8191cc363d9119d1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_cts_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 _histogramdd_from_bin_cts(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3d1f19cb182764abeff5715c65aaafd9d47a83ae --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_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 _histogramdd_from_bin_tensors { + using schema = at::Tensor (const at::Tensor &, at::TensorList, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_histogramdd_from_bin_tensors"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_histogramdd_from_bin_tensors(Tensor self, Tensor[] bins, *, Tensor? weight=None, bool density=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density); +}; + +struct TORCH_API _histogramdd_from_bin_tensors_out { + using schema = at::Tensor & (const at::Tensor &, at::TensorList, const ::std::optional &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_histogramdd_from_bin_tensors"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_histogramdd_from_bin_tensors.out(Tensor self, Tensor[] bins, *, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList bins, const ::std::optional & weight, bool density, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_indices.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_indices.h new file mode 100644 index 0000000000000000000000000000000000000000..db13fccd8880c914c43cb2f5d5af96f27db06e4b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_indices.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/_jagged_to_padded_dense_forward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_jagged_to_padded_dense_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..709975e130339e22609397b6c9c6dd1ffc17dcd4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_jagged_to_padded_dense_forward.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::_jagged_to_padded_dense_forward(Tensor values, Tensor[] offsets, SymInt[] max_lengths, float padding_value=0.0) -> Tensor +inline at::Tensor _jagged_to_padded_dense_forward(const at::Tensor & values, at::TensorList offsets, at::IntArrayRef max_lengths, double padding_value=0.0) { + return at::_ops::_jagged_to_padded_dense_forward::call(values, offsets, c10::fromIntArrayRefSlow(max_lengths), padding_value); +} +namespace symint { + template >> + at::Tensor _jagged_to_padded_dense_forward(const at::Tensor & values, at::TensorList offsets, at::IntArrayRef max_lengths, double padding_value=0.0) { + return at::_ops::_jagged_to_padded_dense_forward::call(values, offsets, c10::fromIntArrayRefSlow(max_lengths), padding_value); + } +} + +// aten::_jagged_to_padded_dense_forward(Tensor values, Tensor[] offsets, SymInt[] max_lengths, float padding_value=0.0) -> Tensor +inline at::Tensor _jagged_to_padded_dense_forward_symint(const at::Tensor & values, at::TensorList offsets, c10::SymIntArrayRef max_lengths, double padding_value=0.0) { + return at::_ops::_jagged_to_padded_dense_forward::call(values, offsets, max_lengths, padding_value); +} +namespace symint { + template >> + at::Tensor _jagged_to_padded_dense_forward(const at::Tensor & values, at::TensorList offsets, c10::SymIntArrayRef max_lengths, double padding_value=0.0) { + return at::_ops::_jagged_to_padded_dense_forward::call(values, offsets, max_lengths, padding_value); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ad36b303793b9cde7e3a4c67f3746080a4678ba4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_det_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_det(const at::Tensor & A); +TORCH_API ::std::tuple _linalg_det_out(at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, const at::Tensor & A); +TORCH_API ::std::tuple _linalg_det_outf(const at::Tensor & A, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_native.h new file mode 100644 index 0000000000000000000000000000000000000000..60306c361ed915ed346d8e187c0967dcda97cbd2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_eigvals_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 _linalg_eigvals(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..94f38f038d2997977c3fb29e115637e999c1ed81 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_linalg_solve_ex_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_solve_ex(const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false); +TORCH_API ::std::tuple _linalg_solve_ex_out(at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info, const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false); +TORCH_API ::std::tuple _linalg_solve_ex_outf(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_local_scalar_dense_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_local_scalar_dense_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..99cfefb5c2ec89c849cf7df2546ecb2963810d65 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_local_scalar_dense_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::Scalar _local_scalar_dense(const at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dep_token_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dep_token_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..030752cde06bd157caf8eda40666c19d70bb96b9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dep_token_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 _make_dep_token { + using schema = at::Tensor (::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::_make_dep_token"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_make_dep_token(*, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor"; + static at::Tensor call(::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, ::std::optional memory_format); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_copy_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a7020c6c92f8511ea455ab5f48fd866a15bad797 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_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 & _make_dual_copy_out(const at::Tensor & primal, const at::Tensor & tangent, int64_t level, at::Tensor & out); +TORCH_API at::Tensor _make_dual_copy(const at::Tensor & primal, const at::Tensor & tangent, int64_t level); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d67d9b4b3c0fb19960ad59d2525888210a92a518 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_make_dual_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 _make_dual { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_make_dual"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_make_dual(Tensor(a) primal, Tensor tangent, int level) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & primal, const at::Tensor & tangent, int64_t level); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & primal, const at::Tensor & tangent, int64_t level); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5ba45a470bd14a35f60b2ad9ae1bb19bc5aaffd9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_mps_convolution_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 & _mps_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); +TORCH_API at::Tensor & _mps_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, at::Tensor & out); +TORCH_API at::Tensor & _mps_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); +TORCH_API at::Tensor & _mps_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, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4ee12e590c6de945c7866ef58138ea66d9dec11c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_neg_view_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 _neg_view(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.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_and_nested_example.h new file mode 100644 index 0000000000000000000000000000000000000000..4aac1138945fc8a7c1bdef997b766e5ce7255e00 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_from_padded_and_nested_example.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_from_padded_and_nested_example(Tensor padded, Tensor nt_example) -> Tensor +inline at::Tensor _nested_from_padded_and_nested_example(const at::Tensor & padded, const at::Tensor & nt_example) { + return at::_ops::_nested_from_padded_and_nested_example::call(padded, nt_example); +} + +// aten::_nested_from_padded_and_nested_example.out(Tensor padded, Tensor nt_example, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_from_padded_and_nested_example_out(at::Tensor & out, const at::Tensor & padded, const at::Tensor & nt_example) { + return at::_ops::_nested_from_padded_and_nested_example_out::call(padded, nt_example, out); +} +// aten::_nested_from_padded_and_nested_example.out(Tensor padded, Tensor nt_example, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_from_padded_and_nested_example_outf(const at::Tensor & padded, const at::Tensor & nt_example, at::Tensor & out) { + return at::_ops::_nested_from_padded_and_nested_example_out::call(padded, nt_example, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_offsets.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_offsets.h new file mode 100644 index 0000000000000000000000000000000000000000..0fb7ce3010d56efa8ae34380b50ea8c234ca3315 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_offsets.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_offsets(Tensor self) -> Tensor +inline at::Tensor _nested_get_offsets(const at::Tensor & self) { + return at::_ops::_nested_get_offsets::call(self); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_values_copy_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_values_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5d7d78e200bba774be22615dd8f06031765a0056 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_values_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 & _nested_get_values_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & _nested_get_values_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_values_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_values_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..149f406fbbb93a5c754370371c56b51f0fd221ab --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_get_values_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _nested_get_values { + 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::_nested_get_values"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_nested_get_values(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_select_backward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_select_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..056dbfacc3fee9ccdf7f24e24b864b43f1ddd68f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_select_backward.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::_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor +inline at::Tensor _nested_select_backward(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::_nested_select_backward::call(grad_output, self, dim, index); +} +namespace symint { + template >> + at::Tensor _nested_select_backward(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, int64_t index) { + return at::_ops::_nested_select_backward::call(grad_output, self, dim, index); + } +} + +// aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor +inline at::Tensor _nested_select_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::_nested_select_backward::call(grad_output, self, dim, index); +} +namespace symint { + template >> + at::Tensor _nested_select_backward(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, c10::SymInt index) { + return at::_ops::_nested_select_backward::call(grad_output, self, dim, index); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..90183b9489485b0bce55d37725bc643761218da9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_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 bool _nested_tensor_from_mask_left_aligned(const at::Tensor & t, const at::Tensor & mask); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_tensor_list_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_tensor_list_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8d9d1065ef27f307efb9e654b718678e5fdce377 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_from_tensor_list_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 _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); +TORCH_API 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); +TORCH_API 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); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..406098009966baf37efea23e78407119aacdd936 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides_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_tensor_strides_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & _nested_tensor_strides_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2f71cbe1d17eb5aa399854d7045899c419ed0d8d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_tensor_strides_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 & _nested_tensor_strides_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _nested_tensor_strides(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_jagged.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_jagged.h new file mode 100644 index 0000000000000000000000000000000000000000..4eb3bb12a14c2a15f9f8adeb3b049f637fb79a33 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_nested_view_from_jagged.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_view_from_jagged(Tensor(a) self, Tensor offsets, Tensor dummy, Tensor? lengths=None, int ragged_idx=1, Tensor? min_seqlen=None, Tensor? max_seqlen=None) -> Tensor(a) +inline at::Tensor _nested_view_from_jagged(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={}) { + return at::_ops::_nested_view_from_jagged::call(self, offsets, dummy, lengths, ragged_idx, min_seqlen, max_seqlen); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f4de1e7beaa5c6a4b8a0f0281cffc6b6e1db4757 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_pack_padded_sequence_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 _pack_padded_sequence_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef input_size, const at::Tensor & batch_sizes, bool batch_first); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward.h new file mode 100644 index 0000000000000000000000000000000000000000..48cf0808f2b54e07f802612df7630dca0f825d05 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward.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::_padded_dense_to_jagged_forward(Tensor dense, Tensor[] offsets, SymInt? total_L=None) -> Tensor +inline at::Tensor _padded_dense_to_jagged_forward(const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L=::std::nullopt) { + return at::_ops::_padded_dense_to_jagged_forward::call(dense, offsets, total_L.has_value() ? ::std::make_optional(c10::SymInt(*total_L)) : ::std::nullopt); +} +namespace symint { + template >> + at::Tensor _padded_dense_to_jagged_forward(const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L=::std::nullopt) { + return at::_ops::_padded_dense_to_jagged_forward::call(dense, offsets, total_L.has_value() ? ::std::make_optional(c10::SymInt(*total_L)) : ::std::nullopt); + } +} + +// aten::_padded_dense_to_jagged_forward(Tensor dense, Tensor[] offsets, SymInt? total_L=None) -> Tensor +inline at::Tensor _padded_dense_to_jagged_forward_symint(const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L=::std::nullopt) { + return at::_ops::_padded_dense_to_jagged_forward::call(dense, offsets, total_L); +} +namespace symint { + template >> + at::Tensor _padded_dense_to_jagged_forward(const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L=::std::nullopt) { + return at::_ops::_padded_dense_to_jagged_forward::call(dense, offsets, total_L); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_pin_memory_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_pin_memory_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f2da4741d3bab819b3bf29100039b2a2e4d0da77 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_pin_memory_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 _pin_memory { + using schema = 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::_pin_memory"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_pin_memory(Tensor self, Device? device=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional device); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional device); +}; + +struct TORCH_API _pin_memory_out { + using schema = 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::_pin_memory"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_pin_memory.out(Tensor self, Device? device=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional device, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional device, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b3d3acc88549936300923dee53ded8cd81acea0c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_prelu_kernel_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 _prelu_kernel_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_propagate_xla_data_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_propagate_xla_data_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bb50fb7771a9d98de90d16a1d11ee20e78041faa --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_propagate_xla_data_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API void _propagate_xla_data(const at::Tensor & input, const at::Tensor & output); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0895291e71cbecc7cf1205d024c80775fbdcd1bf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sample_dirichlet_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 _sample_dirichlet { + using schema = 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::_sample_dirichlet"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sample_dirichlet(Tensor self, Generator? generator=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional generator); +}; + +struct TORCH_API _sample_dirichlet_out { + using schema = 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::_sample_dirichlet"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_sample_dirichlet.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional generator, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_saturate_weight_to_fp16.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_saturate_weight_to_fp16.h new file mode 100644 index 0000000000000000000000000000000000000000..fa722f7b237bfefe9b2b89a6a349e9cdb870d68f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_saturate_weight_to_fp16.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::_saturate_weight_to_fp16(Tensor weight) -> Tensor +inline at::Tensor _saturate_weight_to_fp16(const at::Tensor & weight) { + return at::_ops::_saturate_weight_to_fp16::call(weight); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0c4f59a5c39125b7832c94f078e16ee471356511 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _scaled_dot_product_cudnn_attention(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_native.h new file mode 100644 index 0000000000000000000000000000000000000000..725bafabb037bf540e54de25a1a63267c22b858d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_scaled_dot_product_cudnn_attention_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _scaled_dot_product_cudnn_attention_cuda(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_bias, bool compute_log_sumexp, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_segment_reduce_backward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_segment_reduce_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..be9397ca319d0477f74324049492a08db5782674 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_segment_reduce_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 _segment_reduce_backward(const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const ::std::optional & lengths={}, const ::std::optional & offsets={}, int64_t axis=0, const ::std::optional & initial=::std::nullopt); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7981ce6d643a79f94ec909015e57133deaa66514 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_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 _softmax(const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_outf(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..156e618d581416743636150a9d44c665f20ccaea --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_softmax_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 _softmax(const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool half_to_float); +TORCH_API at::Tensor & _softmax_outf(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe.h new file mode 100644 index 0000000000000000000000000000000000000000..502d15a06a7ff6338c00084c5ddae464c3e49855 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe.h @@ -0,0 +1,69 @@ +#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_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_compressed_tensor_unsafe_symint(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_compressed_tensor_unsafe_symint(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, size, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, size, dtype, layout, device, pin_memory); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors.h new file mode 100644 index 0000000000000000000000000000000000000000..e334603d66a145389eab596dc6746f5655c24f5e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors.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::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False, bool? is_coalesced=None) -> Tensor +inline at::Tensor _sparse_coo_tensor_with_dims_and_tensors(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, const at::Tensor & indices, const at::Tensor & values, at::TensorOptions options, ::std::optional is_coalesced=::std::nullopt) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors::call(sparse_dim, dense_dim, c10::fromIntArrayRefSlow(size), indices, values, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), is_coalesced); +} +namespace symint { + template >> + at::Tensor _sparse_coo_tensor_with_dims_and_tensors(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, const at::Tensor & indices, const at::Tensor & values, at::TensorOptions options, ::std::optional is_coalesced=::std::nullopt) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors::call(sparse_dim, dense_dim, c10::fromIntArrayRefSlow(size), indices, values, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), is_coalesced); + } +} + +// aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False, bool? is_coalesced=None) -> Tensor +inline at::Tensor _sparse_coo_tensor_with_dims_and_tensors(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef 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) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors::call(sparse_dim, dense_dim, c10::fromIntArrayRefSlow(size), indices, values, dtype, layout, device, pin_memory, is_coalesced); +} +namespace symint { + template >> + at::Tensor _sparse_coo_tensor_with_dims_and_tensors(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef 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) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors::call(sparse_dim, dense_dim, c10::fromIntArrayRefSlow(size), indices, values, dtype, layout, device, pin_memory, is_coalesced); + } +} + +// aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False, bool? is_coalesced=None) -> Tensor +inline at::Tensor _sparse_coo_tensor_with_dims_and_tensors_symint(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, at::TensorOptions options, ::std::optional is_coalesced=::std::nullopt) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors::call(sparse_dim, dense_dim, size, indices, values, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), is_coalesced); +} +namespace symint { + template >> + at::Tensor _sparse_coo_tensor_with_dims_and_tensors(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, at::TensorOptions options, ::std::optional is_coalesced=::std::nullopt) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors::call(sparse_dim, dense_dim, size, indices, values, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), is_coalesced); + } +} + +// aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False, bool? is_coalesced=None) -> Tensor +inline at::Tensor _sparse_coo_tensor_with_dims_and_tensors_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) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors::call(sparse_dim, dense_dim, size, indices, values, dtype, layout, device, pin_memory, is_coalesced); +} +namespace symint { + template >> + at::Tensor _sparse_coo_tensor_with_dims_and_tensors(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) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors::call(sparse_dim, dense_dim, size, indices, values, dtype, layout, device, pin_memory, is_coalesced); + } +} + +// aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, bool? is_coalesced=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_out(at::Tensor & out, int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional is_coalesced=::std::nullopt) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors_out::call(sparse_dim, dense_dim, c10::fromIntArrayRefSlow(size), indices, values, is_coalesced, out); +} +namespace symint { + template >> + at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_out(at::Tensor & out, int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional is_coalesced=::std::nullopt) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors_out::call(sparse_dim, dense_dim, c10::fromIntArrayRefSlow(size), indices, values, is_coalesced, out); + } +} + +// aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, bool? is_coalesced=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_outf(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional is_coalesced, at::Tensor & out) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors_out::call(sparse_dim, dense_dim, c10::fromIntArrayRefSlow(size), indices, values, is_coalesced, out); +} +namespace symint { + template >> + at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_outf(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional is_coalesced, at::Tensor & out) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors_out::call(sparse_dim, dense_dim, c10::fromIntArrayRefSlow(size), indices, values, is_coalesced, out); + } +} + +// aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, bool? is_coalesced=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_symint_out(at::Tensor & out, int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional is_coalesced=::std::nullopt) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors_out::call(sparse_dim, dense_dim, size, indices, values, is_coalesced, out); +} +namespace symint { + template >> + at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_out(at::Tensor & out, int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, ::std::optional is_coalesced=::std::nullopt) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors_out::call(sparse_dim, dense_dim, size, indices, values, is_coalesced, out); + } +} + +// aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, bool? is_coalesced=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_symint_outf(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) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors_out::call(sparse_dim, dense_dim, size, indices, values, is_coalesced, out); +} +namespace symint { + template >> + at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_outf(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) { + return at::_ops::_sparse_coo_tensor_with_dims_and_tensors_out::call(sparse_dim, dense_dim, size, indices, values, is_coalesced, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mm_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..51d95f833ebfb82638ee4a0612605a154388f96d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_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 _sparse_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::_sparse_mm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_mm(Tensor sparse, Tensor dense) -> Tensor"; + static at::Tensor call(const at::Tensor & sparse, const at::Tensor & dense); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sparse, const at::Tensor & dense); +}; + +struct TORCH_API _sparse_mm_reduce { + using schema = at::Tensor (const 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::_sparse_mm"; + static constexpr const char* overload_name = "reduce"; + static constexpr const char* schema_str = "_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor"; + static at::Tensor call(const at::Tensor & sparse, const at::Tensor & dense, c10::string_view reduce); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sparse, const at::Tensor & dense, c10::string_view reduce); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..782daae66114062183bf075a1b922f48fb759210 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_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_mm_reduce_impl { + using schema = ::std::tuple (const 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::_sparse_mm_reduce_impl"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_mm_reduce_impl(Tensor self, Tensor other, str reduce) -> (Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & other, c10::string_view reduce); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, c10::string_view reduce); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..058a62ff82958143cc261bd5fa211b91d3e8c4dd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm_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 _sparse_semi_structured_addmm(const at::Tensor & input, const at::Tensor & mat1, const at::Tensor & mat1_meta, const at::Tensor & mat2, const at::Scalar & alpha=1, const at::Scalar & beta=1, ::std::optional out_dtype=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_linear_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_linear_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4536ca3b9f85f1ea61107711fb14c56011af73db --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_semi_structured_linear_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 _sparse_semi_structured_linear(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & meta, const ::std::optional & bias={}, ::std::optional activation=::std::nullopt, ::std::optional out_dtype=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_sum_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_sum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..6040e0818252c8eeccff36b09f897fefdb33e56a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_sparse_sum_ops.h @@ -0,0 +1,72 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_sum { + 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::_sparse_sum"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_sparse_sum(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 _sparse_sum_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::_sparse_sum"; + static constexpr const char* overload_name = "dtype"; + static constexpr const char* schema_str = "_sparse_sum.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 _sparse_sum_dim { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_sum"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "_sparse_sum.dim(Tensor self, int[1] dim) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim); +}; + +struct TORCH_API _sparse_sum_dim_dtype { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::ScalarType); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_sum"; + static constexpr const char* overload_name = "dim_dtype"; + static constexpr const char* schema_str = "_sparse_sum.dim_dtype(Tensor self, int[1] dim, *, ScalarType dtype) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, at::ScalarType dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, at::ScalarType dtype); +}; + +struct TORCH_API _sparse_sum_dim_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_sparse_sum"; + static constexpr const char* overload_name = "dim_out"; + static constexpr const char* schema_str = "_sparse_sum.dim_out(Tensor self, int[1] dim, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a738efee255589bae006ab6c543142cb442e491f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_view_copy_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _test_autograd_multiple_dispatch_view_copy { + 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::_test_autograd_multiple_dispatch_view_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_test_autograd_multiple_dispatch_view_copy(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API _test_autograd_multiple_dispatch_view_copy_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::_test_autograd_multiple_dispatch_view_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_test_autograd_multiple_dispatch_view_copy.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/_test_functorch_fallback_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_test_functorch_fallback_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8d07396f8c3346e6626664f265c33a3c70280daa --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_test_functorch_fallback_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 & _test_functorch_fallback_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor _test_functorch_fallback(const at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_intlist.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_intlist.h new file mode 100644 index 0000000000000000000000000000000000000000..770e369b971535cd0a82d4bc6bd5ff76da392dde --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_test_optional_intlist.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::_test_optional_intlist(Tensor values, int[]? addends) -> Tensor +inline at::Tensor _test_optional_intlist(const at::Tensor & values, at::OptionalIntArrayRef addends) { + return at::_ops::_test_optional_intlist::call(values, addends); +} + +// aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_optional_intlist_out(at::Tensor & out, const at::Tensor & values, at::OptionalIntArrayRef addends) { + return at::_ops::_test_optional_intlist_out::call(values, addends, out); +} +// aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_optional_intlist_outf(const at::Tensor & values, at::OptionalIntArrayRef addends, at::Tensor & out) { + return at::_ops::_test_optional_intlist_out::call(values, addends, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cd1d4e8077a4084f8989d4b7c45e281f7b55170c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_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 _thnn_fused_gru_cell_backward(const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csc_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csc_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1468d03e0ca884293018672cb95c049332a13971 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_to_sparse_csc_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _to_sparse_csc_out(at::Tensor & out, const at::Tensor & self, ::std::optional dense_dim=::std::nullopt); +TORCH_API at::Tensor & _to_sparse_csc_outf(const at::Tensor & self, ::std::optional dense_dim, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd.h new file mode 100644 index 0000000000000000000000000000000000000000..668a4ba66259a8121e06123b373681b5af10d9dd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd.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::_transformer_encoder_layer_fwd(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None) -> Tensor +inline at::Tensor _transformer_encoder_layer_fwd(const at::Tensor & src, int64_t embed_dim, int64_t num_heads, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, bool use_gelu, bool norm_first, double eps, const at::Tensor & norm_weight_1, const at::Tensor & norm_bias_1, const at::Tensor & norm_weight_2, const at::Tensor & norm_bias_2, const at::Tensor & ffn_weight_1, const at::Tensor & ffn_bias_1, const at::Tensor & ffn_weight_2, const at::Tensor & ffn_bias_2, const ::std::optional & mask={}, ::std::optional mask_type=::std::nullopt) { + return at::_ops::_transformer_encoder_layer_fwd::call(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type); +} + +// aten::_transformer_encoder_layer_fwd.out(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _transformer_encoder_layer_fwd_out(at::Tensor & out, const at::Tensor & src, int64_t embed_dim, int64_t num_heads, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, bool use_gelu, bool norm_first, double eps, const at::Tensor & norm_weight_1, const at::Tensor & norm_bias_1, const at::Tensor & norm_weight_2, const at::Tensor & norm_bias_2, const at::Tensor & ffn_weight_1, const at::Tensor & ffn_bias_1, const at::Tensor & ffn_weight_2, const at::Tensor & ffn_bias_2, const ::std::optional & mask={}, ::std::optional mask_type=::std::nullopt) { + return at::_ops::_transformer_encoder_layer_fwd_out::call(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type, out); +} +// aten::_transformer_encoder_layer_fwd.out(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _transformer_encoder_layer_fwd_outf(const at::Tensor & src, int64_t embed_dim, int64_t num_heads, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, bool use_gelu, bool norm_first, double eps, const at::Tensor & norm_weight_1, const at::Tensor & norm_bias_1, const at::Tensor & norm_weight_2, const at::Tensor & norm_bias_2, const at::Tensor & ffn_weight_1, const at::Tensor & ffn_bias_1, const at::Tensor & ffn_weight_2, const at::Tensor & ffn_bias_2, const ::std::optional & mask, ::std::optional mask_type, at::Tensor & out) { + return at::_ops::_transformer_encoder_layer_fwd_out::call(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eb53df157ab86cd2c7247a4ef9ca2f4058470112 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_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 _transformer_encoder_layer_fwd(const at::Tensor & src, int64_t embed_dim, int64_t num_heads, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, bool use_gelu, bool norm_first, double eps, const at::Tensor & norm_weight_1, const at::Tensor & norm_bias_1, const at::Tensor & norm_weight_2, const at::Tensor & norm_bias_2, const at::Tensor & ffn_weight_1, const at::Tensor & ffn_bias_1, const at::Tensor & ffn_weight_2, const at::Tensor & ffn_bias_2, const ::std::optional & mask={}, ::std::optional mask_type=::std::nullopt); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0545d19ff1d6885eca01d88218696ac9f6fc01f2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_trilinear_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 & _trilinear_out(const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim, at::Tensor & out); +TORCH_API at::Tensor _trilinear(const at::Tensor & i1, const at::Tensor & i2, const at::Tensor & i3, at::IntArrayRef expand1, at::IntArrayRef expand2, at::IntArrayRef expand3, at::IntArrayRef sumdim, int64_t unroll_dim=1); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..360977d215aabc1470651aa884b4f465bdb4f027 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _triton_scaled_dot_attention(const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p=0.0); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_unique2_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_unique2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1432d3ac1d8976ded1c7ce3e2c7dd29a07036765 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_unique2_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 _unique2 { + using schema = ::std::tuple (const at::Tensor &, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_unique2"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "_unique2(Tensor self, bool sorted=True, bool return_inverse=False, bool return_counts=False) -> (Tensor, Tensor, Tensor)"; + static ::std::tuple call(const at::Tensor & self, bool sorted, bool return_inverse, bool return_counts); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool sorted, bool return_inverse, bool return_counts); +}; + +struct TORCH_API _unique2_out { + using schema = ::std::tuple (const at::Tensor &, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::_unique2"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "_unique2.out(Tensor self, bool sorted=True, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))"; + static ::std::tuple call(const at::Tensor & self, bool sorted, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool sorted, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..bba09ce35b638a8ee70e242a62e41267b0658da0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured__upsample_nearest_exact1d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, ::std::optional scales); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6b1ac0964407745ae5099f897a5f3d8acb50985e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_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 _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); +TORCH_API at::Tensor & _upsample_nearest_exact2d_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_nearest_exact2d_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_nearest_exact2d_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_nearest_exact2d_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 meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b29ccbcbb11a87df71016d8b19a0e6725319d62c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_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 _upsample_nearest_exact3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_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_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_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_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_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_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & _upsample_nearest_exact3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::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_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4322ddfd4e96810f65cf4bebcf3720a876a5c313 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_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 { +TORCH_API at::Tensor _upsample_nearest_exact3d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors); +struct TORCH_API structured__upsample_nearest_exact3d_out_cpu : public at::meta::structured__upsample_nearest_exact3d { +void impl(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +struct TORCH_API structured__upsample_nearest_exact3d_out_cuda : public at::meta::structured__upsample_nearest_exact3d { +void impl(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +TORCH_API at::Tensor _upsample_nearest_exact3d_quantized_cpu(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); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..28271e862247c03094fe1df2a898864502e3c246 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API void _validate_sparse_csc_tensor_args(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int8pack_mm.h b/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int8pack_mm.h new file mode 100644 index 0000000000000000000000000000000000000000..5879eae7dc38bc3f34b2ba2762cea5a60e7f0358 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/_weight_int8pack_mm.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::_weight_int8pack_mm(Tensor self, Tensor mat2, Tensor scales) -> Tensor +inline at::Tensor _weight_int8pack_mm(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scales) { + return at::_ops::_weight_int8pack_mm::call(self, mat2, scales); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/acos_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/acos_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a18c200a82da74105a022caddeec7f9508359c45 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/acos_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 acos(const at::Tensor & self); +TORCH_API at::Tensor & acos_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..61bb2f393fb4f3fc7af940efa3ae4ea983983734 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_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 adaptive_max_pool2d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool2d_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API ::std::tuple adaptive_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/addbmm_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/addbmm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..37f7c864c2ae13e0fe3b5d63e3b021b5a2af823f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/addbmm_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 addbmm(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addbmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addbmm_outf(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & addbmm_(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, 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/addcdiv_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d5253848a8ebbe0e16d11e1ec1e6b14c1c79c949 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/addcdiv_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 addcdiv(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); +TORCH_API at::Tensor & addcdiv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); +TORCH_API at::Tensor & addcdiv_outf(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & addcdiv_(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3e08a08c7df503fef6b35e7eb51310ddbb4655b4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/addcmul_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_addcmul_out : public at::meta::structured_addcmul { +void impl(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..44764014468430624a6078cff56e48bf728f579a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/addmm_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_addmm : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/addr_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/addr_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0166c5531009d66c6d6f3f187a4a4e221bad584d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/addr_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 math_addr(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & math_addr_out(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & addr_(at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor addr(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addr_out(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, 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/addr_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/addr_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fdb6dc271a8591cf0ad5bc2423596100496b2608 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/addr_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 addr { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addr"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "addr(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha); +}; + +struct TORCH_API addr_ { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addr_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "addr_(Tensor(a!) self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha); +}; + +struct TORCH_API addr_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::addr"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "addr.out(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/alias_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/alias_native.h new file mode 100644 index 0000000000000000000000000000000000000000..be36983439597a4839a666f036b4bc95c76c3e6a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/alias_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 alias(const at::Tensor & self); +TORCH_API at::Tensor alias_nested(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/amin_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/amin_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ac8b8896b16ce13ef163cdeb9c57dfa74638e365 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/amin_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 amin(const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); +TORCH_API at::Tensor & amin_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); +TORCH_API at::Tensor & amin_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/arctan.h b/lib/python3.12/site-packages/torch/include/ATen/ops/arctan.h new file mode 100644 index 0000000000000000000000000000000000000000..d40895a6755ab8984f46cb3cb71046bc49ae50f1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/arctan.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::arctan(Tensor self) -> Tensor +inline at::Tensor arctan(const at::Tensor & self) { + return at::_ops::arctan::call(self); +} + +// aten::arctan_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & arctan_(at::Tensor & self) { + return at::_ops::arctan_::call(self); +} + +// aten::arctan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arctan_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::arctan_out::call(self, out); +} +// aten::arctan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arctan_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::arctan_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided.h b/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided.h new file mode 100644 index 0000000000000000000000000000000000000000..17b8c6cf481eeeba98dcf4a200ec4dc93f4c4794 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/as_strided.h @@ -0,0 +1,69 @@ +#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::as_strided(Tensor(a) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a) +inline at::Tensor as_strided(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt); +} +namespace symint { + template >> + at::Tensor as_strided(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt); + } +} + +// aten::as_strided(Tensor(a) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a) +inline at::Tensor as_strided_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided::call(self, size, stride, storage_offset); +} +namespace symint { + template >> + at::Tensor as_strided(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided::call(self, size, stride, storage_offset); + } +} + +// aten::as_strided_(Tensor(a!) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a!) +inline const at::Tensor & as_strided_(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt); +} +namespace symint { + template >> + const at::Tensor & as_strided_(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), storage_offset.has_value() ? ::std::make_optional(c10::SymInt(*storage_offset)) : ::std::nullopt); + } +} + +// aten::as_strided_(Tensor(a!) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a!) +inline const at::Tensor & as_strided__symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_::call(self, size, stride, storage_offset); +} +namespace symint { + template >> + const at::Tensor & as_strided_(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset=::std::nullopt) { + return at::_ops::as_strided_::call(self, size, stride, storage_offset); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_1d_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_1d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ec584ce60f0ff0938de5c63119911c862253ef4d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_1d_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 atleast_1d(const at::Tensor & self); +TORCH_API ::std::vector atleast_1d(at::TensorList tensors); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_1d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_1d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ab0f21026dc358c1d1b2548e3692b34df80f4035 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_1d_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 atleast_1d(const at::Tensor & self); +TORCH_API ::std::vector atleast_1d(at::TensorList tensors); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_2d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..27d97ad4eb2787d844704df387cfbc6067c75e0a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_2d_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 atleast_2d(const at::Tensor & self); +TORCH_API ::std::vector atleast_2d(at::TensorList tensors); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_3d_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_3d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d5f28fd1e5037fbda545ed97e3c5c6c644c1f99c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/atleast_3d_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 atleast_3d { + 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::atleast_3d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "atleast_3d(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 atleast_3d_Sequence { + 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::atleast_3d"; + static constexpr const char* overload_name = "Sequence"; + static constexpr const char* schema_str = "atleast_3d.Sequence(Tensor[] tensors) -> Tensor[]"; + static ::std::vector call(at::TensorList tensors); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6be140b1cfa0c4f59a20eaaee58333d18f1ac4e8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool2d_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_avg_pool2d_out_cpu : public at::meta::structured_avg_pool2d { +void impl(const at::Tensor & self, int64_t kH, int64_t kW, int64_t dH, int64_t dW, int64_t padH, int64_t padW, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, const at::Tensor & out); +}; +struct TORCH_API structured_avg_pool2d_out_cuda : public at::meta::structured_avg_pool2d { +void impl(const at::Tensor & self, int64_t kH, int64_t kW, int64_t dH, int64_t dW, int64_t padH, int64_t padW, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, const at::Tensor & out); +}; +TORCH_API at::Tensor mkldnn_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 & mkldnn_avg_pool2d_out(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); +TORCH_API at::Tensor avg_pool2d_quantized_cpu(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); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2ac493946bb9fdd7277e1f1008f8870967620185 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/avg_pool3d_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_avg_pool3d_out_cpu : public at::meta::structured_avg_pool3d { +void impl(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, const at::Tensor & out); +}; +struct TORCH_API structured_avg_pool3d_out_cuda : public at::meta::structured_avg_pool3d { +void impl(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, const at::Tensor & out); +}; +TORCH_API at::Tensor mkldnn_avg_pool3d(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 & mkldnn_avg_pool3d_out(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); +TORCH_API at::Tensor avg_pool3d_quantized_cpu(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); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/baddbmm_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/baddbmm_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4abb0f00f03871700736d478a9c704cf33ab58d2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/baddbmm_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 baddbmm(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & baddbmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & baddbmm_outf(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & baddbmm_(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/baddbmm_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/baddbmm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4bc745f6277fc2cabd90f1953c69aa62149aa9a9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/baddbmm_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 baddbmm { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::baddbmm"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "baddbmm(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha); +}; + +struct TORCH_API baddbmm_ { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::baddbmm_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "baddbmm_(Tensor(a!) self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha); +}; + +struct TORCH_API baddbmm_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::baddbmm"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "baddbmm.out(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_elemt_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_elemt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b1150d60fb877db69698cb90c6eb4077c8a794dd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_elemt_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_elemt { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, const ::std::optional &, const at::Tensor &, const at::Tensor &, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::batch_norm_elemt"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "batch_norm_elemt(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps); +}; + +struct TORCH_API batch_norm_elemt_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, const ::std::optional &, const at::Tensor &, const at::Tensor &, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::batch_norm_elemt"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "batch_norm_elemt.out(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9d2bbf614b71fb93356db4f84b96e01956daf388 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_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_with_counts { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, double, double, const 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_with_counts"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "batch_norm_gather_stats_with_counts(Tensor input, Tensor mean, Tensor invstd, Tensor? running_mean, Tensor? running_var, float momentum, float eps, Tensor counts) -> (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, const at::Tensor & counts); + 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, const at::Tensor & counts); +}; + +struct TORCH_API batch_norm_gather_stats_with_counts_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, double, double, const at::Tensor &, 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_with_counts"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "batch_norm_gather_stats_with_counts.out(Tensor input, Tensor mean, Tensor invstd, Tensor? running_mean, Tensor? running_var, float momentum, float eps, Tensor counts, *, 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, const at::Tensor & counts, 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, const at::Tensor & counts, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5f71e046985e4917651de5154166089c7b23e515 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_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 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, bool cudnn_enabled); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_update_stats.h b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_update_stats.h new file mode 100644 index 0000000000000000000000000000000000000000..da735da08a7d199bf8239ad04a5ad2a386029dc8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/batch_norm_update_stats.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_update_stats(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum) -> (Tensor, Tensor) +inline ::std::tuple batch_norm_update_stats(const at::Tensor & input, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum) { + return at::_ops::batch_norm_update_stats::call(input, running_mean, running_var, momentum); +} + +// aten::batch_norm_update_stats.out(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple batch_norm_update_stats_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & input, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum) { + return at::_ops::batch_norm_update_stats_out::call(input, running_mean, running_var, momentum, out0, out1); +} +// aten::batch_norm_update_stats.out(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple batch_norm_update_stats_outf(const at::Tensor & input, const ::std::optional & running_mean, const ::std::optional & running_var, double momentum, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::batch_norm_update_stats_out::call(input, running_mean, running_var, momentum, out0, out1); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4e406b6a647ac1d1a4f8923b4ea4e776ccd30836 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/binary_cross_entropy_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 binary_cross_entropy_backward_cpu(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & binary_cross_entropy_backward_out_cpu(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); +TORCH_API at::Tensor binary_cross_entropy_backward_cuda(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & binary_cross_entropy_backward_out_cuda(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_left_shift_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_left_shift_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..457f388f16a7bf1bd5b318648cac338e374a992b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_left_shift_ops.h @@ -0,0 +1,105 @@ +#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 bitwise_left_shift_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::bitwise_left_shift"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "bitwise_left_shift.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 bitwise_left_shift__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::bitwise_left_shift_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "bitwise_left_shift_.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 bitwise_left_shift_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::bitwise_left_shift"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "bitwise_left_shift.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); +}; + +struct TORCH_API bitwise_left_shift_Tensor_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::bitwise_left_shift"; + static constexpr const char* overload_name = "Tensor_Scalar"; + static constexpr const char* schema_str = "bitwise_left_shift.Tensor_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 bitwise_left_shift__Tensor_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::bitwise_left_shift_"; + static constexpr const char* overload_name = "Tensor_Scalar"; + static constexpr const char* schema_str = "bitwise_left_shift_.Tensor_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 bitwise_left_shift_Tensor_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::bitwise_left_shift"; + static constexpr const char* overload_name = "Tensor_Scalar_out"; + static constexpr const char* schema_str = "bitwise_left_shift.Tensor_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 bitwise_left_shift_Scalar_Tensor { + 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::bitwise_left_shift"; + static constexpr const char* overload_name = "Scalar_Tensor"; + static constexpr const char* schema_str = "bitwise_left_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor"; + static at::Tensor call(const at::Scalar & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other); +}; + +struct TORCH_API bitwise_left_shift_Scalar_Tensor_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::bitwise_left_shift"; + static constexpr const char* overload_name = "Scalar_Tensor_out"; + static constexpr const char* schema_str = "bitwise_left_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_not_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_not_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cf94c9e57d6d19a7bea8a2006c2ef250c837e765 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_not_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor bitwise_not(const at::Tensor & self); +TORCH_API at::Tensor & bitwise_not_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & bitwise_not_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & bitwise_not_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_xor_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_xor_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cc72633f4d0a17579a1ab3a15c38fd86662941a1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_xor_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_bitwise_xor_Tensor : 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/bitwise_xor_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_xor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..aeb919b64d217228f549daaec2cc58ecc35af589 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bitwise_xor_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_xor_out : public at::meta::structured_bitwise_xor_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +TORCH_API at::Tensor bitwise_xor(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & bitwise_xor_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_xor_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor bitwise_xor(const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_xor_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/blackman_window_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/blackman_window_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..173bcf6a01b6576d12924771fe248d75f0d3b105 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/blackman_window_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 blackman_window(int64_t window_length, at::TensorOptions options={}); +TORCH_API at::Tensor blackman_window(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & blackman_window_out(at::Tensor & out, int64_t window_length); +TORCH_API at::Tensor & blackman_window_outf(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor blackman_window(int64_t window_length, bool periodic, at::TensorOptions options={}); +TORCH_API at::Tensor blackman_window(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & blackman_window_out(at::Tensor & out, int64_t window_length, bool periodic); +TORCH_API at::Tensor & blackman_window_outf(int64_t window_length, bool periodic, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/blackman_window_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/blackman_window_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d4ad0fa31d7c4af251daccd989728d7254abb4d6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/blackman_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 blackman_window(int64_t window_length, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & blackman_window_out(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor blackman_window(int64_t window_length, bool periodic, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & blackman_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/block_diag_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/block_diag_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b1b76be9646bf755eb896eb79f8efde2ed3a665c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/block_diag_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 block_diag(at::TensorList tensors); +TORCH_API at::Tensor & block_diag_out(at::TensorList tensors, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bmm.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bmm.h new file mode 100644 index 0000000000000000000000000000000000000000..6dfc9612702cacdfef410cf0aedc90809051f482 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bmm.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::bmm(Tensor self, Tensor mat2) -> Tensor +inline at::Tensor bmm(const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::bmm::call(self, mat2); +} + +// aten::bmm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2) { + return at::_ops::bmm_out::call(self, mat2, out); +} +// aten::bmm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bmm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out) { + return at::_ops::bmm_out::call(self, mat2, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..24f873e339c639ea39f9091d4431e8871ec1ca47 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_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 bmm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3abf2e8d9d832f19026e66aa85d8a2d7de40c8d3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/bmm_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 bmm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/broadcast_to_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/broadcast_to_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ccd2d32256c73f30139e4e62b72e8c604c4d61b1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/broadcast_to_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 broadcast_to(const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor broadcast_to_symint(const at::Tensor & self, c10::SymIntArrayRef size); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cat_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cat_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e504a5eaf81ddf258dd7682f86be0f21731d5c2e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cat_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 cat(const at::ITensorListRef & tensors, int64_t dim=0); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cat_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cat_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d92ace2d563ab99964d19742f8caa3593c6abbaa --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cat_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 cat(const at::ITensorListRef & tensors, int64_t dim=0); +TORCH_API at::Tensor & cat_out(at::Tensor & out, const at::ITensorListRef & tensors, int64_t dim=0); +TORCH_API at::Tensor & cat_outf(const at::ITensorListRef & tensors, int64_t dim, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0eafb6d551fb25bcb814acf1e021f242e00490bf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cauchy_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 cauchy(const at::Tensor & self, double median=0, double sigma=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & cauchy_out(const at::Tensor & self, double median, double sigma, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & cauchy_(at::Tensor & self, double median=0, double sigma=1, ::std::optional generator=::std::nullopt); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/ccol_indices_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/ccol_indices_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..066af4d8e48fe1c6b979ed75adf4f771a45678e4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/ccol_indices_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 ccol_indices { + 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::ccol_indices"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "ccol_indices(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/channel_shuffle.h b/lib/python3.12/site-packages/torch/include/ATen/ops/channel_shuffle.h new file mode 100644 index 0000000000000000000000000000000000000000..233ad23ee208b6f20d1c8e2f5efd459bd480980d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/channel_shuffle.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::channel_shuffle(Tensor self, SymInt groups) -> Tensor +inline at::Tensor channel_shuffle(const at::Tensor & self, int64_t groups) { + return at::_ops::channel_shuffle::call(self, groups); +} +namespace symint { + template >> + at::Tensor channel_shuffle(const at::Tensor & self, int64_t groups) { + return at::_ops::channel_shuffle::call(self, groups); + } +} + +// aten::channel_shuffle(Tensor self, SymInt groups) -> Tensor +inline at::Tensor channel_shuffle_symint(const at::Tensor & self, c10::SymInt groups) { + return at::_ops::channel_shuffle::call(self, groups); +} +namespace symint { + template >> + at::Tensor channel_shuffle(const at::Tensor & self, c10::SymInt groups) { + return at::_ops::channel_shuffle::call(self, groups); + } +} + +// aten::channel_shuffle.out(Tensor self, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & channel_shuffle_out(at::Tensor & out, const at::Tensor & self, int64_t groups) { + return at::_ops::channel_shuffle_out::call(self, groups, out); +} +namespace symint { + template >> + at::Tensor & channel_shuffle_out(at::Tensor & out, const at::Tensor & self, int64_t groups) { + return at::_ops::channel_shuffle_out::call(self, groups, out); + } +} + +// aten::channel_shuffle.out(Tensor self, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & channel_shuffle_outf(const at::Tensor & self, int64_t groups, at::Tensor & out) { + return at::_ops::channel_shuffle_out::call(self, groups, out); +} +namespace symint { + template >> + at::Tensor & channel_shuffle_outf(const at::Tensor & self, int64_t groups, at::Tensor & out) { + return at::_ops::channel_shuffle_out::call(self, groups, out); + } +} + +// aten::channel_shuffle.out(Tensor self, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & channel_shuffle_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymInt groups) { + return at::_ops::channel_shuffle_out::call(self, groups, out); +} +namespace symint { + template >> + at::Tensor & channel_shuffle_out(at::Tensor & out, const at::Tensor & self, c10::SymInt groups) { + return at::_ops::channel_shuffle_out::call(self, groups, out); + } +} + +// aten::channel_shuffle.out(Tensor self, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & channel_shuffle_symint_outf(const at::Tensor & self, c10::SymInt groups, at::Tensor & out) { + return at::_ops::channel_shuffle_out::call(self, groups, out); +} +namespace symint { + template >> + at::Tensor & channel_shuffle_outf(const at::Tensor & self, c10::SymInt groups, at::Tensor & out) { + return at::_ops::channel_shuffle_out::call(self, groups, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..56c7a1d424c01a2d4ee89a8b3d328bf8f09002a4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cholesky_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 cholesky(const at::Tensor & self, bool upper=false); +TORCH_API at::Tensor & cholesky_out(at::Tensor & out, const at::Tensor & self, bool upper=false); +TORCH_API at::Tensor & cholesky_outf(const at::Tensor & self, bool upper, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0fb9e60f21e135559f8dbc984ad9e0d7b1cf791b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/clamp_max_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor clamp_max(const at::Tensor & self, const at::Scalar & max); +TORCH_API at::Tensor & clamp_max_(at::Tensor & self, const at::Scalar & max); +TORCH_API at::Tensor clamp_max(const at::Tensor & self, const at::Tensor & max); +TORCH_API at::Tensor & clamp_max_(at::Tensor & self, const at::Tensor & max); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/clone_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/clone_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1654ad22976341b2657f403d41f16f717b816a43 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/clone_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 clone(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & clone_out(at::Tensor & out, const at::Tensor & self, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & clone_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/coalesce_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/coalesce_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bfc3a49df65860e9c885dc2a3a451e1c4ff73aac --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/coalesce_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 coalesce(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/col2im_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/col2im_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..072785412e57ce5e9cf8ffbbd686e194ca441004 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/col2im_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 col2im(const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor col2im_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & col2im_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & col2im_outf(const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out); +TORCH_API at::Tensor & col2im_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); +TORCH_API at::Tensor & col2im_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/col_indices_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/col_indices_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8bef705eac81429519850f6d231ac3cb6fafcbb7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/col_indices_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 col_indices { + 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::col_indices"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "col_indices(Tensor(a) self) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/conv1d_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/conv1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dbb7eaa79b17d85178740fb99cc13717785566b2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/conv1d_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API conv1d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conv1d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "conv1d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, SymInt[1] padding=0, SymInt[1] dilation=1, SymInt groups=1) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +struct TORCH_API conv1d_padding { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::string_view, c10::SymIntArrayRef, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conv1d"; + static constexpr const char* overload_name = "padding"; + static constexpr const char* schema_str = "conv1d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, str padding=\"valid\", SymInt[1] dilation=1, SymInt groups=1) -> Tensor"; + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..21f0fbe203f9fc7c390aa89c360cca998dea9e09 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/conv_tbc_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_tbc { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conv_tbc"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "conv_tbc(Tensor self, Tensor weight, Tensor bias, int pad=0) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & bias, int64_t pad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const at::Tensor & bias, int64_t pad); +}; + +struct TORCH_API conv_tbc_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::conv_tbc"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "conv_tbc.out(Tensor self, Tensor weight, Tensor bias, int pad=0, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & bias, int64_t pad, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const at::Tensor & bias, int64_t pad, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose2d_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose2d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c1104bcb83ab1aa0fd4409cbc17d3e2a479e8ab7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/conv_transpose2d_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 conv_transpose2d(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); +TORCH_API at::Tensor conv_transpose2d_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)); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/convolution_backward_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/convolution_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..179abb68f754e9d79e45f18988572ee10dde3723 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/convolution_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple convolution_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalIntArrayRef bias_sizes, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_symint(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalIntArrayRef bias_sizes, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalIntArrayRef bias_sizes, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple convolution_backward_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); +TORCH_API ::std::tuple convolution_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask, 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/copy.h b/lib/python3.12/site-packages/torch/include/ATen/ops/copy.h new file mode 100644 index 0000000000000000000000000000000000000000..671b1af9599ecc6403a3adeb173a96717969bbd4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/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::copy(Tensor self, Tensor src, bool non_blocking=False) -> Tensor +inline at::Tensor copy(const at::Tensor & self, const at::Tensor & src, bool non_blocking=false) { + return at::_ops::copy::call(self, src, non_blocking); +} + +// aten::copy.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, bool non_blocking=false) { + return at::_ops::copy_out::call(self, src, non_blocking, out); +} +// aten::copy.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copy_outf(const at::Tensor & self, const at::Tensor & src, bool non_blocking, at::Tensor & out) { + return at::_ops::copy_out::call(self, src, non_blocking, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse.h b/lib/python3.12/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse.h new file mode 100644 index 0000000000000000000000000000000000000000..d728e7d08de34cb4179d590570ba0481e960d582 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/copy_sparse_to_sparse.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::copy_sparse_to_sparse_(Tensor(a!) self, Tensor src, bool non_blocking=False) -> Tensor(a!) +inline at::Tensor & copy_sparse_to_sparse_(at::Tensor & self, const at::Tensor & src, bool non_blocking=false) { + return at::_ops::copy_sparse_to_sparse_::call(self, src, non_blocking); +} + +// aten::copy_sparse_to_sparse.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copy_sparse_to_sparse_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, bool non_blocking=false) { + return at::_ops::copy_sparse_to_sparse_out::call(self, src, non_blocking, out); +} +// aten::copy_sparse_to_sparse.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & copy_sparse_to_sparse_outf(const at::Tensor & self, const at::Tensor & src, bool non_blocking, at::Tensor & out) { + return at::_ops::copy_sparse_to_sparse_out::call(self, src, non_blocking, out); +} + +// aten::copy_sparse_to_sparse(Tensor self, Tensor src, bool non_blocking=False) -> Tensor +inline at::Tensor copy_sparse_to_sparse(const at::Tensor & self, const at::Tensor & src, bool non_blocking=false) { + return at::_ops::copy_sparse_to_sparse::call(self, src, non_blocking); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cross_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cross_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3ed9e02c9d589d7a0de636e7ddbabfc0c073ba53 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cross_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 cross(const at::Tensor & self, const at::Tensor & other, ::std::optional dim=::std::nullopt); +TORCH_API at::Tensor & cross_out(const at::Tensor & self, const at::Tensor & other, ::std::optional dim, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ecbd914196a29abe7a4df5c30411557f165ce90f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_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 crow_indices(const at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_copy_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3900cbe09ee6798fea5ed87a5782752253563dfa --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/crow_indices_copy_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API crow_indices_copy { + 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::crow_indices_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "crow_indices_copy(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 crow_indices_copy_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::crow_indices_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "crow_indices_copy.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/cudnn_affine_grid_generator.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator.h new file mode 100644 index 0000000000000000000000000000000000000000..cee13c19cf38acd800de97aa4174bd42d907591d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator.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::cudnn_affine_grid_generator(Tensor theta, int N, int C, int H, int W) -> Tensor grid +inline at::Tensor cudnn_affine_grid_generator(const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W) { + return at::_ops::cudnn_affine_grid_generator::call(theta, N, C, H, W); +} + +// aten::cudnn_affine_grid_generator.out(Tensor theta, int N, int C, int H, int W, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_affine_grid_generator_out(at::Tensor & out, const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W) { + return at::_ops::cudnn_affine_grid_generator_out::call(theta, N, C, H, W, out); +} +// aten::cudnn_affine_grid_generator.out(Tensor theta, int N, int C, int H, int W, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_affine_grid_generator_outf(const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W, at::Tensor & out) { + return at::_ops::cudnn_affine_grid_generator_out::call(theta, N, C, H, W, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..461adc5f950985f74f09e4a1961089dc67a82a3f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator_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 & cudnn_affine_grid_generator_backward_out(const at::Tensor & grad, int64_t N, int64_t C, int64_t H, int64_t W, at::Tensor & out); +TORCH_API at::Tensor cudnn_affine_grid_generator_backward(const at::Tensor & grad, int64_t N, int64_t C, int64_t H, int64_t W); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f3f8f0e1fdf4c230a2913b6274dbaf681fa4df17 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_affine_grid_generator_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 cudnn_affine_grid_generator(const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_transpose_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_transpose_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ea395fda1178ed8442b2519b768bb1f9336f60e0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_convolution_transpose_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 & cudnn_convolution_transpose_out_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, at::Tensor & out); +TORCH_API 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); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8423d3881dfbebb212c422f4e66484bd64d7e3e2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cudnn_grid_sampler_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 & cudnn_grid_sampler_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & grid); +TORCH_API at::Tensor & cudnn_grid_sampler_outf(const at::Tensor & self, const at::Tensor & grid, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..acb29423b475c4d9ee7796a625715c038daa19e0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/cumprod_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 cumprod(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & cumprod_(at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/data_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/data_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ef0c918c22793167d9999d7eeb7fd359c15e5ab0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/data_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 data(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/dequantize_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/dequantize_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c49e74c3f1fe439bedcdb8a67ed2abd9c57c20c9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/dequantize_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 & dequantize_self_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor dequantize_cpu_or_cuda(const at::Tensor & self); +TORCH_API at::Tensor dequantize_quantized(const at::Tensor & self); +TORCH_API void dequantize_tensors_out(at::TensorList tensors, at::TensorList out); +TORCH_API ::std::vector dequantize_tensors_quantized_cpu(at::TensorList tensors); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/diag_embed_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/diag_embed_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c5a0b8823a92decf1bdf36e7d7670bba6e06958f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/diag_embed_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 & diag_embed_out(const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out); +TORCH_API at::Tensor diag_embed(const at::Tensor & self, int64_t offset=0, int64_t dim1=-2, int64_t dim2=-1); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_copy_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6334d30399b02d20da4687e3249761036bfec08e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/diagonal_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 diagonal_copy(const at::Tensor & self, int64_t offset=0, int64_t dim1=0, int64_t dim2=1); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/dot_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/dot_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5b1afbaf3fad2ce3d9412807d2725e44663d2471 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/dot_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 dot(const at::Tensor & self, const at::Tensor & tensor); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/empty_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/empty_native.h new file mode 100644 index 0000000000000000000000000000000000000000..da1da256957f9b5fcc72585fc7d9ecef9a6430af --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/empty_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 + + +namespace at { +namespace native { +TORCH_API at::Tensor empty_names(at::IntArrayRef size, ::std::optional names, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & empty_names_out(at::IntArrayRef size, ::std::optional names, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor & empty_out(at::IntArrayRef size, ::std::optional memory_format, at::Tensor & out); +TORCH_API at::Tensor empty_cpu(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty_cuda(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty_meta_symint(c10::SymIntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty_sparse(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty_sparse_compressed(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty_sparse_compressed_symint(c10::SymIntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty_sparse_symint(c10::SymIntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty_mkldnn(at::IntArrayRef size, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor empty_unknown_quantized(at::IntArrayRef size, ::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/erfc_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/erfc_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6e0b4dec8808e4052cc11f4d927cbffdccaf25be --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/erfc_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 erfc(const at::Tensor & self); +TORCH_API at::Tensor & erfc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & erfc_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & erfc_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..93661b78959e228109f840bace8058893dd5313e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/erfinv_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 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 cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_native.h new file mode 100644 index 0000000000000000000000000000000000000000..70405219d4db4c4195370dba0e8a99c07f538da1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_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_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); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..479f4c38d709290949c1ef940623db5483870a53 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_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 fbgemm_linear_int8_weight { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, 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::fbgemm_linear_int8_weight"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fbgemm_linear_int8_weight(Tensor input, Tensor weight, Tensor packed, Tensor col_offsets, Scalar weight_scale, Scalar weight_zero_point, Tensor bias) -> Tensor"; + static at::Tensor call(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); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, 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 at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cbe2fab078b584210b71678a75d7847ce82ff2ab --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fft_hfft { + using schema = at::Tensor (const at::Tensor &, ::std::optional, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fft_hfft"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fft_hfft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor"; + static at::Tensor call(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm); +}; + +struct TORCH_API fft_hfft_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, 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::fft_hfft"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "fft_hfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional n, int64_t dim, ::std::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ifft2_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ifft2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3335dc73a033264064256a2b9f1364f83ed9c204 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fft_ifft2_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_ifft2_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_ifft2_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/fill_diagonal_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fill_diagonal_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..634fab90907009d06a30c4041f306d73bb7ea75d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fill_diagonal_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 fill_diagonal_ { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::fill_diagonal_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "fill_diagonal_(Tensor(a!) self, Scalar fill_value, bool wrap=False) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & fill_value, bool wrap); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & fill_value, bool wrap); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/flatten_dense_tensors_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/flatten_dense_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d3f0b0003e42e694501f0c3c6acbd39ba7c30b50 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/flatten_dense_tensors_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 flatten_dense_tensors { + 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::flatten_dense_tensors"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "flatten_dense_tensors(Tensor[] tensors) -> Tensor"; + static at::Tensor call(at::TensorList tensors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/flipud_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/flipud_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1b293309b2c97dbc554c08c98f0dbe5b9e42f3e1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/flipud_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 flipud(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/float_power_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/float_power_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4c6144c97749766aacbe55a450887cb804ea4c61 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/float_power_ops.h @@ -0,0 +1,105 @@ +#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 float_power_Tensor_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::float_power"; + static constexpr const char* overload_name = "Tensor_Tensor_out"; + static constexpr const char* schema_str = "float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out); +}; + +struct TORCH_API float_power_Tensor_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::float_power"; + static constexpr const char* overload_name = "Tensor_Tensor"; + static constexpr const char* schema_str = "float_power.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & exponent); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & exponent); +}; + +struct TORCH_API float_power_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::float_power"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out); +}; + +struct TORCH_API float_power_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::float_power"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "float_power.Scalar(Scalar self, Tensor exponent) -> Tensor"; + static at::Tensor call(const at::Scalar & self, const at::Tensor & exponent); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & exponent); +}; + +struct TORCH_API float_power_Tensor_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::float_power"; + static constexpr const char* overload_name = "Tensor_Scalar_out"; + static constexpr const char* schema_str = "float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out); +}; + +struct TORCH_API float_power_Tensor_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::float_power"; + static constexpr const char* overload_name = "Tensor_Scalar"; + static constexpr const char* schema_str = "float_power.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Scalar & exponent); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & exponent); +}; + +struct TORCH_API float_power__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::float_power_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "float_power_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Scalar & exponent); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & exponent); +}; + +struct TORCH_API float_power__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::float_power_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "float_power_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, const at::Tensor & exponent); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & exponent); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2fe850e86c4bcbf6cae16477de5719c2e7e7cfd9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_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 floor_divide(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & floor_divide_outf(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 compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..20492b854dc7970c97060c4e362b5967f98efd18 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_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_fmax : 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/fmax_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_native.h new file mode 100644 index 0000000000000000000000000000000000000000..772b90b546a0e86e240c393b70e490b11e4a6598 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_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_fmax_out : public at::meta::structured_fmax { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..bdda0855e2205b7cf28744125b55fd0deb9b7e62 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & fractional_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) { + return at::_ops::fractional_max_pool2d_backward_grad_input::call(grad_output, self, kernel_size, output_size, indices, grad_input); +} +// aten::fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & fractional_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input) { + return at::_ops::fractional_max_pool2d_backward_grad_input::call(grad_output, self, kernel_size, output_size, indices, grad_input); +} + +// aten::fractional_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices) -> Tensor +inline at::Tensor fractional_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) { + return at::_ops::fractional_max_pool2d_backward::call(grad_output, self, kernel_size, output_size, indices); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..374070e1b1ea9bb9b6b80f73dc9667eec350c48c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor fractional_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..82c6a0c27b7401c851dce0d45b182cc171d07466 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_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_fractional_max_pool2d_backward : public at::impl::MetaBase { + + + void meta(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..74bdcde879bdc245c29363d54b2b4e60573c6311 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_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_fractional_max_pool3d_out_cpu : public at::meta::structured_fractional_max_pool3d { +void impl(const at::Tensor & self, int64_t poolSizeT, int64_t poolSizeH, int64_t poolSizeW, int64_t outputT, int64_t outputH, int64_t outputW, const at::Tensor & random_samples, int64_t numBatch, int64_t numPlanes, int64_t inputT, int64_t inputH, int64_t inputW, const at::Tensor & output, const at::Tensor & indices); +}; +struct TORCH_API structured_fractional_max_pool3d_out_cuda : public at::meta::structured_fractional_max_pool3d { +void impl(const at::Tensor & self, int64_t poolSizeT, int64_t poolSizeH, int64_t poolSizeW, int64_t outputT, int64_t outputH, int64_t outputW, const at::Tensor & random_samples, int64_t numBatch, int64_t numPlanes, int64_t inputT, int64_t inputH, int64_t inputW, const at::Tensor & output, const at::Tensor & indices); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a4afd84d9678136255beda99578984648aecf7c2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor frobenius_norm(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & frobenius_norm_out(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/full.h b/lib/python3.12/site-packages/torch/include/ATen/ops/full.h new file mode 100644 index 0000000000000000000000000000000000000000..e7a0660584a4c55470c8bc3a7d9fffbb0350e80f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/full.h @@ -0,0 +1,131 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::full.names(int[] size, Scalar fill_value, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::full_names::call(size, fill_value, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::full.names(int[] size, Scalar fill_value, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::full_names::call(size, fill_value, names, dtype, layout, device, pin_memory); +} + +// aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}) { + return at::_ops::full::call(c10::fromIntArrayRefSlow(size), fill_value, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}) { + return at::_ops::full::call(c10::fromIntArrayRefSlow(size), fill_value, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::full::call(c10::fromIntArrayRefSlow(size), fill_value, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::full::call(c10::fromIntArrayRefSlow(size), fill_value, dtype, layout, device, pin_memory); + } +} + +// aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor full_symint(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}) { + return at::_ops::full::call(size, fill_value, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor full(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}) { + return at::_ops::full::call(size, fill_value, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor full_symint(c10::SymIntArrayRef size, const at::Scalar & fill_value, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::full::call(size, fill_value, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor full(c10::SymIntArrayRef size, const at::Scalar & fill_value, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::full::call(size, fill_value, dtype, layout, device, pin_memory); + } +} + +// aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value) { + return at::_ops::full_out::call(c10::fromIntArrayRefSlow(size), fill_value, out); +} +namespace symint { + template >> + at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value) { + return at::_ops::full_out::call(c10::fromIntArrayRefSlow(size), fill_value, out); + } +} + +// aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) { + return at::_ops::full_out::call(c10::fromIntArrayRefSlow(size), fill_value, out); +} +namespace symint { + template >> + at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) { + return at::_ops::full_out::call(c10::fromIntArrayRefSlow(size), fill_value, out); + } +} + +// aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & full_symint_out(at::Tensor & out, c10::SymIntArrayRef size, const at::Scalar & fill_value) { + return at::_ops::full_out::call(size, fill_value, out); +} +namespace symint { + template >> + at::Tensor & full_out(at::Tensor & out, c10::SymIntArrayRef size, const at::Scalar & fill_value) { + return at::_ops::full_out::call(size, fill_value, out); + } +} + +// aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & full_symint_outf(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) { + return at::_ops::full_out::call(size, fill_value, out); +} +namespace symint { + template >> + at::Tensor & full_outf(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) { + return at::_ops::full_out::call(size, fill_value, out); + } +} + +// aten::full.names_out(int[] size, Scalar fill_value, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names) { + return at::_ops::full_names_out::call(size, fill_value, names, out); +} +// aten::full.names_out(int[] size, Scalar fill_value, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names, at::Tensor & out) { + return at::_ops::full_names_out::call(size, fill_value, names, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/gather_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/gather_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..54e866da05dfb7c5afa762c43ba89342cd12913a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/gather_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 gather(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad=false); +TORCH_API at::Tensor & gather_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad=false); +TORCH_API at::Tensor & gather_outf(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/gather_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/gather_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fe06750582187e8e29726c75b942e7c0ea557664 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/gather_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 gather_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, 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::gather"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "gather.out(Tensor self, int dim, Tensor index, *, bool sparse_grad=False, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out); +}; + +struct TORCH_API gather { + using schema = at::Tensor (const at::Tensor &, int64_t, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gather"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "gather(Tensor self, int dim, Tensor index, *, bool sparse_grad=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad); +}; + +struct TORCH_API gather_dimname_out { + using schema = at::Tensor & (const at::Tensor &, at::Dimname, 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::gather"; + static constexpr const char* overload_name = "dimname_out"; + static constexpr const char* schema_str = "gather.dimname_out(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out); +}; + +struct TORCH_API gather_dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::gather"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "gather.dimname(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..50918137f2522ff9cf22356afdadafa2f36843ca --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_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 gcd(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & gcd_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fa915dc91bc9194e93fcf99f124570314d57201b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor gelu_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none"); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fe5129821001bc6dfbfc55640e2e699b04fe1f83 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor gelu_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none"); +TORCH_API at::Tensor & gelu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none"); +TORCH_API at::Tensor & gelu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ed1c2a4592f8cf086cd9acc73c30542dbff14a23 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API geqrf_a { + using schema = ::std::tuple (const at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::geqrf"; + static constexpr const char* overload_name = "a"; + static constexpr const char* schema_str = "geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau)"; + static ::std::tuple call(const at::Tensor & self, at::Tensor & a, at::Tensor & tau); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & a, at::Tensor & tau); +}; + +struct TORCH_API geqrf { + using schema = ::std::tuple (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::geqrf"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "geqrf(Tensor self) -> (Tensor a, Tensor tau)"; + static ::std::tuple call(const at::Tensor & self); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/ger_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/ger_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1329ffbb662862ee4e443e5403305dafdc8a6ea6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/ger_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor ger(const at::Tensor & self, const at::Tensor & vec2); +TORCH_API at::Tensor & ger_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec2); +TORCH_API at::Tensor & ger_outf(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2d28fdc1c9d8d076eeb1de2cf0def482f510c9e5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_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 & glu_backward_jvp_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, at::Tensor & out); +TORCH_API at::Tensor glu_backward_jvp(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); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..459da89fab45e69d5d1e38b467776c883fe881a4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_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 glu_jvp { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::glu_jvp"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "glu_jvp(Tensor glu, Tensor x, Tensor dx, int dim) -> Tensor"; + static at::Tensor call(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim); +}; + +struct TORCH_API glu_jvp_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::glu_jvp"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..bda539ab05ab2d3af82678fed7c3c072af4cd723 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/glu_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_glu : public TensorIteratorBase { + + + void meta(const at::Tensor & self, int64_t dim); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..540de004e7a63a7d304da9636d58c94701a3d9cf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_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 grid_sampler_2d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e5722d88243346058ae366b70e7f3aadbf9e8e18 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_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 group_norm(const at::Tensor & input, int64_t num_groups, const ::std::optional & weight={}, const ::std::optional & bias={}, double eps=1e-05, bool cudnn_enabled=true); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/gt_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/gt_native.h new file mode 100644 index 0000000000000000000000000000000000000000..50acfcd0d100bb2a5815c43815a71a5a2e0751e2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/gt_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_gt_Scalar_out : public at::meta::structured_gt_Scalar { +void impl(const at::Tensor & self, const at::Scalar & other, const at::Tensor & out); +}; +TORCH_API at::Tensor gt_scalar_nested(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor gt_quantized_cpu(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & gt_out_quantized_cpu(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +struct TORCH_API structured_gt_Tensor_out : public at::meta::structured_gt_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +TORCH_API at::Tensor gt_quantized_cpu(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & gt_out_quantized_cpu(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/hardtanh_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..096a736ed0d53e29e00dfb03e249a4e6981830b6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_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 hardtanh_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hardtanh_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input); +}; + +struct TORCH_API hardtanh_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::hardtanh_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "hardtanh_backward(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..39c520468b9d3671e6a5e847d0488e4d2a61635f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor heaviside(const at::Tensor & self, const at::Tensor & values); +TORCH_API at::Tensor & heaviside_(at::Tensor & self, const at::Tensor & values); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/histc_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/histc_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dc6f0db6aeae39e5229d10539e520599cd9f127d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/histc_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 histc(const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0); +TORCH_API at::Tensor & histc_out(at::Tensor & out, const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0); +TORCH_API at::Tensor & histc_outf(const at::Tensor & self, int64_t bins, const at::Scalar & min, const at::Scalar & max, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/hsplit.h b/lib/python3.12/site-packages/torch/include/ATen/ops/hsplit.h new file mode 100644 index 0000000000000000000000000000000000000000..90dcb2debefb834f1ee82e789952bf5712721679 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/hsplit.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::hsplit.int(Tensor(a -> *) self, int sections) -> Tensor(a)[] +inline ::std::vector hsplit(const at::Tensor & self, int64_t sections) { + return at::_ops::hsplit_int::call(self, sections); +} + +// aten::hsplit.array(Tensor(a -> *) self, int[] indices) -> Tensor(a)[] +inline ::std::vector hsplit(const at::Tensor & self, at::IntArrayRef indices) { + return at::_ops::hsplit_array::call(self, indices); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c19936a33610a166a0e56aae14ccd357b9afd95c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/huber_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 huber_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0); +TORCH_API at::Tensor & huber_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0); +TORCH_API at::Tensor & huber_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/huber_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a5d021d1717508b6f610b14d75ec8f84f98ef97c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/huber_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 at::Tensor huber_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0); +TORCH_API at::Tensor & huber_loss_out(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/i0_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/i0_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b5cd615ecd35730f9e17cf9663799d7dab3ec000 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/i0_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 i0(const at::Tensor & self); +TORCH_API at::Tensor & i0_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/igamma_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/igamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..988e28b3c486af29148a9288f059737baf70f649 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/igamma_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 igamma_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::igamma"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "igamma.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 igamma { + 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::igamma"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "igamma(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 igamma_ { + 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::igamma_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "igamma_(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/index_add.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_add.h new file mode 100644 index 0000000000000000000000000000000000000000..081e321ce6619fdb6ccc7758e0f58baa0f25b07c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_add.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::index_add.out(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::index_add_out::call(self, dim, index, source, alpha, out); +} +// aten::index_add.out(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::index_add_out::call(self, dim, index, source, alpha, out); +} + +// aten::index_add(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor +inline at::Tensor index_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1) { + return at::_ops::index_add::call(self, dim, index, source, alpha); +} + +// aten::index_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor +inline at::Tensor index_add(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha=1) { + return at::_ops::index_add_dimname::call(self, dim, index, source, alpha); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_add_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_add_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5077332e5c89dac973b6738ae678f70af428bddd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_add_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 index_add_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, 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::index_add"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "index_add.out(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha, 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, const at::Scalar & alpha, at::Tensor & out); +}; + +struct TORCH_API index_add_ { + using schema = at::Tensor & (at::Tensor &, int64_t, 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::index_add_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "index_add_(Tensor(a!) self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha); +}; + +struct TORCH_API index_add { + using schema = at::Tensor (const at::Tensor &, int64_t, 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::index_add"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "index_add(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha); +}; + +struct TORCH_API index_add_dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, 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::index_add"; + static constexpr const char* overload_name = "dimname"; + static constexpr const char* schema_str = "index_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_copy_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_copy_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a12333ade3b0ffd94d8705486b9fdcc1f71928a7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_copy_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 & index_copy_(at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source); +TORCH_API at::Tensor index_copy(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..817635950ce5369895f887983a91bf17e933e453 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_reduce_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_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 cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/index_select_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e08fadbc44582c61c8abc0de6be110d7f7f38cfd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/index_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 index_select_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, int64_t, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::index_select_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "index_select_backward(Tensor grad, SymInt[] self_sizes, int dim, Tensor index) -> Tensor"; + static at::Tensor call(const at::Tensor & grad, c10::SymIntArrayRef self_sizes, int64_t dim, const at::Tensor & index); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, c10::SymIntArrayRef self_sizes, int64_t dim, const at::Tensor & index); +}; + +}} // namespace at::_ops 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..d8ed63e438852171f924df96a10d39957377396b --- /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..40131cf854de239d045455a93d6dcbe2ef5c2f9a --- /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/infinitely_differentiable_gelu_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/infinitely_differentiable_gelu_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7e7a728b084ea226738d46ae10f8061b5799a2d4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/infinitely_differentiable_gelu_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 infinitely_differentiable_gelu_backward(const at::Tensor & grad, const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/is_coalesced_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/is_coalesced_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..34c78ad9f09d6207cc6d03eb39f10534cd9076d2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/is_coalesced_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_coalesced(const at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/is_distributed_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/is_distributed_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..36819d9c3ec11f5cde2da7c112da46b92fdfd0a6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/is_distributed_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API bool is_distributed(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/is_floating_point_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/is_floating_point_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d039f3aed74723577c5334cb6ac7f4816b23cc86 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/is_floating_point_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API bool is_floating_point(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned.h b/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned.h new file mode 100644 index 0000000000000000000000000000000000000000..0d0591e9233602664b71ca2529ce1bef2c3661c6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned.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/is_pinned_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1a2de9b00b414adcdae4b011b76432f46cc25bdd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/is_pinned_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_pinned { + using schema = bool (const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::is_pinned"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "is_pinned(Tensor self, Device? device=None) -> bool"; + static bool call(const at::Tensor & self, ::std::optional device); + static bool redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional device); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/is_set_to_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/is_set_to_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b74140e2f6123209704af82bcb206b5464d5c42d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/is_set_to_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool is_set_to(const at::Tensor & self, const at::Tensor & tensor); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/isclose_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isclose_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a5894b9909dbc65484b6c010e055d0e48face76f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isclose_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 isclose { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, double, double, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::isclose"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "isclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, double rtol, double atol, bool equal_nan); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, double rtol, double atol, bool equal_nan); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/isin_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isin_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..78ff202871c5ee01025a2783a0a48283b00090a9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isin_cuda_dispatch.h @@ -0,0 +1,31 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 isin(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_out(at::Tensor & out, const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_outf(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique, bool invert, at::Tensor & out); +TORCH_API at::Tensor isin(const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_out(at::Tensor & out, const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_outf(const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique, bool invert, at::Tensor & out); +TORCH_API at::Tensor isin(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_out(at::Tensor & out, const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor & isin_outf(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique, bool invert, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/isnan_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isnan_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b31ac1b5353a6c1a60cfc6f5ac2e50b5f2266e5b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isnan_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 isnan(const at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/isneginf_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isneginf_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9b007238b4049fd710b0fb0037fa6f17954227c8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isneginf_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 isneginf(const at::Tensor & self); +TORCH_API at::Tensor & isneginf_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & isneginf_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/isposinf_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/isposinf_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..80523e781050ef36805acbfbd675dcaffa7c26c8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/isposinf_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 isposinf(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/kl_div_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/kl_div_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3ba4fdf397867c01740c65d98789efa9c4c4c3f7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/kl_div_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 kl_div(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, bool log_target=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/kl_div_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/kl_div_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ef2209404328f35d6f9c70b664d70eccfe8ded2c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/kl_div_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 kl_div { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::kl_div"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "kl_div(Tensor self, Tensor target, int reduction=Mean, *, bool log_target=False) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, bool log_target); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, bool log_target); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/kron.h b/lib/python3.12/site-packages/torch/include/ATen/ops/kron.h new file mode 100644 index 0000000000000000000000000000000000000000..b480ab700068af9b2df81cc990c056538ce93c80 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/kron.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::kron(Tensor self, Tensor other) -> Tensor +inline at::Tensor kron(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::kron::call(self, other); +} + +// aten::kron.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & kron_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::kron_out::call(self, other, out); +} +// aten::kron.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & kron_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::kron_out::call(self, other, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/lcm_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/lcm_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..13463573a8ef8fe186cd9806f9820452e87f23d6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/lcm_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_lcm : 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/ldexp_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/ldexp_native.h new file mode 100644 index 0000000000000000000000000000000000000000..891b61c04b509ec572bb6db1b2c912a5ec966837 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/ldexp_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 ldexp(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & ldexp_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & ldexp_(at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/le_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/le_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..99b0f6716cedbd169834f261cafd4382d460d38b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/le_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor le(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & le_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor le(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & le_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/le_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/le_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a482f722fed49e8dc09be1cc0a95c236bd39d769 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/le_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 le_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::le"; + static constexpr const char* overload_name = "Scalar_out"; + static constexpr const char* schema_str = "le.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 le_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::le"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "le.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 le_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::le"; + static constexpr const char* overload_name = "Tensor_out"; + static constexpr const char* schema_str = "le.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); +}; + +struct TORCH_API le_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::le"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "le.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 le__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::le_"; + static constexpr const char* overload_name = "Scalar"; + static constexpr const char* schema_str = "le_.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 le__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::le_"; + static constexpr const char* overload_name = "Tensor"; + static constexpr const char* schema_str = "le_.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); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..07265842f40983ec7b7ad6d79107641c89f907c4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/lerp_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_lerp_Scalar : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +}; +struct TORCH_API structured_lerp_Tensor : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cond_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cond_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fd2bd54cad7476104a6b890e9dc8e9e7eec63400 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cond_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor linalg_cond(const at::Tensor & self, const ::std::optional & p=::std::nullopt); +TORCH_API at::Tensor & linalg_cond_out(at::Tensor & out, const at::Tensor & self, const ::std::optional & p=::std::nullopt); +TORCH_API at::Tensor & linalg_cond_outf(const at::Tensor & self, const ::std::optional & p, at::Tensor & out); +TORCH_API at::Tensor linalg_cond(const at::Tensor & self, c10::string_view p); +TORCH_API at::Tensor & linalg_cond_out(at::Tensor & out, const at::Tensor & self, c10::string_view p); +TORCH_API at::Tensor & linalg_cond_outf(const at::Tensor & self, c10::string_view p, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d633f2aa6510a5b0dbc0885e0754681b125b13f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_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 linalg_cross(const at::Tensor & self, const at::Tensor & other, int64_t dim=-1); +TORCH_API at::Tensor & linalg_cross_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, int64_t dim=-1); +TORCH_API at::Tensor & linalg_cross_outf(const at::Tensor & self, const at::Tensor & other, int64_t dim, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2f5632bd15a0034aee43130f67ee127e3774e14f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_cross_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_cross { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_cross"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_cross(Tensor self, Tensor other, *, int dim=-1) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, int64_t dim); +}; + +struct TORCH_API linalg_cross_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_cross"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_cross.out(Tensor self, Tensor other, *, int dim=-1, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, int64_t dim, at::Tensor & out); +}; + +}} // namespace at::_ops 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..58855136350795d6c4c473cd74975dde70a0d3ea --- /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 +inline at::Tensor linalg_det(const at::Tensor & A) { + return at::_ops::linalg_det::call(A); +} + +// aten::linalg_det.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_det_out(at::Tensor & out, const at::Tensor & A) { + return at::_ops::linalg_det_out::call(A, out); +} +// aten::linalg_det.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_det_outf(const at::Tensor & A, at::Tensor & out) { + return at::_ops::linalg_det_out::call(A, out); +} + +} 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..f4884271b3751138d8447dcf56adc59ab29726f1 --- /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); + 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 self, str UPLO=\"L\") -> (Tensor eigenvalues, Tensor eigenvectors)"; + static ::std::tuple call(const at::Tensor & self, c10::string_view UPLO); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view UPLO); +}; + +struct TORCH_API linalg_eigh_eigvals { + using schema = ::std::tuple (const at::Tensor &, c10::string_view, 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 = "eigvals"; + static constexpr const char* schema_str = "linalg_eigh.eigvals(Tensor self, str UPLO=\"L\", *, Tensor(a!) eigvals, Tensor(b!) eigvecs) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors)"; + static ::std::tuple call(const at::Tensor & self, c10::string_view UPLO, at::Tensor & eigvals, at::Tensor & eigvecs); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view UPLO, at::Tensor & eigvals, at::Tensor & eigvecs); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigvals_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigvals_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b3d126ead33f00cc9f886307a692d4a0e27ecdaf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigvals_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 linalg_eigvals(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigvalsh_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigvalsh_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..38cfa189b5d2dfabc4da4b19489ccb108e8fa5ba --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_eigvalsh_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_eigvalsh(const at::Tensor & self, c10::string_view UPLO="L"); +TORCH_API at::Tensor & linalg_eigvalsh_out(at::Tensor & out, const at::Tensor & self, c10::string_view UPLO="L"); +TORCH_API at::Tensor & linalg_eigvalsh_outf(const at::Tensor & self, c10::string_view UPLO, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..d65d1ac7a8030498da330d690e2e0dc5d8e7995a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_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_ldl_factor_ex : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, bool hermitian, bool check_errors); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..df858127f7fd63ad94be2cafdccd37464cf1af1f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_lu_solve_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor linalg_lu_solve(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left=true, bool adjoint=false); +TORCH_API at::Tensor & linalg_lu_solve_out(at::Tensor & out, const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left=true, bool adjoint=false); +TORCH_API at::Tensor & linalg_lu_solve_outf(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left, bool adjoint, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_qr_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_qr_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4cb2d843d33be9440174748025fa2bf506fe3f4d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_qr_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_qr { + using schema = ::std::tuple (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::linalg_qr"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_qr(Tensor A, str mode='reduced') -> (Tensor Q, Tensor R)"; + static ::std::tuple call(const at::Tensor & A, c10::string_view mode); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::string_view mode); +}; + +struct TORCH_API linalg_qr_out { + using schema = ::std::tuple (const at::Tensor &, c10::string_view, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_qr"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_qr.out(Tensor A, str mode='reduced', *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R)"; + static ::std::tuple call(const at::Tensor & A, c10::string_view mode, at::Tensor & Q, at::Tensor & R); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::string_view mode, at::Tensor & Q, at::Tensor & R); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_solve_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_solve_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ce6506d6985f9d5696e0523cb01daced1a851803 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_solve_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_solve { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_solve"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "linalg_solve(Tensor A, Tensor B, *, bool left=True) -> Tensor"; + static at::Tensor call(const at::Tensor & A, const at::Tensor & B, bool left); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, const at::Tensor & B, bool left); +}; + +struct TORCH_API linalg_solve_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::linalg_solve"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "linalg_solve.out(Tensor A, Tensor B, *, bool left=True, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & A, const at::Tensor & B, bool left, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, const at::Tensor & B, bool left, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_svdvals_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_svdvals_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c4fc9dd05ffbd292afc0bb8b1a6b76d5432b709e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/linalg_svdvals_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_svdvals(const at::Tensor & A, ::std::optional driver=::std::nullopt); +TORCH_API at::Tensor & linalg_svdvals_out(at::Tensor & out, const at::Tensor & A, ::std::optional driver=::std::nullopt); +TORCH_API at::Tensor & linalg_svdvals_outf(const at::Tensor & A, ::std::optional driver, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/log_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/log_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..b73cb80ce1bd2ee8fce856b7116ce33ee4d72954 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/log_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_log : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..09e052791e60af056f00cb2c8bb66fa72f994847 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logaddexp_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 logaddexp_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::logaddexp"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "logaddexp.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 logaddexp { + 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::logaddexp"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "logaddexp(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/logdet_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logdet_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d916fbe9dd97906ae3ead4e62cbe75691a03f34 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logdet_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 logdet(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8e49c95ec0dd0f30ca62807ca390f01f97b63da4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logical_or_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 logical_or(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_or_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/logit_backward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logit_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d62a0c3b3cfe9e8d790141618e7557591d8d5197 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logit_backward_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor logit_backward(const at::Tensor & grad_output, const at::Tensor & self, ::std::optional eps=::std::nullopt); +TORCH_API at::Tensor & logit_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, ::std::optional eps=::std::nullopt); +TORCH_API at::Tensor & logit_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, ::std::optional eps, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/logit_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/logit_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..100579586410a79cc291d331cdf7bd7de49c9dd3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/logit_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 logit(const at::Tensor & self, ::std::optional eps=::std::nullopt); +TORCH_API at::Tensor & logit_out(at::Tensor & out, const at::Tensor & self, ::std::optional eps=::std::nullopt); +TORCH_API at::Tensor & logit_outf(const at::Tensor & self, ::std::optional eps, at::Tensor & out); +TORCH_API at::Tensor & logit_(at::Tensor & self, ::std::optional eps=::std::nullopt); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/lstm_cell_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/lstm_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c1495f7aca39e2cf436e3d102f45ebbeea3ebf61 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/lstm_cell_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 lstm_cell(const at::Tensor & input, at::TensorList hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional & b_ih={}, const ::std::optional & b_hh={}); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/lstm_mps_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/lstm_mps_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0eff4a7a538f3727746de562407df00cbf36ec9c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/lstm_mps_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 lstm_mps_backward { + using schema = ::std::tuple,::std::vector> (const ::std::optional &, const ::std::optional &, const ::std::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::lstm_mps_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "lstm_mps_backward(Tensor? grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor[], Tensor[])"; + static ::std::tuple,::std::vector> call(const ::std::optional & grad_y, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & z_state, const at::Tensor & cell_state_fwd, const at::Tensor & input, const at::Tensor & layersOutputs, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first); + static ::std::tuple,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, const ::std::optional & grad_y, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & z_state, const at::Tensor & cell_state_fwd, const at::Tensor & input, const at::Tensor & layersOutputs, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first); +}; + +struct TORCH_API lstm_mps_backward_out { + using schema = void (const ::std::optional &, const ::std::optional &, const ::std::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::lstm_mps_backward"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "lstm_mps_backward.out(Tensor? grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!)[] out1, Tensor(c!)[] out2) -> ()"; + static void call(const ::std::optional & grad_y, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & z_state, const at::Tensor & cell_state_fwd, const at::Tensor & input, const at::Tensor & layersOutputs, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first, at::Tensor & out0, at::TensorList out1, at::TensorList out2); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const ::std::optional & grad_y, const ::std::optional & grad_hy, const ::std::optional & grad_cy, const at::Tensor & z_state, const at::Tensor & cell_state_fwd, const at::Tensor & input, const at::Tensor & layersOutputs, at::TensorList hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first, at::Tensor & out0, at::TensorList out1, at::TensorList out2); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/lt_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/lt_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f03c8b47c3bee2b428275c467a02fdbd2c2da2eb --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/lt_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_lt_Scalar : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Scalar & other); +}; +struct TORCH_API structured_lt_Tensor : 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/lu_unpack.h b/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack.h new file mode 100644 index 0000000000000000000000000000000000000000..b09231438e255ae62620d7216c64479f7828f515 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/lu_unpack.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::lu_unpack(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True) -> (Tensor P, Tensor L, Tensor U) +inline ::std::tuple lu_unpack(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data=true, bool unpack_pivots=true) { + return at::_ops::lu_unpack::call(LU_data, LU_pivots, unpack_data, unpack_pivots); +} + +// aten::lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True, *, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) +inline ::std::tuple lu_unpack_out(at::Tensor & P, at::Tensor & L, at::Tensor & U, const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data=true, bool unpack_pivots=true) { + return at::_ops::lu_unpack_out::call(LU_data, LU_pivots, unpack_data, unpack_pivots, P, L, U); +} +// aten::lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True, *, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) +inline ::std::tuple lu_unpack_outf(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots, at::Tensor & P, at::Tensor & L, at::Tensor & U) { + return at::_ops::lu_unpack_out::call(LU_data, LU_pivots, unpack_data, unpack_pivots, P, L, U); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f4d67377d710ba6fdb83e22773d4f79809e3abeb --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_fill_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor masked_fill(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); +TORCH_API at::Tensor & masked_fill_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); +TORCH_API at::Tensor & masked_fill_outf(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor masked_fill(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); +TORCH_API at::Tensor & masked_fill_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); +TORCH_API at::Tensor & masked_fill_outf(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d5d4436d4d26ac9c46f70f1455184aaa5922518f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_scatter_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_scatter_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::masked_scatter_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "masked_scatter_backward(Tensor grad_output, Tensor mask, SymInt[] sizes) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & mask, c10::SymIntArrayRef sizes); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & mask, c10::SymIntArrayRef sizes); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_native.h new file mode 100644 index 0000000000000000000000000000000000000000..915ae34ec84befc83af9f904a2092eeb8ef465b0 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/masked_select_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 masked_select_cpu(const at::Tensor & self, const at::Tensor & mask); +TORCH_API at::Tensor & masked_select_out_cpu(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); +TORCH_API at::Tensor masked_select_cuda(const at::Tensor & self, const at::Tensor & mask); +TORCH_API at::Tensor & masked_select_out_cuda(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d8b5f2f5d5da1d7bcc3b5d9b518c2376c2acdf95 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/matmul_backward_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple matmul_backward_out(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & other, ::std::array mask, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple matmul_backward_nested(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & other, ::std::array mask); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/matrix_H_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/matrix_H_native.h new file mode 100644 index 0000000000000000000000000000000000000000..65c4a66dbddef66fd784446b41beea93cc7c5140 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/matrix_H_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 matrix_H(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/matrix_power_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/matrix_power_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f365ae4930ab6653957866f62f4e5d31a4025a4e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/matrix_power_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 matrix_power(const at::Tensor & self, int64_t n); +TORCH_API at::Tensor & matrix_power_out(const at::Tensor & self, int64_t n, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_backward_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_backward_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dc219d66a9ccc27ff012654661a59012a6091f80 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_backward_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & max_pool2d_backward_out(at::Tensor & out, const at::Tensor & grad_output, 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 & max_pool2d_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, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..04ea12298a75b2eef1df0122bbbdd74cb3dbdf69 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool2d_with_indices_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 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); +TORCH_API ::std::tuple max_pool2d_with_indices_out(at::Tensor & out, at::Tensor & indices, 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 ::std::tuple max_pool2d_with_indices_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d.h new file mode 100644 index 0000000000000000000000000000000000000000..3277f9f100fa82bb397d5a568cb6b1fda333dda7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/max_pool3d.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::max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor +inline at::Tensor max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::max_pool3d::call(self, kernel_size, stride, padding, dilation, ceil_mode); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool3d_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool3d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f5ccf388e5c9806a4babb04273bab8c65a836607 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/max_unpool3d_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 max_unpool3d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor max_unpool3d_symint(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor & max_unpool3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor & max_unpool3d_outf(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_unpool3d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); +TORCH_API at::Tensor & max_unpool3d_symint_outf(const at::Tensor & self, const at::Tensor & indices, c10::SymIntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f7c3c6c1efbdc7db986cf76b1f3ff7c994c10bcd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/maximum_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_maximum : 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/meshgrid_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/meshgrid_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1f4110abbfd40b7a3adf704f3e49a2ed6b1c1f5c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/meshgrid_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 meshgrid(at::TensorList tensors); +TORCH_API ::std::vector meshgrid(at::TensorList tensors, c10::string_view indexing); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/minimum_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/minimum_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..af5e18072fac24ea9d017660f3bb6a37ce784f91 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/minimum_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_minimum : 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/miopen_convolution_relu_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_relu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..182b563d90ef83419d4a3f701384095b8fca61b7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_convolution_relu_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 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); +TORCH_API at::Tensor miopen_convolution_relu_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_rnn_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_rnn_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3e6d49723fc179a769ace4f864d5ed66cd68441f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/miopen_rnn_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 miopen_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state); +TORCH_API ::std::tuple miopen_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const ::std::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/mish_backward_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/mish_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a150e80649b0b6d42d767d9210c770e98d21aaf7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/mish_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 mish_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/mm_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/mm_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0fee6727424a90532d2288f51c35b8d7ec01f47a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/mm_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 mm(const at::Tensor & self, const at::Tensor & mat2); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/msort_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/msort_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e321ab1d6b38c758dee7209182daf5d3b0f3b3b1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/msort_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 msort(const at::Tensor & self); +TORCH_API at::Tensor & msort_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & msort_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..c8e37e61616b7e3148ed75fa6ab6a90ba0fad1fa --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/multilabel_margin_loss_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::multilabel_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & multilabel_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target) { + return at::_ops::multilabel_margin_loss_backward_grad_input::call(grad_output, self, target, reduction, is_target, grad_input); +} +// aten::multilabel_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & multilabel_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input) { + return at::_ops::multilabel_margin_loss_backward_grad_input::call(grad_output, self, target, reduction, is_target, grad_input); +} + +// aten::multilabel_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target) -> Tensor +inline at::Tensor multilabel_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target) { + return at::_ops::multilabel_margin_loss_backward::call(grad_output, self, target, reduction, is_target); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/mvlgamma_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/mvlgamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..15feb2faea25300aae8cc4bc4120a705f230bcba --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/mvlgamma_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 mvlgamma_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mvlgamma"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "mvlgamma.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p, at::Tensor & out); +}; + +struct TORCH_API mvlgamma { + using schema = at::Tensor (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mvlgamma"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mvlgamma(Tensor self, int p) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p); +}; + +struct TORCH_API mvlgamma_ { + using schema = at::Tensor & (at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::mvlgamma_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "mvlgamma_(Tensor(a!) self, int p) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t p); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t p); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nan_to_num_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nan_to_num_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b5f2651a8dca9ab7f39b1e03b7bb224290e13f0d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nan_to_num_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 nan_to_num(const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); +TORCH_API at::Tensor & nan_to_num_(at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/negative_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/negative_native.h new file mode 100644 index 0000000000000000000000000000000000000000..85bde5712d776c3d31d5185ac49e7bef06978c7e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/negative_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 negative(const at::Tensor & self); +TORCH_API at::Tensor & negative_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & negative_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6a6da3a819f0718b514568576d414d26eaef1636 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_forward_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple nll_loss2d_forward_cpu(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_out_cpu(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_cuda(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_out_cuda(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); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9497996c80014f37693228d53e0d3842c54fac80 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss2d_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 nll_loss2d_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nll_loss2d"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & out); +}; + +struct TORCH_API nll_loss2d { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nll_loss2d"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor"; + static at::Tensor call(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, c10::SymInt ignore_index); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f13610cc09d06b9f3a4b4ebb03ce1bc80d7d8255 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API nll_loss_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nll_loss_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(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); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API nll_loss_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, int64_t, c10::SymInt, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nll_loss_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor"; + static at::Tensor call(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); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_forward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..85925396e31178f3d1ab049698d365e6e2d29333 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nll_loss_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_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); +TORCH_API ::std::tuple nll_loss_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_loss_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_loss_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_loss_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/nonzero_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..24d7d2dfa70d45871f7d1c57c40aac607783bb6d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_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 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 cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8350d727b4e7fa8ab9ce01c64aea4ed2a05e309b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/nonzero_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API nonzero_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nonzero"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "nonzero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API nonzero { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::nonzero"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "nonzero(Tensor self) -> Tensor"; + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/normal_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/normal_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aec9c3a0559f9047d87d9fa8964bc13826bec7bf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/normal_cpu_dispatch.h @@ -0,0 +1,32 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 & normal_(at::Tensor & self, double mean=0, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor normal(const at::Tensor & mean, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, const at::Tensor & mean, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(const at::Tensor & mean, double std, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(double mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, double mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(double mean, const at::Tensor & std, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(const at::Tensor & mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, const at::Tensor & mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(const at::Tensor & mean, const at::Tensor & std, ::std::optional generator, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/normal_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/normal_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ed423d3476303fc6c90085e846587d8a95b84b47 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/normal_meta_dispatch.h @@ -0,0 +1,32 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 & normal_(at::Tensor & self, double mean=0, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor normal(const at::Tensor & mean, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, const at::Tensor & mean, double std=1, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(const at::Tensor & mean, double std, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(double mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, double mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(double mean, const at::Tensor & std, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor normal(const at::Tensor & mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_out(at::Tensor & out, const at::Tensor & mean, const at::Tensor & std, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & normal_outf(const at::Tensor & mean, const at::Tensor & std, ::std::optional generator, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/ones.h b/lib/python3.12/site-packages/torch/include/ATen/ops/ones.h new file mode 100644 index 0000000000000000000000000000000000000000..330eff57a57d5a89f4248eaa637eb046ee444823 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/ones.h @@ -0,0 +1,131 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::ones.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones(at::IntArrayRef size, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::ones_names::call(size, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::ones.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones(at::IntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::ones_names::call(size, names, dtype, layout, device, pin_memory); +} + +// aten::ones(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::ones::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor ones(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::ones::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::ones(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::ones::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor ones(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::ones::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::ones(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones_symint(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::ones::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor ones(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::ones::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::ones(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor ones_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::ones::call(size, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor ones(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::ones::call(size, dtype, layout, device, pin_memory); + } +} + +// aten::ones.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::ones_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & ones_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::ones_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::ones.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::ones_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & ones_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::ones_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::ones.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_symint_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::ones_out::call(size, out); +} +namespace symint { + template >> + at::Tensor & ones_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::ones_out::call(size, out); + } +} + +// aten::ones.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_symint_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::ones_out::call(size, out); +} +namespace symint { + template >> + at::Tensor & ones_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::ones_out::call(size, out); + } +} + +// aten::ones.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_out(at::Tensor & out, at::IntArrayRef size, ::std::optional names) { + return at::_ops::ones_names_out::call(size, names, out); +} +// aten::ones.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ones_outf(at::IntArrayRef size, ::std::optional names, at::Tensor & out) { + return at::_ops::ones_names_out::call(size, names, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/ormqr.h b/lib/python3.12/site-packages/torch/include/ATen/ops/ormqr.h new file mode 100644 index 0000000000000000000000000000000000000000..137e899800312cc8a02cdf43b9d583fe8bc39056 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/ormqr.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::ormqr.out(Tensor self, Tensor input2, Tensor input3, bool left=True, bool transpose=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ormqr_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left=true, bool transpose=false) { + return at::_ops::ormqr_out::call(self, input2, input3, left, transpose, out); +} +// aten::ormqr.out(Tensor self, Tensor input2, Tensor input3, bool left=True, bool transpose=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & ormqr_outf(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left, bool transpose, at::Tensor & out) { + return at::_ops::ormqr_out::call(self, input2, input3, left, transpose, out); +} + +// aten::ormqr(Tensor self, Tensor input2, Tensor input3, bool left=True, bool transpose=False) -> Tensor +inline at::Tensor ormqr(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left=true, bool transpose=false) { + return at::_ops::ormqr::call(self, input2, input3, left, transpose); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/permute_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/permute_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e11061ec0405a2e6413d73325ee2cb996ebe90ec --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/permute_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 permute { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::permute"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "permute(Tensor(a) self, int[] dims) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dims); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dims); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/positive_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/positive_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2223f43a5925e6df9445b997c231765c6814df60 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/positive_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 positive(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/pow_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/pow_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..036bfc2116166dc587516768b73662991206605a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/pow_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,27 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 pow(const at::Tensor & self, const at::Tensor & exponent); +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(const at::Tensor & self, const at::Scalar & exponent); +TORCH_API at::Tensor & pow_(at::Tensor & self, const at::Scalar & exponent); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/prelu_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/prelu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bb0fb2c3fbde8d13771008eb4ecc61ffd08421d2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/prelu_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 { + 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"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "prelu(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/put_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/put_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d52570b662c012d4b85b2ed292d7ba1abe029f41 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/put_meta_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & put_(at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/q_zero_point_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/q_zero_point_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6ccc48a690f2aeb0d4a1e1c9d3bb0012ded7ffdc --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/q_zero_point_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 int64_t q_zero_point_quant(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_channel_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_channel_native.h new file mode 100644 index 0000000000000000000000000000000000000000..543b8ad39015f0cf7b18df4ae5b1d46205ed3e0b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_channel_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_channel_out(const at::Tensor & self, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::ScalarType dtype, at::Tensor & out); +TORCH_API at::Tensor quantize_per_channel(const at::Tensor & self, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::ScalarType dtype); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic.h b/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic.h new file mode 100644 index 0000000000000000000000000000000000000000..b906eb0a51946755d0ec58bf36b67f7a83b51b17 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_dynamic.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::quantize_per_tensor_dynamic(Tensor self, ScalarType dtype, bool reduce_range) -> Tensor +inline at::Tensor quantize_per_tensor_dynamic(const at::Tensor & self, at::ScalarType dtype, bool reduce_range) { + return at::_ops::quantize_per_tensor_dynamic::call(self, dtype, reduce_range); +} + +// aten::quantize_per_tensor_dynamic.out(Tensor self, ScalarType dtype, bool reduce_range, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantize_per_tensor_dynamic_out(at::Tensor & out, const at::Tensor & self, at::ScalarType dtype, bool reduce_range) { + return at::_ops::quantize_per_tensor_dynamic_out::call(self, dtype, reduce_range, out); +} +// aten::quantize_per_tensor_dynamic.out(Tensor self, ScalarType dtype, bool reduce_range, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantize_per_tensor_dynamic_outf(const at::Tensor & self, at::ScalarType dtype, bool reduce_range, at::Tensor & out) { + return at::_ops::quantize_per_tensor_dynamic_out::call(self, dtype, reduce_range, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..61aa32cfa285db9cc027a703c4840dd0bba9ccd7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/quantize_per_tensor_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 & quantize_per_tensor_out(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype, at::Tensor & out); +TORCH_API at::Tensor quantize_per_tensor(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype); +TORCH_API at::Tensor & quantize_per_tensor_tensor_qparams_out(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype, at::Tensor & out); +TORCH_API at::Tensor quantize_per_tensor_tensor_qparams(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype); +TORCH_API void quantize_per_tensor_tensors_out(at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype, at::TensorList out); +TORCH_API ::std::vector quantize_per_tensor_list_cpu(at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_gru_cell_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_gru_cell_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f21bf5affbb1d009cec2fb90a4e869ff3e9cb590 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_gru_cell_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 quantized_gru_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 native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool1d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_pool1d.h new file mode 100644 index 0000000000000000000000000000000000000000..2affde5d2ed4b2cb40b235f8e52073d51a560ebc --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_max_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::quantized_max_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> Tensor +inline at::Tensor quantized_max_pool1d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::quantized_max_pool1d::call(self, kernel_size, stride, padding, dilation, ceil_mode); +} + +// aten::quantized_max_pool1d.out(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::quantized_max_pool1d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} +// aten::quantized_max_pool1d.out(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline 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) { + return at::_ops::quantized_max_pool1d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell.h b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_rnn_tanh_cell.h new file mode 100644 index 0000000000000000000000000000000000000000..52e7985d78fac3617b4ec76b155514ea3f03a244 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/quantized_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::quantized_rnn_tanh_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor b_ih, Tensor b_hh, Tensor packed_ih, Tensor packed_hh, Tensor col_offsets_ih, Tensor col_offsets_hh, Scalar scale_ih, Scalar scale_hh, Scalar zero_point_ih, Scalar zero_point_hh) -> Tensor +inline at::Tensor quantized_rnn_tanh_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) { + return at::_ops::quantized_rnn_tanh_cell::call(input, hx, w_ih, w_hh, b_ih, b_hh, packed_ih, packed_hh, col_offsets_ih, col_offsets_hh, scale_ih, scale_hh, zero_point_ih, zero_point_hh); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/randn.h b/lib/python3.12/site-packages/torch/include/ATen/ops/randn.h new file mode 100644 index 0000000000000000000000000000000000000000..315ab32f7d812f9703a7e82512bc671e0620c0de --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/randn.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::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::randn::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randn(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::randn::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randn(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn_symint(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::randn::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randn(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::randn::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn::call(size, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randn(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn::call(size, dtype, layout, device, pin_memory); + } +} + +// aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn(at::IntArrayRef size, ::std::optional generator, at::TensorOptions options={}) { + return at::_ops::randn_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 randn(at::IntArrayRef size, ::std::optional generator, at::TensorOptions options={}) { + return at::_ops::randn_generator::call(c10::fromIntArrayRefSlow(size), generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn(at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn_generator::call(c10::fromIntArrayRefSlow(size), generator, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randn(at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn_generator::call(c10::fromIntArrayRefSlow(size), generator, dtype, layout, device, pin_memory); + } +} + +// aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options={}) { + return at::_ops::randn_generator::call(size, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randn(c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options={}) { + return at::_ops::randn_generator::call(size, generator, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn_generator::call(size, generator, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randn(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn_generator::call(size, generator, dtype, layout, device, pin_memory); + } +} + +// aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn(at::IntArrayRef size, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::randn_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 randn(at::IntArrayRef size, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::randn_names::call(c10::fromIntArrayRefSlow(size), names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn(at::IntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn_names::call(c10::fromIntArrayRefSlow(size), names, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randn(at::IntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn_names::call(c10::fromIntArrayRefSlow(size), names, dtype, layout, device, pin_memory); + } +} + +// aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::randn_names::call(size, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template >> + at::Tensor randn(c10::SymIntArrayRef size, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::randn_names::call(size, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor randn_symint(c10::SymIntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn_names::call(size, names, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randn(c10::SymIntArrayRef size, ::std::optional names, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::randn_names::call(size, names, dtype, layout, device, pin_memory); + } +} + +// aten::randn.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 randn(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::randn_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 randn(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::randn_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::randn.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 randn(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::randn_generator_with_names::call(c10::fromIntArrayRefSlow(size), generator, names, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randn(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::randn_generator_with_names::call(c10::fromIntArrayRefSlow(size), generator, names, dtype, layout, device, pin_memory); + } +} + +// aten::randn.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 randn_symint(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::randn_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 randn(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::TensorOptions options={}) { + return at::_ops::randn_generator_with_names::call(size, generator, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::randn.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 randn_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::randn_generator_with_names::call(size, generator, names, dtype, layout, device, pin_memory); +} +namespace symint { + template >> + at::Tensor randn(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::randn_generator_with_names::call(size, generator, names, dtype, layout, device, pin_memory); + } +} + +// aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::randn_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::randn_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::randn_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template >> + at::Tensor & randn_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::randn_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_symint_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::randn_out::call(size, out); +} +namespace symint { + template >> + at::Tensor & randn_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::randn_out::call(size, out); + } +} + +// aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_symint_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::randn_out::call(size, out); +} +namespace symint { + template >> + at::Tensor & randn_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::randn_out::call(size, out); + } +} + +// aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator) { + return at::_ops::randn_generator_out::call(c10::fromIntArrayRefSlow(size), generator, out); +} +namespace symint { + template >> + at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator) { + return at::_ops::randn_generator_out::call(c10::fromIntArrayRefSlow(size), generator, out); + } +} + +// aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_outf(at::IntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randn_generator_out::call(c10::fromIntArrayRefSlow(size), generator, out); +} +namespace symint { + template >> + at::Tensor & randn_outf(at::IntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randn_generator_out::call(c10::fromIntArrayRefSlow(size), generator, out); + } +} + +// aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator) { + return at::_ops::randn_generator_out::call(size, generator, out); +} +namespace symint { + template >> + at::Tensor & randn_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator) { + return at::_ops::randn_generator_out::call(size, generator, out); + } +} + +// aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_symint_outf(c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randn_generator_out::call(size, generator, out); +} +namespace symint { + template >> + at::Tensor & randn_outf(c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out) { + return at::_ops::randn_generator_out::call(size, generator, out); + } +} + +// aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, ::std::optional names) { + return at::_ops::randn_names_out::call(c10::fromIntArrayRefSlow(size), names, out); +} +namespace symint { + template >> + at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, ::std::optional names) { + return at::_ops::randn_names_out::call(c10::fromIntArrayRefSlow(size), names, out); + } +} + +// aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_outf(at::IntArrayRef size, ::std::optional names, at::Tensor & out) { + return at::_ops::randn_names_out::call(c10::fromIntArrayRefSlow(size), names, out); +} +namespace symint { + template >> + at::Tensor & randn_outf(at::IntArrayRef size, ::std::optional names, at::Tensor & out) { + return at::_ops::randn_names_out::call(c10::fromIntArrayRefSlow(size), names, out); + } +} + +// aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional names) { + return at::_ops::randn_names_out::call(size, names, out); +} +namespace symint { + template >> + at::Tensor & randn_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional names) { + return at::_ops::randn_names_out::call(size, names, out); + } +} + +// aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_symint_outf(c10::SymIntArrayRef size, ::std::optional names, at::Tensor & out) { + return at::_ops::randn_names_out::call(size, names, out); +} +namespace symint { + template >> + at::Tensor & randn_outf(c10::SymIntArrayRef size, ::std::optional names, at::Tensor & out) { + return at::_ops::randn_names_out::call(size, names, out); + } +} + +// aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator, ::std::optional names) { + return at::_ops::randn_generator_with_names_out::call(c10::fromIntArrayRefSlow(size), generator, names, out); +} +namespace symint { + template >> + at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, ::std::optional generator, ::std::optional names) { + return at::_ops::randn_generator_with_names_out::call(c10::fromIntArrayRefSlow(size), generator, names, out); + } +} + +// aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_outf(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out) { + return at::_ops::randn_generator_with_names_out::call(c10::fromIntArrayRefSlow(size), generator, names, out); +} +namespace symint { + template >> + at::Tensor & randn_outf(at::IntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out) { + return at::_ops::randn_generator_with_names_out::call(c10::fromIntArrayRefSlow(size), generator, names, out); + } +} + +// aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_symint_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names) { + return at::_ops::randn_generator_with_names_out::call(size, generator, names, out); +} +namespace symint { + template >> + at::Tensor & randn_out(at::Tensor & out, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names) { + return at::_ops::randn_generator_with_names_out::call(size, generator, names, out); + } +} + +// aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & randn_symint_outf(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out) { + return at::_ops::randn_generator_with_names_out::call(size, generator, names, out); +} +namespace symint { + template >> + at::Tensor & randn_outf(c10::SymIntArrayRef size, ::std::optional generator, ::std::optional names, at::Tensor & out) { + return at::_ops::randn_generator_with_names_out::call(size, generator, names, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/randperm_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/randperm_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..96820339ec3628828ae0f9eb497fe9acf63e4084 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/randperm_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 & randperm_out(at::Tensor & out, int64_t n, ::std::optional generator); +TORCH_API at::Tensor & randperm_outf(int64_t n, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & randperm_symint_out(at::Tensor & out, c10::SymInt n, ::std::optional generator); +TORCH_API at::Tensor & randperm_symint_outf(c10::SymInt n, ::std::optional generator, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/range_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/range_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..10f3abe30d1824e54681fb603d101e726bfe290e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/range_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 range(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step=1, at::TensorOptions options={}); +TORCH_API at::Tensor range(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor range(const at::Scalar & start, const at::Scalar & end, at::TensorOptions options={}); +TORCH_API at::Tensor range(const at::Scalar & start, const at::Scalar & end, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & range_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end); +TORCH_API at::Tensor & range_outf(const at::Scalar & start, const at::Scalar & end, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/real.h b/lib/python3.12/site-packages/torch/include/ATen/ops/real.h new file mode 100644 index 0000000000000000000000000000000000000000..b191fa0d76c2a8207b2bc92cdd366886c2eedc13 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/real.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::real(Tensor(a) self) -> Tensor(a) +inline at::Tensor real(const at::Tensor & self) { + return at::_ops::real::call(self); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2c16ddf552e3160b1ea3e7d7e6a393e014003dcd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad2d_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 reflection_pad2d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad2d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & reflection_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & reflection_pad2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & reflection_pad2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b9d92488810252e187ac75f1d72ea7da54bffc0d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/reflection_pad3d_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_reflection_pad3d_out_cpu : public at::meta::structured_reflection_pad3d { +void impl(const at::Tensor & self, at::ArrayRef padding, const at::Tensor & out); +}; +struct TORCH_API structured_reflection_pad3d_out_cuda : public at::meta::structured_reflection_pad3d { +void impl(const at::Tensor & self, at::ArrayRef padding, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/relu_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/relu_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..131b920493179ecfcb882e72806ae09291c8758a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/relu_meta_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & relu_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/repeat_interleave_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/repeat_interleave_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..794edd6c62ac54abcfdb9e13a3ac6a7b5e2c5fca --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/repeat_interleave_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 & repeat_interleave_out(at::Tensor & out, const at::Tensor & repeats, ::std::optional output_size=::std::nullopt); +TORCH_API at::Tensor & repeat_interleave_outf(const at::Tensor & repeats, ::std::optional output_size, at::Tensor & out); +TORCH_API at::Tensor & repeat_interleave_symint_out(at::Tensor & out, const at::Tensor & repeats, ::std::optional output_size=::std::nullopt); +TORCH_API at::Tensor & repeat_interleave_symint_outf(const at::Tensor & repeats, ::std::optional output_size, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e1eeafc52b837e26baef8f39c6b65726f835bee3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad1d_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor replication_pad1d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d.h new file mode 100644 index 0000000000000000000000000000000000000000..5fb807eebe4a148424cdb623f8bbb7a13fba225a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_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::replication_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & replication_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad2d_out::call(self, c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template >> + at::Tensor & replication_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad2d_out::call(self, c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::replication_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & replication_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::replication_pad2d_out::call(self, c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template >> + at::Tensor & replication_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::replication_pad2d_out::call(self, c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::replication_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & replication_pad2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad2d_out::call(self, padding, out); +} +namespace symint { + template >> + at::Tensor & replication_pad2d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad2d_out::call(self, padding, out); + } +} + +// aten::replication_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & replication_pad2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::replication_pad2d_out::call(self, padding, out); +} +namespace symint { + template >> + at::Tensor & replication_pad2d_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::replication_pad2d_out::call(self, padding, out); + } +} + +// aten::replication_pad2d(Tensor self, SymInt[4] padding) -> Tensor +inline at::Tensor replication_pad2d(const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad2d::call(self, c10::fromIntArrayRefSlow(padding)); +} +namespace symint { + template >> + at::Tensor replication_pad2d(const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::replication_pad2d::call(self, c10::fromIntArrayRefSlow(padding)); + } +} + +// aten::replication_pad2d(Tensor self, SymInt[4] padding) -> Tensor +inline at::Tensor replication_pad2d_symint(const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad2d::call(self, padding); +} +namespace symint { + template >> + at::Tensor replication_pad2d(const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::replication_pad2d::call(self, padding); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c4a4ee4822e042140f185268150cd019e4d3afcc --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad2d_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor replication_pad2d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad2d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & replication_pad2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d14ed35d343f131dd660727d022b66f59de970d7 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/replication_pad3d_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor replication_pad3d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad3d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..675413163764cd6e6ebf8109111acdad8f010a23 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/reshape_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 reshape { + 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::reshape"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "reshape(Tensor(a) self, SymInt[] shape) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef shape); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef shape); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu_cell.h b/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu_cell.h new file mode 100644 index 0000000000000000000000000000000000000000..63bd164e38e82ab95b4ec29edd6e0ba4255f1125 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu_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_relu_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor +inline at::Tensor rnn_relu_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_relu_cell::call(input, hx, w_ih, w_hh, b_ih, b_hh); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu_cell_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/rnn_relu_cell_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0b4f2fdaabcac50c87b320aa114722ec3ded3a10 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/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 rnn_relu_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={}); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/row_stack_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/row_stack_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..02f55630443a6e0595484d987cc9ea27389b75ff --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/row_stack_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 row_stack { + 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::row_stack"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "row_stack(Tensor[] tensors) -> Tensor"; + static at::Tensor call(at::TensorList tensors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +struct TORCH_API row_stack_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::row_stack"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "row_stack.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/rrelu.h b/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu.h new file mode 100644 index 0000000000000000000000000000000000000000..ef9c7264588726e923b92aea6f2cb4b6e11ee1db --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu.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::rrelu(Tensor self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor +inline at::Tensor rrelu(const at::Tensor & self, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, ::std::optional generator=::std::nullopt) { + return at::_ops::rrelu::call(self, lower, upper, training, generator); +} + +// aten::rrelu_(Tensor(a!) self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!) +inline at::Tensor & rrelu_(at::Tensor & self, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, ::std::optional generator=::std::nullopt) { + return at::_ops::rrelu_::call(self, lower, upper, training, generator); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise.h b/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise.h new file mode 100644 index 0000000000000000000000000000000000000000..a1f68ca981b915b33375e4ac3cb9ab96d1c0a55f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/rrelu_with_noise.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::rrelu_with_noise.out(Tensor self, Tensor(b!) noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rrelu_with_noise_out(at::Tensor & out, const at::Tensor & self, at::Tensor & noise, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, ::std::optional generator=::std::nullopt) { + return at::_ops::rrelu_with_noise_out::call(self, noise, lower, upper, training, generator, out); +} +// aten::rrelu_with_noise.out(Tensor self, Tensor(b!) noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & rrelu_with_noise_outf(const at::Tensor & self, at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, ::std::optional generator, at::Tensor & out) { + return at::_ops::rrelu_with_noise_out::call(self, noise, lower, upper, training, generator, out); +} + +// aten::rrelu_with_noise(Tensor self, Tensor(b!) noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor +inline at::Tensor rrelu_with_noise(const at::Tensor & self, at::Tensor & noise, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, ::std::optional generator=::std::nullopt) { + return at::_ops::rrelu_with_noise::call(self, noise, lower, upper, training, generator); +} + +// aten::rrelu_with_noise_(Tensor(a!) self, Tensor(b!) noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!) +inline at::Tensor & rrelu_with_noise_(at::Tensor & self, at::Tensor & noise, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, ::std::optional generator=::std::nullopt) { + return at::_ops::rrelu_with_noise_::call(self, noise, lower, upper, training, generator); +} + +// aten::rrelu_with_noise_functional(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> (Tensor, Tensor noise_out) +inline ::std::tuple rrelu_with_noise_functional(const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, ::std::optional generator=::std::nullopt) { + return at::_ops::rrelu_with_noise_functional::call(self, noise, lower, upper, training, generator); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_native.h new file mode 100644 index 0000000000000000000000000000000000000000..14b34e847000cd95f7eb3db5e0c92baa0dedbbf4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/rsqrt_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_rsqrt_out : public at::meta::structured_rsqrt { +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/select_backward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/select_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..36081d401811989a9b6d169d085d619be753025b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/select_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::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index) -> Tensor +inline at::Tensor select_backward(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t index) { + return at::_ops::select_backward::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, index); +} +namespace symint { + template >> + at::Tensor select_backward(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t index) { + return at::_ops::select_backward::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, index); + } +} + +// aten::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index) -> Tensor +inline at::Tensor select_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index) { + return at::_ops::select_backward::call(grad_output, input_sizes, dim, index); +} +namespace symint { + template >> + at::Tensor select_backward(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index) { + return at::_ops::select_backward::call(grad_output, input_sizes, dim, index); + } +} + +// aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_backward_out(at::Tensor & out, const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t index) { + return at::_ops::select_backward_out::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, index, out); +} +namespace symint { + template >> + at::Tensor & select_backward_out(at::Tensor & out, const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t index) { + return at::_ops::select_backward_out::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, index, out); + } +} + +// aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_backward_outf(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t index, at::Tensor & out) { + return at::_ops::select_backward_out::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, index, out); +} +namespace symint { + template >> + at::Tensor & select_backward_outf(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t dim, int64_t index, at::Tensor & out) { + return at::_ops::select_backward_out::call(grad_output, c10::fromIntArrayRefSlow(input_sizes), dim, index, out); + } +} + +// aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_backward_symint_out(at::Tensor & out, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index) { + return at::_ops::select_backward_out::call(grad_output, input_sizes, dim, index, out); +} +namespace symint { + template >> + at::Tensor & select_backward_out(at::Tensor & out, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index) { + return at::_ops::select_backward_out::call(grad_output, input_sizes, dim, index, out); + } +} + +// aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index, at::Tensor & out) { + return at::_ops::select_backward_out::call(grad_output, input_sizes, dim, index, out); +} +namespace symint { + template >> + at::Tensor & select_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt index, at::Tensor & out) { + return at::_ops::select_backward_out::call(grad_output, input_sizes, dim, index, out); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/selu_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/selu_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7631d915124bc98cdc3c3f1ad4c2478203efbab1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/selu_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 selu { + 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::selu"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "selu(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 selu_ { + 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::selu_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "selu_(Tensor(a!) self) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/set_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/set_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..13f69245b630f17899fc3ae9884b4f2de4233469 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/set_compositeexplicitautograd_dispatch.h @@ -0,0 +1,37 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 set(const at::Tensor & self, at::Storage source); +TORCH_API at::Tensor & set_out(at::Tensor & out, const at::Tensor & self, at::Storage source); +TORCH_API at::Tensor & set_outf(const at::Tensor & self, at::Storage source, at::Tensor & out); +TORCH_API at::Tensor set(const at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor set_symint(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor & set_out(at::Tensor & out, const at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor & set_outf(const at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out); +TORCH_API at::Tensor & set_symint_out(at::Tensor & out, const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor & set_symint_outf(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); +TORCH_API at::Tensor set(const at::Tensor & self, const at::Tensor & source); +TORCH_API at::Tensor & set_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & source); +TORCH_API at::Tensor & set_outf(const at::Tensor & self, const at::Tensor & source, at::Tensor & out); +TORCH_API at::Tensor set(const at::Tensor & self); +TORCH_API at::Tensor & set_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & set_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/set_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/set_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f58ebc53bc74b0ce6739cf925d4c4ffe578d32dd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/set_meta_dispatch.h @@ -0,0 +1,27 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 & set_(at::Tensor & self, at::Storage source); +TORCH_API at::Tensor & set_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); +TORCH_API at::Tensor & set__symint(at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride={}); +TORCH_API at::Tensor & set_(at::Tensor & self, const at::Tensor & source); +TORCH_API at::Tensor & set_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sgn_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sgn_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..d2c392205d64631bdc49537127c701710dc3ff86 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sgn_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_sgn : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ba92dc0c314e812358d21ef4b3feec5b9774f356 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_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 sigmoid_backward(const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & sigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & sigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_meta.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..0734d068594abfa2809432e7a97814e67cf51767 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_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_sigmoid : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aaa3969d45fe5c17b787504685b8aa96c7ce27db --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sigmoid_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 sigmoid(const at::Tensor & self); +TORCH_API at::Tensor & sigmoid_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sigmoid_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sigmoid_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward.h b/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..a930734c23752f6e1901dbfab432282192044cd3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::silu_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & silu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::silu_backward_grad_input::call(grad_output, self, grad_input); +} +// aten::silu_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & silu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input) { + return at::_ops::silu_backward_grad_input::call(grad_output, self, grad_input); +} + +// aten::silu_backward(Tensor grad_output, Tensor self) -> Tensor +inline at::Tensor silu_backward(const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::silu_backward::call(grad_output, self); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dd254bf37ebfe3b285cf199aa223434d9360615a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/silu_backward_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor silu_backward(const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & silu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & silu_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/sin_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sin_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..996e28f921ece8d52101b984686e1b6745694e3b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sin_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 sin(const at::Tensor & self); +TORCH_API at::Tensor & sin_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/slogdet_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/slogdet_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4569985bdfd9f15f89cf61640e5bc414de0187a8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/slogdet_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 slogdet(const at::Tensor & self); +TORCH_API ::std::tuple slogdet_out(at::Tensor & sign, at::Tensor & logabsdet, const at::Tensor & self); +TORCH_API ::std::tuple slogdet_outf(const at::Tensor & self, at::Tensor & sign, at::Tensor & logabsdet); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8881d16c239adc9dfe354024d6d1466a3f030150 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_dilated3d_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor slow_conv_dilated3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor slow_conv_dilated3d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0c464e0aa96934e63d4afcf3e162ecd92771e1d8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/slow_conv_transpose2d_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 slow_conv_transpose2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor slow_conv_transpose2d_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), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); +TORCH_API at::Tensor & slow_conv_transpose2d_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, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); +TORCH_API at::Tensor & slow_conv_transpose2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out); +TORCH_API at::Tensor & slow_conv_transpose2d_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), c10::SymIntArrayRef output_padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1)); +TORCH_API at::Tensor & slow_conv_transpose2d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef dilation, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/softmax_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/softmax_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..16ed380b90449e359bea0b8031fe0dd94b5915a6 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/softmax_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 softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor softmax(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..522c4415031265b873780fd7b180a7703eb3b036 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/softplus_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 softplus_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::softplus_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "softplus_backward.grad_input(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, at::Tensor & grad_input); +}; + +struct TORCH_API softplus_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::softplus_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "softplus_backward(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold) -> Tensor"; + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7355061cb53a17756b4d059d882f272e7c0aa9f3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/softshrink_backward_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_softshrink_backward_out : public at::meta::structured_softshrink_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_bsc_tensor_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_bsc_tensor_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d2a1c0962e519d11fc50552a41d032c25fe78285 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_bsc_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_bsc_tensor(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(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); +TORCH_API at::Tensor sparse_bsc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::TensorOptions options); +TORCH_API at::Tensor sparse_bsc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_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_compressed_tensor_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_compressed_tensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..def74de55dca09972a4624e312706beba1c3707c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_compressed_tensor_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_compressed_tensor_comp_plain_value_size { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, ::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_compressed_tensor"; + static constexpr const char* overload_name = "comp_plain_value_size"; + static constexpr const char* schema_str = "sparse_compressed_tensor.comp_plain_value_size(Tensor compressed_indices, Tensor plain_indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor"; + static at::Tensor call(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API sparse_compressed_tensor_comp_plain_value { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, ::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_compressed_tensor"; + static constexpr const char* overload_name = "comp_plain_value"; + static constexpr const char* schema_str = "sparse_compressed_tensor.comp_plain_value(Tensor compressed_indices, Tensor plain_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor"; + static at::Tensor call(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, ::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_csc_tensor_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_csc_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..13540329fe8936472ba2dbe84d5f0e49465209bf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sparse_csc_tensor_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_csc_tensor(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={}); +TORCH_API at::Tensor sparse_csc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, ::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/special_bessel_j1_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j1_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..300df779b2a6ce36824f30ba946fea0b638b1631 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_bessel_j1_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_j1(const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_j1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_j1_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_chebyshev_polynomial_t_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..93c8f776daf6f24878d81bd111c72552d7481a31 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_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_chebyshev_polynomial_t(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_t_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_t_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_chebyshev_polynomial_t_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..42cb5aae5e686fd8dcf846a62d80f0c2e111c95f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_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_chebyshev_polynomial_t(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_t_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_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_entr_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_entr_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..039dd3719f721552ec55ad4947932572e8dcdc70 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_entr_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_entr(const at::Tensor & self); +TORCH_API at::Tensor & special_entr_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_entr_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_erf_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_erf_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c24de7dd216da2c483a8bb819b02f16da2b91fbf --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_erf_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_erf(const at::Tensor & self); +TORCH_API at::Tensor & special_erf_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_expm1.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_expm1.h new file mode 100644 index 0000000000000000000000000000000000000000..3abca3e600b939c2f4e4f6b652b589a87ada1412 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_expm1.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_expm1(Tensor self) -> Tensor +inline at::Tensor special_expm1(const at::Tensor & self) { + return at::_ops::special_expm1::call(self); +} + +// aten::special_expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_expm1_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_expm1_out::call(self, out); +} +// aten::special_expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_expm1_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_expm1_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l.h new file mode 100644 index 0000000000000000000000000000000000000000..fc49f88888cc92f2a2578308c5727a54c5bbf75c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_laguerre_polynomial_l(Tensor x, Tensor n) -> Tensor +inline at::Tensor special_laguerre_polynomial_l(const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_laguerre_polynomial_l::call(x, n); +} + +// aten::special_laguerre_polynomial_l.x_scalar(Scalar x, Tensor n) -> Tensor +inline at::Tensor special_laguerre_polynomial_l(const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_laguerre_polynomial_l_x_scalar::call(x, n); +} + +// aten::special_laguerre_polynomial_l.n_scalar(Tensor x, Scalar n) -> Tensor +inline at::Tensor special_laguerre_polynomial_l(const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_laguerre_polynomial_l_n_scalar::call(x, n); +} + +// aten::special_laguerre_polynomial_l.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_laguerre_polynomial_l_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n) { + return at::_ops::special_laguerre_polynomial_l_out::call(x, n, out); +} +// aten::special_laguerre_polynomial_l.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_laguerre_polynomial_l_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_laguerre_polynomial_l_out::call(x, n, out); +} + +// aten::special_laguerre_polynomial_l.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_laguerre_polynomial_l_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n) { + return at::_ops::special_laguerre_polynomial_l_x_scalar_out::call(x, n, out); +} +// aten::special_laguerre_polynomial_l.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_laguerre_polynomial_l_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { + return at::_ops::special_laguerre_polynomial_l_x_scalar_out::call(x, n, out); +} + +// aten::special_laguerre_polynomial_l.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_laguerre_polynomial_l_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n) { + return at::_ops::special_laguerre_polynomial_l_n_scalar_out::call(x, n, out); +} +// aten::special_laguerre_polynomial_l.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_laguerre_polynomial_l_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { + return at::_ops::special_laguerre_polynomial_l_n_scalar_out::call(x, n, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..04aedbe51b8f90414698254408cc241fcd796460 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_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_laguerre_polynomial_l(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_laguerre_polynomial_l_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_laguerre_polynomial_l_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_log1p_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log1p_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8fa322c8682ec33497f80df70b99b45ee112ac1d --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log1p_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor special_log1p(const at::Tensor & self); +TORCH_API at::Tensor & special_log1p_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_log1p_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..72d601723e994852ecb2c272013519ae272b1ff5 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_log_ndtr_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_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 meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_logit.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_logit.h new file mode 100644 index 0000000000000000000000000000000000000000..2560b96df46005c52793587435dbc775b2ec1f5b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_logit.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_logit(Tensor self, float? eps=None) -> Tensor +inline at::Tensor special_logit(const at::Tensor & self, ::std::optional eps=::std::nullopt) { + return at::_ops::special_logit::call(self, eps); +} + +// aten::special_logit.out(Tensor self, float? eps=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_logit_out(at::Tensor & out, const at::Tensor & self, ::std::optional eps=::std::nullopt) { + return at::_ops::special_logit_out::call(self, eps, out); +} +// aten::special_logit.out(Tensor self, float? eps=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_logit_outf(const at::Tensor & self, ::std::optional eps, at::Tensor & out) { + return at::_ops::special_logit_out::call(self, eps, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7cc4edf25667439e005b2ce200a34c8f75926f67 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_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_modified_bessel_i1(const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_multigammaln.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_multigammaln.h new file mode 100644 index 0000000000000000000000000000000000000000..999f57cad76e9ae9e84d2f9ad9e1be1efbedbae9 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_multigammaln.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_multigammaln(Tensor self, int p) -> Tensor +inline at::Tensor special_multigammaln(const at::Tensor & self, int64_t p) { + return at::_ops::special_multigammaln::call(self, p); +} + +// aten::special_multigammaln.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_multigammaln_out(at::Tensor & out, const at::Tensor & self, int64_t p) { + return at::_ops::special_multigammaln_out::call(self, p, out); +} +// aten::special_multigammaln.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_multigammaln_outf(const at::Tensor & self, int64_t p, at::Tensor & out) { + return at::_ops::special_multigammaln_out::call(self, p, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_multigammaln_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_multigammaln_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..598a3e6395c5e1f7fc077e1d42d8be2413918031 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_multigammaln_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_multigammaln { + using schema = at::Tensor (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_multigammaln"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "special_multigammaln(Tensor self, int p) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p); +}; + +struct TORCH_API special_multigammaln_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::special_multigammaln"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "special_multigammaln.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtri.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtri.h new file mode 100644 index 0000000000000000000000000000000000000000..07d1f0f64f195f99144202bc322afbe57f45e8f2 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_ndtri.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_ndtri(Tensor self) -> Tensor +inline at::Tensor special_ndtri(const at::Tensor & self) { + return at::_ops::special_ndtri::call(self); +} + +// aten::special_ndtri.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_ndtri_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_ndtri_out::call(self, out); +} +// aten::special_ndtri.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_ndtri_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_ndtri_out::call(self, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..79d6ca661168ecc22559ff5cbada3250710cafb4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/special_scaled_modified_bessel_k1_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_scaled_modified_bessel_k1(const at::Tensor & x); +TORCH_API at::Tensor & special_scaled_modified_bessel_k1_out(at::Tensor & out, const at::Tensor & x); +TORCH_API at::Tensor & special_scaled_modified_bessel_k1_outf(const at::Tensor & x, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..de5d530a8cf30e1c82665705ee5d25de1647bc4b --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt_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 sqrt(const at::Tensor & self); +TORCH_API at::Tensor & sqrt_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sqrt_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sqrt_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..90848bd1d220e529fce895697ba36a6dc5463b51 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sqrt_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 sqrt(const at::Tensor & self); +TORCH_API at::Tensor & sqrt_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sqrt_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sqrt_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_copy_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9552cf530ab98a76ffc3172d6f2c68d6766f701c --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/squeeze_copy_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 squeeze_copy { + 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::squeeze_copy"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "squeeze_copy(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 squeeze_copy_dim { + using schema = at::Tensor (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze_copy"; + static constexpr const char* overload_name = "dim"; + static constexpr const char* schema_str = "squeeze_copy.dim(Tensor self, int dim) -> Tensor"; + static at::Tensor call(const at::Tensor & self, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +struct TORCH_API squeeze_copy_dims { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze_copy"; + static constexpr const char* overload_name = "dims"; + static constexpr const char* schema_str = "squeeze_copy.dims(Tensor self, int[] dim) -> Tensor"; + static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim); +}; + +struct TORCH_API squeeze_copy_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::squeeze_copy"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "squeeze_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API squeeze_copy_dim_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze_copy"; + static constexpr const char* overload_name = "dim_out"; + static constexpr const char* schema_str = "squeeze_copy.dim_out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, at::Tensor & out); +}; + +struct TORCH_API squeeze_copy_dims_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::squeeze_copy"; + static constexpr const char* overload_name = "dims_out"; + static constexpr const char* schema_str = "squeeze_copy.dims_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/stack_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/stack_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..473a1f66b86af8d9cba645b5f1a9a696e2969f3e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/stack_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 stack(at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & stack_out(at::Tensor & out, at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & stack_outf(at::TensorList tensors, int64_t dim, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/std_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/std_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..57afa6d2238732558b388d6be8e2471d7f34eb4f --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/std_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 std(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & std_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/svd_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/svd_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ded1579c82c630e6e7c4ce60e063f4e32795844 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/svd_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple svd(const at::Tensor & self, bool some=true, bool compute_uv=true); +TORCH_API ::std::tuple svd_out(at::Tensor & U, at::Tensor & S, at::Tensor & V, const at::Tensor & self, bool some=true, bool compute_uv=true); +TORCH_API ::std::tuple svd_outf(const at::Tensor & self, bool some, bool compute_uv, at::Tensor & U, at::Tensor & S, at::Tensor & V); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/swapdims_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/swapdims_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..179bb5a73ed6c9d91898be74a25fbebec9c32be1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/swapdims_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 swapdims { + using schema = at::Tensor (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::swapdims"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "swapdims(Tensor(a) self, int dim0, int dim1) -> Tensor(a)"; + static at::Tensor call(const at::Tensor & self, int64_t dim0, int64_t dim1); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1); +}; + +struct TORCH_API swapdims_ { + using schema = at::Tensor & (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::swapdims_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "swapdims_(Tensor(a!) self, int dim0, int dim1) -> Tensor(a!)"; + static at::Tensor & call(at::Tensor & self, int64_t dim0, int64_t dim1); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim0, int64_t dim1); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size.h new file mode 100644 index 0000000000000000000000000000000000000000..078f9a53f7d8d34dfc678e0fe2bd0e1f76ead97a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::sym_constrain_range_for_size(Scalar size, *, int? min=None, int? max=None) -> () +inline void sym_constrain_range_for_size(const at::Scalar & size, ::std::optional min=::std::nullopt, ::std::optional max=::std::nullopt) { + return at::_ops::sym_constrain_range_for_size::call(size, min, max); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/sym_size_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/sym_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b39fdbf7edd9698a33bdabf8df01b5a3d61e9759 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/sym_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 sym_size_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_size"; + static constexpr const char* overload_name = "int"; + static constexpr const char* schema_str = "sym_size.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/take_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/take_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..980c00e7f4bf16c41d87992e2571790f0b35d47a --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/take_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 take(const at::Tensor & self, const at::Tensor & index); +TORCH_API at::Tensor & take_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & index); +TORCH_API at::Tensor & take_outf(const at::Tensor & self, const at::Tensor & index, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/tan_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/tan_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ab10b6feef4def8c7125c3430f05ded3b563144 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/tan_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 tan(const at::Tensor & self); +TORCH_API at::Tensor & tan_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & tan_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & tan_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/tensor_split.h b/lib/python3.12/site-packages/torch/include/ATen/ops/tensor_split.h new file mode 100644 index 0000000000000000000000000000000000000000..1e13ef3bd8abdb41e7bb9e3b8e1a320cc516b176 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/tensor_split.h @@ -0,0 +1,74 @@ +#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::tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[] +inline ::std::vector tensor_split(const at::Tensor & self, int64_t sections, int64_t dim=0) { + return at::_ops::tensor_split_sections::call(self, sections, dim); +} +namespace symint { + template >> + ::std::vector tensor_split(const at::Tensor & self, int64_t sections, int64_t dim=0) { + return at::_ops::tensor_split_sections::call(self, sections, dim); + } +} + +// aten::tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[] +inline ::std::vector tensor_split_symint(const at::Tensor & self, c10::SymInt sections, int64_t dim=0) { + return at::_ops::tensor_split_sections::call(self, sections, dim); +} +namespace symint { + template >> + ::std::vector tensor_split(const at::Tensor & self, c10::SymInt sections, int64_t dim=0) { + return at::_ops::tensor_split_sections::call(self, sections, dim); + } +} + +// aten::tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[] +inline ::std::vector tensor_split(const at::Tensor & self, at::IntArrayRef indices, int64_t dim=0) { + return at::_ops::tensor_split_indices::call(self, c10::fromIntArrayRefSlow(indices), dim); +} +namespace symint { + template >> + ::std::vector tensor_split(const at::Tensor & self, at::IntArrayRef indices, int64_t dim=0) { + return at::_ops::tensor_split_indices::call(self, c10::fromIntArrayRefSlow(indices), dim); + } +} + +// aten::tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[] +inline ::std::vector tensor_split_symint(const at::Tensor & self, c10::SymIntArrayRef indices, int64_t dim=0) { + return at::_ops::tensor_split_indices::call(self, indices, dim); +} +namespace symint { + template >> + ::std::vector tensor_split(const at::Tensor & self, c10::SymIntArrayRef indices, int64_t dim=0) { + return at::_ops::tensor_split_indices::call(self, indices, dim); + } +} + +// aten::tensor_split.tensor_indices_or_sections(Tensor(a -> *) self, Tensor tensor_indices_or_sections, int dim=0) -> Tensor(a)[] +inline ::std::vector tensor_split(const at::Tensor & self, const at::Tensor & tensor_indices_or_sections, int64_t dim=0) { + return at::_ops::tensor_split_tensor_indices_or_sections::call(self, tensor_indices_or_sections, dim); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_native.h new file mode 100644 index 0000000000000000000000000000000000000000..af97f5bfa3af722ab3fb1b36133401092aaf16b3 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/threshold_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_threshold_out : public at::meta::structured_threshold { +void impl(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, const at::Tensor & out); +}; +TORCH_API at::Tensor threshold_quantized_cpu(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_backward_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4e7d221203e58040da48e652ed4a599b47abe912 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/to_mkldnn_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 to_mkldnn_backward(const at::Tensor & grad, const at::Tensor & input); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/to_padded_tensor_compositeexplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/to_padded_tensor_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..33813782147e753fa4fb05702939d39220ee80bc --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/to_padded_tensor_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 & to_padded_tensor_out(at::Tensor & out, const at::Tensor & self, double padding, at::OptionalIntArrayRef output_size=::std::nullopt); +TORCH_API at::Tensor & to_padded_tensor_outf(const at::Tensor & self, double padding, at::OptionalIntArrayRef output_size, at::Tensor & out); +TORCH_API at::Tensor & to_padded_tensor_symint_out(at::Tensor & out, const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size=::std::nullopt); +TORCH_API at::Tensor & to_padded_tensor_symint_outf(const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/trace_backward_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/trace_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5e95242aa2af6716eb71736e1bc4211e34276502 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/trace_backward_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 trace_backward(const at::Tensor & grad, at::IntArrayRef sizes); +TORCH_API at::Tensor trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_solve_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_solve_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..12d0c544b43d1434968c5c222110be8d87063a2e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/triangular_solve_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API triangular_solve_X { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, bool, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::triangular_solve"; + static constexpr const char* overload_name = "X"; + static constexpr const char* schema_str = "triangular_solve.X(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False, *, Tensor(a!) X, Tensor(b!) M) -> (Tensor(a!) solution, Tensor(b!) cloned_coefficient)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M); +}; + +struct TORCH_API triangular_solve { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::triangular_solve"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "triangular_solve(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False) -> (Tensor solution, Tensor cloned_coefficient)"; + static ::std::tuple call(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/tril_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/tril_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a1dea6f0207fbe2ed9ddf9490f6c2d6d0b1ae616 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/tril_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_tril_cpu : public at::meta::structured_tril { +void impl(const at::Tensor & self, int64_t diagonal, const at::Tensor & out); +}; +struct TORCH_API structured_tril_cuda : public at::meta::structured_tril { +void impl(const at::Tensor & self, int64_t diagonal, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aedc8efc7e51b841a7ed0630efd72e353da1e0e4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/triu_indices_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 triu_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset, ::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/unfold_native.h b/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3c442664bdeadb62319c74c64667bbfa03fb37e1 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/unfold_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 unfold(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); +} // namespace native +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/uniform_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/uniform_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..45d14193bf0691b0560665a18ef806eef408d909 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/uniform_meta_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & uniform_(at::Tensor & self, double from=0, double to=1, ::std::optional generator=::std::nullopt); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d.h new file mode 100644 index 0000000000000000000000000000000000000000..bb1eee8307ef430a7f247b25f26ae62755ddfbd4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_bicubic2d.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.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_bicubic2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_bicubic2d_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(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_bicubic2d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors); + } +} + +// aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_bicubic2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_bicubic2d_vec::call(input, output_size, align_corners, scale_factors); +} +namespace symint { + template >> + at::Tensor upsample_bicubic2d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_bicubic2d_vec::call(input, output_size, align_corners, scale_factors); + } +} + +// aten::upsample_bicubic2d.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_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_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_bicubic2d_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_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); + } +} + +// aten::upsample_bicubic2d.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_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_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_bicubic2d_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_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out); + } +} + +// aten::upsample_bicubic2d.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_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_out::call(self, output_size, align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_bicubic2d_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_out::call(self, output_size, align_corners, scales_h, scales_w, out); + } +} + +// aten::upsample_bicubic2d.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_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_out::call(self, output_size, align_corners, scales_h, scales_w, out); +} +namespace symint { + template >> + at::Tensor & upsample_bicubic2d_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_out::call(self, output_size, align_corners, scales_h, scales_w, out); + } +} + +// aten::upsample_bicubic2d(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_bicubic2d(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::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor upsample_bicubic2d(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::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w); + } +} + +// aten::upsample_bicubic2d(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_bicubic2d_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::call(self, output_size, align_corners, scales_h, scales_w); +} +namespace symint { + template >> + at::Tensor upsample_bicubic2d(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::call(self, output_size, align_corners, scales_h, scales_w); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d.h new file mode 100644 index 0000000000000000000000000000000000000000..70a9306600de7a04491a4163eba0314913eea764 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d.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_linear1d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_linear1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_linear1d_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_linear1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_linear1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors); + } +} + +// aten::upsample_linear1d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor +inline at::Tensor upsample_linear1d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_linear1d_vec::call(input, output_size, align_corners, scale_factors); +} +namespace symint { + template >> + at::Tensor upsample_linear1d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors) { + return at::_ops::upsample_linear1d_vec::call(input, output_size, align_corners, scale_factors); + } +} + +// aten::upsample_linear1d.out(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_linear1d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales, out); +} +namespace symint { + template >> + at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_linear1d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales, out); + } +} + +// aten::upsample_linear1d.out(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_linear1d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales, at::Tensor & out) { + return at::_ops::upsample_linear1d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales, out); +} +namespace symint { + template >> + at::Tensor & upsample_linear1d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales, at::Tensor & out) { + return at::_ops::upsample_linear1d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales, out); + } +} + +// aten::upsample_linear1d.out(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_linear1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_linear1d_out::call(self, output_size, align_corners, scales, out); +} +namespace symint { + template >> + at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_linear1d_out::call(self, output_size, align_corners, scales, out); + } +} + +// aten::upsample_linear1d.out(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & upsample_linear1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales, at::Tensor & out) { + return at::_ops::upsample_linear1d_out::call(self, output_size, align_corners, scales, out); +} +namespace symint { + template >> + at::Tensor & upsample_linear1d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales, at::Tensor & out) { + return at::_ops::upsample_linear1d_out::call(self, output_size, align_corners, scales, out); + } +} + +// aten::upsample_linear1d(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None) -> Tensor +inline at::Tensor upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_linear1d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales); +} +namespace symint { + template >> + at::Tensor upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_linear1d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales); + } +} + +// aten::upsample_linear1d(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None) -> Tensor +inline at::Tensor upsample_linear1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_linear1d::call(self, output_size, align_corners, scales); +} +namespace symint { + template >> + at::Tensor upsample_linear1d(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales=::std::nullopt) { + return at::_ops::upsample_linear1d::call(self, output_size, align_corners, scales); + } +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d5ef04bfd8f3468aa02ebbd8080636abf125ae14 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_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_linear1d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_linear1d_backward"; + static constexpr const char* overload_name = "grad_input"; + static constexpr const char* schema_str = "upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=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, 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, at::Tensor & grad_input); +}; + +struct TORCH_API upsample_linear1d_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + static constexpr const char* name = "aten::upsample_linear1d_backward"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "upsample_linear1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=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); + 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); +}; + +}} // namespace at::_ops diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_compositeimplicitautograd_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64362c9433849e1832bbbbdd11465a4c9edb1ace --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_linear1d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor upsample_linear1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); +TORCH_API at::Tensor upsample_linear1d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional> scale_factors); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d03fd79c0fe51a2015afa6fc0eb2a08d793e5ec --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest2d_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor upsample_nearest2d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_nearest2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::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/upsample_nearest3d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4c4973b8a3eed7aa40215b8164c873090f315132 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_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_nearest3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_nearest3d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::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_nearest3d_backward_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..61ac4bb2861e9cc6ed0d5031c3da86e66bd39714 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_nearest3d_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_nearest3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_nearest3d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_nearest3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_nearest3d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::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_trilinear3d_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0f085020b38f330728f9012051b52549f895556e --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/upsample_trilinear3d_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_trilinear3d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_trilinear3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_trilinear3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/var_mean_cpu_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/var_mean_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f95f48ebc19c5d4fe01699220a69d4881658e8c4 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/var_mean_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 var_mean(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false); + +} // namespace cpu +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/vdot.h b/lib/python3.12/site-packages/torch/include/ATen/ops/vdot.h new file mode 100644 index 0000000000000000000000000000000000000000..c34232a9a26082bf1ab04b93d3ae19d58f3eedbd --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/vdot.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::vdot(Tensor self, Tensor other) -> Tensor +inline at::Tensor vdot(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::vdot::call(self, other); +} + +// aten::vdot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & vdot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::vdot_out::call(self, other, out); +} +// aten::vdot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & vdot_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::vdot_out::call(self, other, out); +} + +} diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/vdot_cuda_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/vdot_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..323c083f5b5346aac90afbb5582c2c8f68aab0de --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/vdot_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor vdot(const at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/view_meta_dispatch.h b/lib/python3.12/site-packages/torch/include/ATen/ops/view_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a03452aa9fd2a975250c202e431fe0f21012f286 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/view_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 view(const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor view_symint(const at::Tensor & self, c10::SymIntArrayRef size); + +} // namespace meta +} // namespace at diff --git a/lib/python3.12/site-packages/torch/include/ATen/ops/zero_ops.h b/lib/python3.12/site-packages/torch/include/ATen/ops/zero_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b0c40ac89872d8650aaab8a5fc9116ba750b9ec8 --- /dev/null +++ b/lib/python3.12/site-packages/torch/include/ATen/ops/zero_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 zero_ { + 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::zero_"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "zero_(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 zero_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::zero"; + static constexpr const char* overload_name = "out"; + static constexpr const char* schema_str = "zero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)"; + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API zero { + 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::zero"; + static constexpr const char* overload_name = ""; + static constexpr const char* schema_str = "zero(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