diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e6b956b448a3775fe5459fb263aad74a9da665c4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_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 + + +namespace at { +namespace native { +TORCH_API at::Tensor & _adaptive_avg_pool2d_backward_out(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor adaptive_avg_pool2d_backward_cpu(const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor adaptive_avg_pool2d_backward_cuda(const at::Tensor & grad_output, const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cslt_compress_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cslt_compress_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ff1939496e4cb07df47bb8c99e39021f4d6a5acc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cslt_compress_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cslt_compress { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cslt_compress") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cslt_compress(Tensor input) -> Tensor") + static at::Tensor call(const at::Tensor & input); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..705f92e0dae8a12bcf85b48320db4e505c88530e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cudnn_rnn_flatten_weight_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional); +TORCH_API at::Tensor _cudnn_rnn_flatten_weight_symint(at::TensorList weight_arr, int64_t weight_stride0, c10::SymInt input_size, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, bool bidirectional); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_div_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_div_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..095352971134779f667bda619fcd91c68f059789 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_div_cuda_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_div(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_div(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_(at::TensorList self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log2_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3b95be26cbc56a50b4414f495b0df5b74c9cfcc3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log2_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_log2 { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_log2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_log2(Tensor[] self) -> Tensor[]") + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log2_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_log2_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_log2_(Tensor(a!)[] self) -> ()") + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_log2_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_log2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_log2.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/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_has_same_storage_numel_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_has_same_storage_numel_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7f7c9ed1a692caaad53f4998ae533a8a2686e89e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_has_same_storage_numel_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 _has_same_storage_numel(const at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_solve_ex_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_solve_ex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b37b707251e12303f155e0b5debb0d4729d0e301 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_solve_ex_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured__linalg_solve_ex_out : public at::meta::structured__linalg_solve_ex { +void impl(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, const at::Tensor & result, const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & info); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_make_dual.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_make_dual.h new file mode 100644 index 0000000000000000000000000000000000000000..1c7316d1f1b479ab3b4ca36064f760dad92afd87 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_make_dual.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::_make_dual(Tensor(a) primal, Tensor tangent, int level) -> Tensor(a) +inline at::Tensor _make_dual(const at::Tensor & primal, const at::Tensor & tangent, int64_t level) { + return at::_ops::_make_dual::call(primal, tangent, level); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_get_ragged_idx.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_get_ragged_idx.h new file mode 100644 index 0000000000000000000000000000000000000000..fdefa93b3a780f1d0fa592e014ff2f3831fe279b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_get_ragged_idx.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_ragged_idx(Tensor self) -> int +inline int64_t _nested_get_ragged_idx(const at::Tensor & self) { + return at::_ops::_nested_get_ragged_idx::call(self); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..24e70f45bc201dadaaa9af71c3bd376217a3bc12 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_padded_dense_to_jagged_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 _padded_dense_to_jagged_forward { + using schema = at::Tensor (const at::Tensor &, at::TensorList, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_padded_dense_to_jagged_forward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_padded_dense_to_jagged_forward(Tensor dense, Tensor[] offsets, SymInt? total_L=None) -> Tensor") + static at::Tensor call(const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & dense, at::TensorList offsets, ::std::optional total_L); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9cdf00823e0902d3667b0ab0061af593207e96a7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_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_flash_attention(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false, ::std::optional scale=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_mm_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_mm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fd5e61ace9b23c167a14de3b2a2e2b962d57533e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_mm_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 _scaled_mm_cuda(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scale_a, const at::Tensor & scale_b, const ::std::optional & bias={}, const ::std::optional & scale_result={}, ::std::optional out_dtype=::std::nullopt, bool use_fast_accum=false); +TORCH_API at::Tensor & _scaled_mm_out_cuda(const at::Tensor & self, const at::Tensor & mat2, const at::Tensor & scale_a, const at::Tensor & scale_b, const ::std::optional & bias, const ::std::optional & scale_result, ::std::optional out_dtype, bool use_fast_accum, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c0da4e941db5590b372270ca7249e6803457c72b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_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 _sparse_coo_tensor_with_dims(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, at::TensorOptions options); +TORCH_API at::Tensor _sparse_coo_tensor_with_dims(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_mm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_mm.h new file mode 100644 index 0000000000000000000000000000000000000000..05167846116363b3d6554cd21ec7f8e067e2277e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_mm.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::_sparse_mm(Tensor sparse, Tensor dense) -> Tensor +inline at::Tensor _sparse_mm(const at::Tensor & sparse, const at::Tensor & dense) { + return at::_ops::_sparse_mm::call(sparse, dense); +} + +// aten::_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor +inline at::Tensor _sparse_mm(const at::Tensor & sparse, const at::Tensor & dense, c10::string_view reduce) { + return at::_ops::_sparse_mm_reduce::call(sparse, dense, reduce); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_mm_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..52fdbb77a2791be1ff146fab6effbbee7d600695 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_mm_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_mm(const at::Tensor & mat1, const at::Tensor & mat1_meta, const at::Tensor & mat2, ::std::optional out_dtype=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_standard_gamma_grad_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_standard_gamma_grad_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1283483fa2b049407686c413d091844c0581cfd3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_standard_gamma_grad_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _standard_gamma_grad(const at::Tensor & self, const at::Tensor & output); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse.h new file mode 100644 index 0000000000000000000000000000000000000000..13b6b25f5636fa4e964a1190135c4895e8d9fcaf --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse.h @@ -0,0 +1,43 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_to_sparse.sparse_dim_out(Tensor self, int sparse_dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_out(at::Tensor & out, const at::Tensor & self, int64_t sparse_dim) { + return at::_ops::_to_sparse_sparse_dim_out::call(self, sparse_dim, out); +} +// aten::_to_sparse.sparse_dim_out(Tensor self, int sparse_dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_outf(const at::Tensor & self, int64_t sparse_dim, at::Tensor & out) { + return at::_ops::_to_sparse_sparse_dim_out::call(self, sparse_dim, out); +} + +// aten::_to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_out(at::Tensor & out, const at::Tensor & self, ::std::optional layout=::std::nullopt, at::OptionalIntArrayRef blocksize=::std::nullopt, ::std::optional dense_dim=::std::nullopt) { + return at::_ops::_to_sparse_out::call(self, layout, blocksize, dense_dim, out); +} +// aten::_to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_outf(const at::Tensor & self, ::std::optional layout, at::OptionalIntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out) { + return at::_ops::_to_sparse_out::call(self, layout, blocksize, dense_dim, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d9d0139be0eb2077b1ac6ff83720b2f8093aed6d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_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 _to_sparse_semi_structured(const at::Tensor & dense); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unpack_dual_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unpack_dual_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4c07d20acdd24bad9fb38b9ed53797ef3a4796ae --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unpack_dual_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 _unpack_dual(const at::Tensor & dual, int64_t level); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..60ff1770aa2855e9eff152b72c08c29b6d28b325 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_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_bilinear2d_aa_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_bilinear2d_aa_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..297db4dc307448bc44d48d7eeb9a97ff8553e828 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_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_exact2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors); +struct TORCH_API structured__upsample_nearest_exact2d_out_cpu : public at::meta::structured__upsample_nearest_exact2d { +void impl(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +struct TORCH_API structured__upsample_nearest_exact2d_out_cuda : public at::meta::structured__upsample_nearest_exact2d { +void impl(const at::Tensor & self, at::ArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & out); +}; +TORCH_API at::Tensor _upsample_nearest_exact2d_quantized_cpu(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c5ee0d44b8317c41240c5dc1e23be768b209d3a7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_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_nearest_exact3d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_upsample_nearest_exact3d_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "grad_input") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_upsample_nearest_exact3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +}; + +struct TORCH_API _upsample_nearest_exact3d_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_upsample_nearest_exact3d_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_upsample_nearest_exact3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8ea029f6584f875276cb4b8f1a64d74b88a3df4a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_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 _weight_int4pack_mm_cpu(const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros); +TORCH_API at::Tensor _weight_int4pack_mm_cuda(const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/acosh_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/acosh_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..893ba418cde8351a4662feb90b5481cf9bfa277c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/acosh_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 acosh(const at::Tensor & self); +TORCH_API at::Tensor & acosh_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/avg_pool3d_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/avg_pool3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..4ae39947615552dbd4aa777ecc3c65b654fc68ab --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/avg_pool3d_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::avg_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & avg_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override) { + return at::_ops::avg_pool3d_backward_grad_input::call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, grad_input); +} +// aten::avg_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & avg_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override, at::Tensor & grad_input) { + return at::_ops::avg_pool3d_backward_grad_input::call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, grad_input); +} + +// aten::avg_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override) -> Tensor +inline at::Tensor avg_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, ::std::optional divisor_override) { + return at::_ops::avg_pool3d_backward::call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6a34f36f47fb647f8635ce4c775449a6d508c0de --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_with_counts_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 batch_norm_gather_stats_with_counts_out(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); +TORCH_API ::std::tuple batch_norm_gather_stats_with_counts_cuda(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); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cholesky_inverse_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cholesky_inverse_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..09aa5cff60273735ef73091f5f02f6f9a0f2eb37 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cholesky_inverse_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cholesky_inverse { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cholesky_inverse") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cholesky_inverse(Tensor self, bool upper=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, bool upper); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper); +}; + +struct TORCH_API cholesky_inverse_out { + using schema = at::Tensor & (const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cholesky_inverse") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cholesky_inverse.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, bool upper, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cummin_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cummin_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0b522404cf7975c19a5f2cbdb1ff504a5dd83b43 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cummin_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple cummin(const at::Tensor & self, at::Dimname dim); +TORCH_API ::std::tuple cummin_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim); +TORCH_API ::std::tuple cummin_outf(const at::Tensor & self, at::Dimname dim, at::Tensor & values, at::Tensor & indices); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ihfftn_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ihfftn_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b2c9e8c2fd5e90f7c18b6f91cf5be0ce59ce422f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ihfftn_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_ihfftn { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fft_ihfftn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ihfftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm); +}; + +struct TORCH_API fft_ihfftn_out { + using schema = const at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, ::std::optional, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fft_ihfftn") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ihfftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") + static const at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out); + static const at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, const at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/flipud_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/flipud_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7521eebf206848176fa0767cd5e09081c18d1283 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/flipud_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 flipud(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fractional_max_pool2d.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fractional_max_pool2d.h new file mode 100644 index 0000000000000000000000000000000000000000..4fde93de0aa829e352544d6df75ee3c83c8408b8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fractional_max_pool2d.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.output(Tensor self, int[2] kernel_size, int[2] output_size, Tensor random_samples, *, Tensor(a!) output, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple fractional_max_pool2d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples) { + return at::_ops::fractional_max_pool2d_output::call(self, kernel_size, output_size, random_samples, output, indices); +} +// aten::fractional_max_pool2d.output(Tensor self, int[2] kernel_size, int[2] output_size, Tensor random_samples, *, Tensor(a!) output, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple fractional_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices) { + return at::_ops::fractional_max_pool2d_output::call(self, kernel_size, output_size, random_samples, output, indices); +} + +// aten::fractional_max_pool2d(Tensor self, int[2] kernel_size, int[2] output_size, Tensor random_samples) -> (Tensor, Tensor) +inline ::std::tuple fractional_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples) { + return at::_ops::fractional_max_pool2d::call(self, kernel_size, output_size, random_samples); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gradient_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gradient_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..265467432cf6c94a1eb3866666f424cd812d91b5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gradient_ops.h @@ -0,0 +1,94 @@ +#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 gradient_scalarint { + using schema = ::std::vector (const at::Tensor &, const ::std::optional &, ::std::optional, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gradient") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "scalarint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gradient.scalarint(Tensor self, *, Scalar? spacing=None, int? dim=None, int edge_order=1) -> Tensor[]") + static ::std::vector call(const at::Tensor & self, const ::std::optional & spacing, ::std::optional dim, int64_t edge_order); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & spacing, ::std::optional dim, int64_t edge_order); +}; + +struct TORCH_API gradient_scalararray { + using schema = ::std::vector (const at::Tensor &, const at::Scalar &, at::IntArrayRef, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gradient") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "scalararray") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gradient.scalararray(Tensor self, *, Scalar spacing, int[] dim, int edge_order=1) -> Tensor[]") + static ::std::vector call(const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order); +}; + +struct TORCH_API gradient_array { + using schema = ::std::vector (const at::Tensor &, at::IntArrayRef, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gradient") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "array") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gradient.array(Tensor self, *, int[] dim, int edge_order=1) -> Tensor[]") + static ::std::vector call(const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order); +}; + +struct TORCH_API gradient_scalarrayint { + using schema = ::std::vector (const at::Tensor &, at::ArrayRef, ::std::optional, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gradient") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "scalarrayint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gradient.scalarrayint(Tensor self, *, Scalar[] spacing, int? dim=None, int edge_order=1) -> Tensor[]") + static ::std::vector call(const at::Tensor & self, at::ArrayRef spacing, ::std::optional dim, int64_t edge_order); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ArrayRef spacing, ::std::optional dim, int64_t edge_order); +}; + +struct TORCH_API gradient_scalarrayarray { + using schema = ::std::vector (const at::Tensor &, at::ArrayRef, at::IntArrayRef, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gradient") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "scalarrayarray") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gradient.scalarrayarray(Tensor self, *, Scalar[] spacing, int[] dim, int edge_order=1) -> Tensor[]") + static ::std::vector call(const at::Tensor & self, at::ArrayRef spacing, at::IntArrayRef dim, int64_t edge_order); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ArrayRef spacing, at::IntArrayRef dim, int64_t edge_order); +}; + +struct TORCH_API gradient_tensorarrayint { + using schema = ::std::vector (const at::Tensor &, at::TensorList, ::std::optional, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gradient") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "tensorarrayint") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gradient.tensorarrayint(Tensor self, *, Tensor[] spacing, int? dim=None, int edge_order=1) -> Tensor[]") + static ::std::vector call(const at::Tensor & self, at::TensorList spacing, ::std::optional dim, int64_t edge_order); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList spacing, ::std::optional dim, int64_t edge_order); +}; + +struct TORCH_API gradient_tensorarray { + using schema = ::std::vector (const at::Tensor &, at::TensorList, at::IntArrayRef, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gradient") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "tensorarray") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gradient.tensorarray(Tensor self, *, Tensor[] spacing, int[] dim, int edge_order=1) -> Tensor[]") + static ::std::vector call(const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hann_window_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hann_window_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8fcf424a82263685734bd2e9783f474e5c7f2f8c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hann_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 hann_window(int64_t window_length, at::TensorOptions options={}); +TORCH_API at::Tensor hann_window(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & hann_window_out(at::Tensor & out, int64_t window_length); +TORCH_API at::Tensor & hann_window_outf(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor hann_window(int64_t window_length, bool periodic, at::TensorOptions options={}); +TORCH_API at::Tensor hann_window(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & hann_window_out(at::Tensor & out, int64_t window_length, bool periodic); +TORCH_API at::Tensor & hann_window_outf(int64_t window_length, bool periodic, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardsigmoid_backward_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardsigmoid_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..071c9e930bf93ac1cf49abdea85fa0e551745093 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardsigmoid_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 hardsigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & hardsigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & hardsigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/infinitely_differentiable_gelu_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/infinitely_differentiable_gelu_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..6092c8e62d6ff35bcddbc9b39a93b5ce4e171883 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/infinitely_differentiable_gelu_backward.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::infinitely_differentiable_gelu_backward(Tensor grad, Tensor self) -> Tensor +inline at::Tensor infinitely_differentiable_gelu_backward(const at::Tensor & grad, const at::Tensor & self) { + return at::_ops::infinitely_differentiable_gelu_backward::call(grad, self); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/le_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/le_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..320ab4dc80b6ab137ecbd1d394857acea4ce8921 --- /dev/null +++ b/.venv/lib/python3.11/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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::le") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::le") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::le") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::le") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::le_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::le_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lgamma_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lgamma_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e9233c0a783f38427c158b2a6377d9ea081edb29 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lgamma_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor lgamma(const at::Tensor & self); +TORCH_API at::Tensor & lgamma_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cross_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cross_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7149e0c7e3711614e8157d2a6b14cd68671ce0e8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cross_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor linalg_cross(const at::Tensor & self, const at::Tensor & other, int64_t dim=-1); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ba81a25fbc914fa1837ccfa424aa4be48f54258d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_ldl_factor_ex_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API ::std::tuple linalg_ldl_factor_ex(const at::Tensor & self, bool hermitian=false, bool check_errors=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_svd.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_svd.h new file mode 100644 index 0000000000000000000000000000000000000000..542f49f14fabb2154bc1b55d2a332b005e694669 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_svd.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linalg_svd(Tensor A, bool full_matrices=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh) +inline ::std::tuple linalg_svd(const at::Tensor & A, bool full_matrices=true, ::std::optional driver=::std::nullopt) { + return at::_ops::linalg_svd::call(A, full_matrices, driver); +} + +// aten::linalg_svd.U(Tensor A, bool full_matrices=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) +inline ::std::tuple linalg_svd_out(at::Tensor & U, at::Tensor & S, at::Tensor & Vh, const at::Tensor & A, bool full_matrices=true, ::std::optional driver=::std::nullopt) { + return at::_ops::linalg_svd_U::call(A, full_matrices, driver, U, S, Vh); +} +// aten::linalg_svd.U(Tensor A, bool full_matrices=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) +inline ::std::tuple linalg_svd_outf(const at::Tensor & A, bool full_matrices, ::std::optional driver, at::Tensor & U, at::Tensor & S, at::Tensor & Vh) { + return at::_ops::linalg_svd_U::call(A, full_matrices, driver, U, S, Vh); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_vecdot_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_vecdot_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8aaa570fcec57b70ea8626cc9eebe62acb39aafc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_vecdot_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor linalg_vecdot(const at::Tensor & x, const at::Tensor & y, int64_t dim=-1); +TORCH_API at::Tensor & linalg_vecdot_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & y, int64_t dim=-1); +TORCH_API at::Tensor & linalg_vecdot_outf(const at::Tensor & x, const at::Tensor & y, int64_t dim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp2_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp2_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ff8b8d60632394a8aee5908179e552ede62f34fd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp2_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor logaddexp2(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a03fe4e01b22c0214234bb89a3077c92808fda56 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp_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 logaddexp(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logaddexp_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mT.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mT.h new file mode 100644 index 0000000000000000000000000000000000000000..dcf67023b797514ea81c19333f461ddfd4348a7b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mT.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/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/matmul_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/matmul_native.h new file mode 100644 index 0000000000000000000000000000000000000000..efe89f5b0f0056e41cac05dc5e67359e07080fdb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/matmul_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 matmul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & matmul_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor matmul_nested(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & matmul_out_nested(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ce9ae3041d664f991cc4f62a4a6697c5595f5d3f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API mkldnn_linear_backward_weights { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_linear_backward_weights") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_linear_backward_weights(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined); +}; + +struct TORCH_API mkldnn_linear_backward_weights_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_linear_backward_weights") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_linear_backward_weights.out(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..185434c66554c7fa8089ff02b69c066a9d3a2af6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API mkldnn_rnn_layer_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_rnn_layer_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_rnn_layer_backward(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace); +}; + +struct TORCH_API mkldnn_rnn_layer_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_rnn_layer_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_rnn_layer_backward.out(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5, Tensor(g!) out6) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!))") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & weight4, const at::Tensor & hx_, const at::Tensor & cx_tmp, const at::Tensor & output, const at::Tensor & hy_, const at::Tensor & cy_, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, bool reverse, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool train, bool bidirectional, at::IntArrayRef batch_sizes, bool batch_first, const at::Tensor & workspace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, at::Tensor & out5, at::Tensor & out6); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multinomial_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multinomial_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2663befee9ab6c38c081951058382cba570a5cea --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multinomial_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 multinomial(const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, int64_t num_samples, bool replacement=false, ::std::optional generator=::std::nullopt); +TORCH_API at::Tensor & multinomial_outf(const at::Tensor & self, int64_t num_samples, bool replacement, ::std::optional generator, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ne_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ne_native.h new file mode 100644 index 0000000000000000000000000000000000000000..deb12e1e270426b1721405c369a83f6cfccf3771 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ne_native.h @@ -0,0 +1,30 @@ +#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_ne_Scalar_out : public at::meta::structured_ne_Scalar { +void impl(const at::Tensor & self, const at::Scalar & other, const at::Tensor & out); +}; +TORCH_API at::Tensor ne_quantized_cpu(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & ne_out_quantized_cpu(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +struct TORCH_API structured_ne_Tensor_out : public at::meta::structured_ne_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +TORCH_API at::Tensor ne_quantized_cpu(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & ne_out_quantized_cpu(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/neg.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/neg.h new file mode 100644 index 0000000000000000000000000000000000000000..0fa59dd0f6250499c1f3c4842ee8ee3cfd929948 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/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::neg(Tensor self) -> Tensor +inline at::Tensor neg(const at::Tensor & self) { + return at::_ops::neg::call(self); +} + +// aten::neg_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & neg_(at::Tensor & self) { + return at::_ops::neg_::call(self); +} + +// aten::neg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & neg_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::neg_out::call(self, out); +} +// aten::neg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & neg_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::neg_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/poisson_nll_loss_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/poisson_nll_loss_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9536452bfa967eb81258460171bcb32e068f927f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/poisson_nll_loss_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 poisson_nll_loss(const at::Tensor & input, const at::Tensor & target, bool log_input, bool full, double eps, int64_t reduction); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/promote_types.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/promote_types.h new file mode 100644 index 0000000000000000000000000000000000000000..537c9ca0fa63f38c586fd5a0eee4b7e34b5fa347 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/promote_types.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::promote_types(ScalarType type1, ScalarType type2) -> ScalarType +inline at::ScalarType promote_types(at::ScalarType type1, at::ScalarType type2) { + return at::_ops::promote_types::call(type1, type2); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/q_per_channel_zero_points_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/q_per_channel_zero_points_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d878bd9311afc3195d7c7f9b81bec472e3312a67 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/q_per_channel_zero_points_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 & q_per_channel_zero_points_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor q_per_channel_zero_points(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randint_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randint_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dbd511d2aa079b693174bca4c0a7d4557c6142a5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randint_compositeexplicitautograd_dispatch.h @@ -0,0 +1,54 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these 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 randint(int64_t high, at::IntArrayRef size, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size); +TORCH_API at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt high, c10::SymIntArrayRef size); +TORCH_API at::Tensor & randint_symint_outf(c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint(int64_t high, at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint_symint(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & randint_symint_outf(c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size); +TORCH_API at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size); +TORCH_API at::Tensor & randint_symint_outf(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::TensorOptions options=at::kLong); +TORCH_API at::Tensor randint_symint(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, ::std::optional generator, at::Tensor & out); +TORCH_API at::Tensor & randint_symint_out(at::Tensor & out, c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator); +TORCH_API at::Tensor & randint_symint_outf(c10::SymInt low, c10::SymInt high, c10::SymIntArrayRef size, ::std::optional generator, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/remainder_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/remainder_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f867079999f810db83861c29100c60e9ba721aaa --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/remainder_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_remainder_Tensor : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/replication_pad3d_backward_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/replication_pad3d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..de8337e6364af2fc66c1834def206fecc3da2690 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/replication_pad3d_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 replication_pad3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad3d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); +TORCH_API at::Tensor & replication_pad3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_backward_symint_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/replication_pad3d_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/replication_pad3d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..448b656bd8987037bf9e9be7f1e8176ce7420ab7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/replication_pad3d_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor replication_pad3d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad3d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & replication_pad3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding); +TORCH_API at::Tensor & replication_pad3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/set_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/set_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8da31886ae5e94c8da571bf2de4a096dab400078 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/set_ops.h @@ -0,0 +1,160 @@ +#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 set__source_Storage { + using schema = at::Tensor & (at::Tensor &, at::Storage); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Storage") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set_.source_Storage(Tensor(a!) self, Storage source) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, at::Storage source); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Storage source); +}; + +struct TORCH_API set__source_Storage_storage_offset { + using schema = at::Tensor & (at::Tensor &, at::Storage, c10::SymInt, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Storage_storage_offset") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set_.source_Storage_storage_offset(Tensor(a!) self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); +}; + +struct TORCH_API set__source_Tensor_storage_offset { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, c10::SymInt, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Tensor_storage_offset") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set_.source_Tensor_storage_offset(Tensor(a!) self, Tensor source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); +}; + +struct TORCH_API set__source_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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set_.source_Tensor(Tensor(a!) self, Tensor source) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & source); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & source); +}; + +struct TORCH_API set_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set_(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 set_source_Storage_out { + using schema = at::Tensor & (const at::Tensor &, at::Storage, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Storage_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set.source_Storage_out(Tensor self, Storage source, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Storage source, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Storage source, at::Tensor & out); +}; + +struct TORCH_API set_source_Storage { + using schema = at::Tensor (const at::Tensor &, at::Storage); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Storage") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set.source_Storage(Tensor self, Storage source) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::Storage source); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Storage source); +}; + +struct TORCH_API set_source_Storage_storage_offset_out { + using schema = at::Tensor & (const at::Tensor &, at::Storage, c10::SymInt, c10::SymIntArrayRef, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Storage_storage_offset_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set.source_Storage_storage_offset_out(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[], *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); +}; + +struct TORCH_API set_source_Storage_storage_offset { + using schema = at::Tensor (const at::Tensor &, at::Storage, c10::SymInt, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Storage_storage_offset") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set.source_Storage_storage_offset(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); +}; + +struct TORCH_API set_source_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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set.source_Tensor_out(Tensor self, Tensor source, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & source, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & source, at::Tensor & out); +}; + +struct TORCH_API set_source_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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "source_Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set.source_Tensor(Tensor self, Tensor source) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & source); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & source); +}; + +struct TORCH_API set_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set.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 set { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::set") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "set(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/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/silu_backward_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/silu_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..58a4faae53d0da60a7f053763381a8cb520c7418 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/silu_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 silu_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sinh_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sinh_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a1426ece7de9e946b7723c0b99c7503b825c6863 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sinh_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 sinh(const at::Tensor & self); +TORCH_API at::Tensor & sinh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sinh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinh_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slice_copy_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slice_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..182ddcf27a0ed0f50bb95ce9100bc9011cc16606 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slice_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor slice_copy(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, int64_t step=1); +TORCH_API at::Tensor slice_copy_symint(const at::Tensor & self, int64_t dim=0, ::std::optional start=::std::nullopt, ::std::optional end=::std::nullopt, c10::SymInt step=1); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_bsc_tensor_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_bsc_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..01aef6ceaafc9e15d0da9612ebc6182d9b285275 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_bsc_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_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, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_bessel_j1.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_bessel_j1.h new file mode 100644 index 0000000000000000000000000000000000000000..2e91ac23269436c10a786070131843a75888539a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_bessel_j1.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_bessel_j1(Tensor self) -> Tensor +inline at::Tensor special_bessel_j1(const at::Tensor & self) { + return at::_ops::special_bessel_j1::call(self); +} + +// aten::special_bessel_j1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_bessel_j1_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_bessel_j1_out::call(self, out); +} +// aten::special_bessel_j1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_bessel_j1_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_bessel_j1_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4982c878a4da0da5a71b6a7602d5b4c557e9521f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_shifted_chebyshev_polynomial_t { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_shifted_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_shifted_chebyshev_polynomial_t(Tensor x, Tensor n) -> Tensor") + static at::Tensor call(const at::Tensor & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_t_x_scalar { + using schema = at::Tensor (const at::Scalar &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_shifted_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "x_scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_shifted_chebyshev_polynomial_t.x_scalar(Scalar x, Tensor n) -> Tensor") + static at::Tensor call(const at::Scalar & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_t_n_scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_shifted_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "n_scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_shifted_chebyshev_polynomial_t.n_scalar(Tensor x, Scalar n) -> Tensor") + static at::Tensor call(const at::Tensor & x, const at::Scalar & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_t_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_shifted_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_shifted_chebyshev_polynomial_t.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_t_x_scalar_out { + using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_shifted_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "x_scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_shifted_chebyshev_polynomial_t.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_shifted_chebyshev_polynomial_t_n_scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_shifted_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "n_scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_shifted_chebyshev_polynomial_t.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_xlog1py.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_xlog1py.h new file mode 100644 index 0000000000000000000000000000000000000000..96c3dd17edcd423fe4fdd6a77ad8db11489afd2d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_xlog1py.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_xlog1py(Tensor self, Tensor other) -> Tensor +inline at::Tensor special_xlog1py(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_xlog1py::call(self, other); +} + +// aten::special_xlog1py.self_scalar(Scalar self, Tensor other) -> Tensor +inline at::Tensor special_xlog1py(const at::Scalar & self, const at::Tensor & other) { + return at::_ops::special_xlog1py_self_scalar::call(self, other); +} + +// aten::special_xlog1py.other_scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor special_xlog1py(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::special_xlog1py_other_scalar::call(self, other); +} + +// aten::special_xlog1py.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlog1py_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_xlog1py_out::call(self, other, out); +} +// aten::special_xlog1py.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlog1py_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_xlog1py_out::call(self, other, out); +} + +// aten::special_xlog1py.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlog1py_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::special_xlog1py_self_scalar_out::call(self, other, out); +} +// aten::special_xlog1py.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlog1py_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_xlog1py_self_scalar_out::call(self, other, out); +} + +// aten::special_xlog1py.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlog1py_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::special_xlog1py_other_scalar_out::call(self, other, out); +} +// aten::special_xlog1py.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_xlog1py_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::special_xlog1py_other_scalar_out::call(self, other, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..08fb8e3d81af625a846cae37be570bcf7ef31470 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/split_with_sizes_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void split_with_sizes_copy_out(at::TensorList out, const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0); +TORCH_API void split_with_sizes_copy_outf(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out); +TORCH_API void split_with_sizes_copy_symint_out(at::TensorList out, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0); +TORCH_API void split_with_sizes_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_mean_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_mean_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..06f20fb8e9c828956a02477dc488a31a43601b07 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_mean_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 ::std::tuple std_mean(const at::Tensor & self, bool unbiased); +TORCH_API ::std::tuple std_mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim=false); +TORCH_API ::std::tuple std_mean(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim=false); +TORCH_API ::std::tuple std_mean(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction=::std::nullopt, bool keepdim=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f224606a81d984798a49152878c699b2f18a92c0 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/std_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 + + +namespace at { +namespace native { +TORCH_API at::Tensor std(const at::Tensor & self, bool unbiased=true); +TORCH_API at::Tensor std(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased=true, bool keepdim=false); +TORCH_API at::Tensor & std_out(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim, at::Tensor & out); +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(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor std_quantized_cpu(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & std_out_quantized_cpu(const at::Tensor & self, at::OptionalIntArrayRef dim, const ::std::optional & correction, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor std(const at::Tensor & self, at::DimnameList dim, bool unbiased=true, bool keepdim=false); +TORCH_API at::Tensor & std_out(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor std(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction=::std::nullopt, bool keepdim=false); +TORCH_API at::Tensor & std_out(const at::Tensor & self, at::DimnameList dim, const ::std::optional & correction, bool keepdim, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/swapdims.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/swapdims.h new file mode 100644 index 0000000000000000000000000000000000000000..f75fc73538f9717aba4355889fecbba53255860f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/swapdims.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::swapdims(Tensor(a) self, int dim0, int dim1) -> Tensor(a) +inline at::Tensor swapdims(const at::Tensor & self, int64_t dim0, int64_t dim1) { + return at::_ops::swapdims::call(self, dim0, dim1); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..659798ef03d981cd46f4200ab982a15bfb6e05e5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_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 threshold_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::threshold_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "grad_input") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "threshold_backward.grad_input(Tensor grad_output, Tensor self, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, 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 & threshold, at::Tensor & grad_input); +}; + +struct TORCH_API threshold_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::threshold_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "threshold_backward(Tensor grad_output, Tensor self, Scalar threshold) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8445a7e500683a99d64d60e761dd0d963b18e43f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold_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 threshold(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +TORCH_API at::Tensor & threshold_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); +TORCH_API at::Tensor & threshold_outf(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & threshold_(at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/to_dense_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/to_dense_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a6527d51fc80eefd9c3a5829874ae15bd478a7de --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/to_dense_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_dense_backward(const at::Tensor & grad, const at::Tensor & input, ::std::optional masked_grad=::std::nullopt); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trace_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trace_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..0742824eabbb02c6029fb9c409af0adc668ce826 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trace_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::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor +inline at::Tensor trace_backward(const at::Tensor & grad, at::IntArrayRef sizes) { + return at::_ops::trace_backward::call(grad, c10::fromIntArrayRefSlow(sizes)); +} +namespace symint { + template ::value>> + at::Tensor trace_backward(const at::Tensor & grad, at::IntArrayRef sizes) { + return at::_ops::trace_backward::call(grad, c10::fromIntArrayRefSlow(sizes)); + } +} + +// aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor +inline at::Tensor trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes) { + return at::_ops::trace_backward::call(grad, sizes); +} +namespace symint { + template ::value>> + at::Tensor trace_backward(const at::Tensor & grad, c10::SymIntArrayRef sizes) { + return at::_ops::trace_backward::call(grad, sizes); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold_copy_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..71d82e0d1412033137033691016d71f3209630e6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unfold_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 unfold_copy { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::unfold_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); +}; + +struct TORCH_API unfold_copy_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::unfold_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unique_consecutive_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unique_consecutive_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..485a121dcbf04b8d22a7b1f977d5d38144408ecd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/unique_consecutive_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 unique_consecutive(const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional dim=::std::nullopt); + +} // namespace cuda +} // namespace at