diff --git a/ckpts/universal/global_step20/zero/16.attention.dense.weight/exp_avg_sq.pt b/ckpts/universal/global_step20/zero/16.attention.dense.weight/exp_avg_sq.pt new file mode 100644 index 0000000000000000000000000000000000000000..55b7e9ed6f4324acc38fc79119b850d167129979 --- /dev/null +++ b/ckpts/universal/global_step20/zero/16.attention.dense.weight/exp_avg_sq.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:13576c94bc996ba02e2fb0df3a99d0e7ea4889614242d46db235db45fd79f0d9 +size 16778411 diff --git a/ckpts/universal/global_step20/zero/20.mlp.dense_h_to_4h.weight/exp_avg.pt b/ckpts/universal/global_step20/zero/20.mlp.dense_h_to_4h.weight/exp_avg.pt new file mode 100644 index 0000000000000000000000000000000000000000..d5fbd87045bce5e6c579f09a9e1dba20737968c3 --- /dev/null +++ b/ckpts/universal/global_step20/zero/20.mlp.dense_h_to_4h.weight/exp_avg.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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b/ckpts/universal/global_step20/zero/4.attention.dense.weight/fp32.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b4d5d0c13f3dba892d8bc27c78960242637f02c6132c7ae7596980466006db7d +size 16778317 diff --git a/ckpts/universal/global_step20/zero/7.input_layernorm.weight/exp_avg.pt b/ckpts/universal/global_step20/zero/7.input_layernorm.weight/exp_avg.pt new file mode 100644 index 0000000000000000000000000000000000000000..216257282f2000445dbe3329060a3470bbc2ed85 --- /dev/null +++ b/ckpts/universal/global_step20/zero/7.input_layernorm.weight/exp_avg.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:60bf772fd545c43209c6ded2da18785dc98755e020e9c616238ad0a24d9950d0 +size 9372 diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d.h new file mode 100644 index 0000000000000000000000000000000000000000..e546b320d6fe64f43c198f27129d7dc458021dc6 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor +inline at::Tensor _adaptive_avg_pool3d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::_adaptive_avg_pool3d::call(self, c10::fromIntArrayRefSlow(output_size)); +} +namespace symint { + template ::value>> + at::Tensor _adaptive_avg_pool3d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::_adaptive_avg_pool3d::call(self, c10::fromIntArrayRefSlow(output_size)); + } +} + +// aten::_adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor +inline at::Tensor _adaptive_avg_pool3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size) { + return at::_ops::_adaptive_avg_pool3d::call(self, output_size); +} +namespace symint { + template ::value>> + at::Tensor _adaptive_avg_pool3d(const at::Tensor & self, c10::SymIntArrayRef output_size) { + return at::_ops::_adaptive_avg_pool3d::call(self, output_size); + } +} + +// aten::_adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _adaptive_avg_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::_adaptive_avg_pool3d_out::call(self, c10::fromIntArrayRefSlow(output_size), out); +} +namespace symint { + template ::value>> + at::Tensor & _adaptive_avg_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::_adaptive_avg_pool3d_out::call(self, c10::fromIntArrayRefSlow(output_size), out); + } +} + +// aten::_adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _adaptive_avg_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::_adaptive_avg_pool3d_out::call(self, c10::fromIntArrayRefSlow(output_size), out); +} +namespace symint { + template ::value>> + at::Tensor & _adaptive_avg_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out) { + return at::_ops::_adaptive_avg_pool3d_out::call(self, c10::fromIntArrayRefSlow(output_size), out); + } +} + +// aten::_adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _adaptive_avg_pool3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size) { + return at::_ops::_adaptive_avg_pool3d_out::call(self, output_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _adaptive_avg_pool3d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size) { + return at::_ops::_adaptive_avg_pool3d_out::call(self, output_size, out); + } +} + +// aten::_adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _adaptive_avg_pool3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out) { + return at::_ops::_adaptive_avg_pool3d_out::call(self, output_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _adaptive_avg_pool3d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out) { + return at::_ops::_adaptive_avg_pool3d_out::call(self, output_size, out); + } +} + +} diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Half_compositeimplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Half_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..18f52404c537743e032003f1bcc4cb6b2b9f84ee --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Half_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _cast_Half(const at::Tensor & self, bool non_blocking=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Long.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Long.h new file mode 100644 index 0000000000000000000000000000000000000000..dedf28b2098d82937f19e3890d9ef08adc5410a1 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Long.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cast_Long(Tensor self, bool non_blocking=False) -> Tensor +inline at::Tensor _cast_Long(const at::Tensor & self, bool non_blocking=false) { + return at::_ops::_cast_Long::call(self, non_blocking); +} + +} diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward_native.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3c3be9e3b3451a119ea22c8b8000b9116241a82d --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_forward_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _cdist_forward_out(const at::Tensor & x1, const at::Tensor & x2, double p, c10::optional compute_mode, at::Tensor & out); +TORCH_API at::Tensor _cdist_forward(const at::Tensor & x1, const at::Tensor & x2, double p, c10::optional compute_mode); +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_choose_qparams_per_tensor.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_choose_qparams_per_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..2374679ba1ccc0d6e78cdbbd474c80d34f2891d5 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_choose_qparams_per_tensor.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_choose_qparams_per_tensor(Tensor self, bool reduce_range=False) -> (float, int) +inline ::std::tuple _choose_qparams_per_tensor(const at::Tensor & self, bool reduce_range=false) { + return at::_ops::_choose_qparams_per_tensor::call(self, reduce_range); +} + +} diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_compositeimplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2c3d3dd64fe291131c987a9586a2520ab0f1afea --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_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 int64_t _cufft_get_plan_cache_max_size(at::DeviceIndex device_index); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_native.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_native.h new file mode 100644 index 0000000000000000000000000000000000000000..356e3b948bfad49101468e220d9318a3cdddded0 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcdiv_native.h @@ -0,0 +1,35 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void _foreach_addcdiv_Scalar_out(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API ::std::vector foreach_tensor_addcdiv_scalar_slow(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void foreach_tensor_addcdiv_scalar_slow_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector foreach_tensor_addcdiv_scalar_cuda(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void foreach_tensor_addcdiv_scalar_cuda_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_ScalarList_out(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API ::std::vector foreach_tensor_addcdiv_scalarlist_slow(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void foreach_tensor_addcdiv_scalarlist_slow_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_addcdiv_scalarlist_cuda(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void foreach_tensor_addcdiv_scalarlist_cuda_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_Tensor_out(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +TORCH_API ::std::vector foreach_tensor_addcdiv_tensor_slow(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void foreach_tensor_addcdiv_tensor_slow_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API ::std::vector foreach_tensor_addcdiv_tensor_cuda(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void foreach_tensor_addcdiv_tensor_cuda_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_compositeexplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5b5b6ccf6387b63ee4b8e539265e00fde664dd64 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_zero_compositeexplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_zero(at::TensorList self); +TORCH_API void _foreach_zero_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_zero_outf(at::TensorList self, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0162f963e7ebe5cb4e7359b4cfb2532e723bd2d2 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_dropout_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fused_dropout { + using schema = ::std::tuple (const at::Tensor &, double, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_fused_dropout") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & self, double p, c10::optional generator); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, c10::optional generator); +}; + +struct TORCH_API _fused_dropout_out { + using schema = ::std::tuple (const at::Tensor &, double, c10::optional, 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::_fused_dropout") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & self, double p, c10::optional generator, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, c10::optional generator, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_native.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9cf24918cae71558e52406990128052a6a4ce0ce --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _histogramdd_from_bin_tensors_out(const at::Tensor & self, at::TensorList bins, const c10::optional & weight, bool density, at::Tensor & out); +TORCH_API at::Tensor _histogramdd(const at::Tensor & self, at::TensorList bins, const c10::optional & weight={}, bool density=false); +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_meta_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..32fb0e84cf49441265dff50fc24367a89f9e4f63 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_index_put_impl_meta_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor & _index_put_impl_(at::Tensor & self, const c10::List> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false); + +} // namespace meta +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_eigh_meta_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_eigh_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6fd8057e8fa55cabefbae8a41412f6bbb8de3300 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_eigh_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API ::std::tuple _linalg_eigh(const at::Tensor & A, c10::string_view UPLO="L", bool compute_v=true); +TORCH_API ::std::tuple _linalg_eigh_out(at::Tensor & eigenvalues, at::Tensor & eigenvectors, const at::Tensor & A, c10::string_view UPLO="L", bool compute_v=true); +TORCH_API ::std::tuple _linalg_eigh_outf(const at::Tensor & A, c10::string_view UPLO, bool compute_v, at::Tensor & eigenvalues, at::Tensor & eigenvectors); + +} // namespace meta +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_pad_enum_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_pad_enum_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..489ad17cc5e11f283eabfc5cd106c8a86648944d --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_pad_enum_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 _pad_enum { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, int64_t, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_pad_enum") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef pad, int64_t mode, c10::optional value); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef pad, int64_t mode, c10::optional value); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_for_cpu_cpu_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_for_cpu_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c81415c23dd1a35ffead92ad7a510a1cca101fec --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_for_cpu_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple _scaled_dot_product_flash_attention_for_cpu(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, double dropout_p=0.0, bool is_causal=false, const c10::optional & attn_mask={}, c10::optional scale=c10::nullopt); + +} // namespace cpu +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..09dd5de7d66efad5d40c446911a7fb7fc3d04395 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_and_tensors_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_coo_tensor_with_dims_and_tensors { + using schema = at::Tensor (int64_t, int64_t, c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, c10::optional, c10::optional, c10::optional, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_coo_tensor_with_dims_and_tensors") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False, bool? is_coalesced=None) -> Tensor") + static at::Tensor call(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional is_coalesced); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional is_coalesced); +}; + +struct TORCH_API _sparse_coo_tensor_with_dims_and_tensors_out { + using schema = at::Tensor & (int64_t, int64_t, c10::SymIntArrayRef, const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_coo_tensor_with_dims_and_tensors") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, bool? is_coalesced=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, c10::optional is_coalesced, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, c10::optional is_coalesced, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_spdiags_compositeexplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_spdiags_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bdb53785581c435b957a0512a5017a7ab598e3e3 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_spdiags_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _spdiags_out(at::Tensor & out, const at::Tensor & diagonals, const at::Tensor & offsets, at::IntArrayRef shape, c10::optional layout=c10::nullopt); +TORCH_API at::Tensor & _spdiags_outf(const at::Tensor & diagonals, const at::Tensor & offsets, at::IntArrayRef shape, c10::optional layout, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_stack_compositeexplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_stack_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..dc1d4d74b83e5dba02b2cfa734f7b4f7d4caf0e8 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_stack_compositeexplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor _stack(at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & _stack_out(at::Tensor & out, at::TensorList tensors, int64_t dim=0); +TORCH_API at::Tensor & _stack_outf(at::TensorList tensors, int64_t dim, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr_compositeexplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eea2e0e9f7dc1514d89fb54e548420a66504e59c --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _to_sparse_csr_out(at::Tensor & out, const at::Tensor & self, c10::optional dense_dim=c10::nullopt); +TORCH_API at::Tensor & _to_sparse_csr_outf(const at::Tensor & self, c10::optional dense_dim, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/addcdiv_cuda_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/addcdiv_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d5253848a8ebbe0e16d11e1ec1e6b14c1c79c949 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/addcdiv_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor addcdiv(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); +TORCH_API at::Tensor & addcdiv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); +TORCH_API at::Tensor & addcdiv_outf(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & addcdiv_(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); + +} // namespace cuda +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/affine_grid_generator_backward_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/affine_grid_generator_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4099d217102a4de73d2c6fca2feb36ed21d6f3e9 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/affine_grid_generator_backward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API affine_grid_generator_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::affine_grid_generator_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "affine_grid_generator_backward(Tensor grad, SymInt[] size, bool align_corners) -> Tensor") + static at::Tensor call(const at::Tensor & grad, c10::SymIntArrayRef size, bool align_corners); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, c10::SymIntArrayRef size, bool align_corners); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/alias_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/alias_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c70954c94dbbb9e2793741fefaf1919b021dd8c3 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/alias_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 alias { + 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::alias") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "alias(Tensor(a) self) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/atan2_meta.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/atan2_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..40a12ecd8d81e8dd872987775c81e8315eb7f963 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/atan2_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_atan2 : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/atanh_meta_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/atanh_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f5285c5980609026c5fd6f9dc861b418c4f12069 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/atanh_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor atanh(const at::Tensor & self); +TORCH_API at::Tensor & atanh_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & atanh_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & atanh_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/bincount.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/bincount.h new file mode 100644 index 0000000000000000000000000000000000000000..f1ead6d7cf1cd7c97d9919293212611ff2094619 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/bincount.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::bincount(Tensor self, Tensor? weights=None, int minlength=0) -> Tensor +inline at::Tensor bincount(const at::Tensor & self, const c10::optional & weights={}, int64_t minlength=0) { + return at::_ops::bincount::call(self, weights, minlength); +} + +// aten::bincount.out(Tensor self, Tensor? weights=None, int minlength=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bincount_out(at::Tensor & out, const at::Tensor & self, const c10::optional & weights={}, int64_t minlength=0) { + return at::_ops::bincount_out::call(self, weights, minlength, out); +} +// aten::bincount.out(Tensor self, Tensor? weights=None, int minlength=0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bincount_outf(const at::Tensor & self, const c10::optional & weights, int64_t minlength, at::Tensor & out) { + return at::_ops::bincount_out::call(self, weights, minlength, out); +} + +} diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_right_shift_cpu_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_right_shift_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e4f494350404ea095dc8db92fd8245357faebc56 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_right_shift_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor bitwise_right_shift(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_right_shift_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_xor_cuda_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_xor_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..667635e3ef5fd5980d07a491d9e20fb822e07ccc --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_xor_cuda_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor bitwise_xor(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_xor_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_xor_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_xor_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/coalesce_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/coalesce_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..626df101f74f73cdf17dd1eddeaf074490bdf1f2 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/coalesce_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 coalesce { + 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::coalesce") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "coalesce(Tensor(a) self) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/copysign_compositeexplicitautogradnonfunctional_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/copysign_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..352fb3c9dbd33dd091d6278bc927e71e582f3ebb --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/copysign_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 copysign(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & copysign_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/cummaxmin_backward_compositeimplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/cummaxmin_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bd02b3094cb7f0d2b5f3a25593ddff718c7bf54 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/cummaxmin_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor cummaxmin_backward(const at::Tensor & grad, const at::Tensor & input, const at::Tensor & indices, int64_t dim); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/dense_dim_cpu_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/dense_dim_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..58cf6588e04b5b1b875a5355cc2b172eb77e7c97 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/dense_dim_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API int64_t dense_dim(const at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/erfc_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/erfc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..923d9528e4f32766b26bca1f77a5dc1c5489270b --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/erfc_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API erfc { + 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::erfc") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "erfc(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API erfc_ { + 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::erfc_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "erfc_(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 erfc_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::erfc") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/expand_copy_compositeexplicitautogradnonfunctional_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/expand_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bd10495bdf7e632272bff747a66eb0284da2c9a3 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/expand_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor expand_copy(const at::Tensor & self, at::IntArrayRef size, bool implicit=false); +TORCH_API at::Tensor expand_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size, bool implicit=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/eye.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/eye.h new file mode 100644 index 0000000000000000000000000000000000000000..74b0bc2db2f70a80646022c1900d9cc4dfd51123 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/eye.h @@ -0,0 +1,201 @@ +#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::eye(SymInt n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye(int64_t n, at::TensorOptions options={}) { + return at::_ops::eye::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor eye(int64_t n, at::TensorOptions options={}) { + return at::_ops::eye::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::eye(SymInt n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye(int64_t n, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::eye::call(n, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor eye(int64_t n, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::eye::call(n, dtype, layout, device, pin_memory); + } +} + +// aten::eye(SymInt n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye_symint(c10::SymInt n, at::TensorOptions options={}) { + return at::_ops::eye::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor eye(c10::SymInt n, at::TensorOptions options={}) { + return at::_ops::eye::call(n, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::eye(SymInt n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye_symint(c10::SymInt n, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::eye::call(n, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor eye(c10::SymInt n, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::eye::call(n, dtype, layout, device, pin_memory); + } +} + +// aten::eye.m(SymInt n, SymInt m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye(int64_t n, int64_t m, at::TensorOptions options={}) { + return at::_ops::eye_m::call(n, m, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor eye(int64_t n, int64_t m, at::TensorOptions options={}) { + return at::_ops::eye_m::call(n, m, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::eye.m(SymInt n, SymInt m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye(int64_t n, int64_t m, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::eye_m::call(n, m, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor eye(int64_t n, int64_t m, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::eye_m::call(n, m, dtype, layout, device, pin_memory); + } +} + +// aten::eye.m(SymInt n, SymInt m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye_symint(c10::SymInt n, c10::SymInt m, at::TensorOptions options={}) { + return at::_ops::eye_m::call(n, m, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor eye(c10::SymInt n, c10::SymInt m, at::TensorOptions options={}) { + return at::_ops::eye_m::call(n, m, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::eye.m(SymInt n, SymInt m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor eye_symint(c10::SymInt n, c10::SymInt m, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::eye_m::call(n, m, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor eye(c10::SymInt n, c10::SymInt m, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::eye_m::call(n, m, dtype, layout, device, pin_memory); + } +} + +// aten::eye.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_out(at::Tensor & out, int64_t n) { + return at::_ops::eye_out::call(n, out); +} +namespace symint { + template ::value>> + at::Tensor & eye_out(at::Tensor & out, int64_t n) { + return at::_ops::eye_out::call(n, out); + } +} + +// aten::eye.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_outf(int64_t n, at::Tensor & out) { + return at::_ops::eye_out::call(n, out); +} +namespace symint { + template ::value>> + at::Tensor & eye_outf(int64_t n, at::Tensor & out) { + return at::_ops::eye_out::call(n, out); + } +} + +// aten::eye.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_symint_out(at::Tensor & out, c10::SymInt n) { + return at::_ops::eye_out::call(n, out); +} +namespace symint { + template ::value>> + at::Tensor & eye_out(at::Tensor & out, c10::SymInt n) { + return at::_ops::eye_out::call(n, out); + } +} + +// aten::eye.out(SymInt n, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_symint_outf(c10::SymInt n, at::Tensor & out) { + return at::_ops::eye_out::call(n, out); +} +namespace symint { + template ::value>> + at::Tensor & eye_outf(c10::SymInt n, at::Tensor & out) { + return at::_ops::eye_out::call(n, out); + } +} + +// aten::eye.m_out(SymInt n, SymInt m, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_out(at::Tensor & out, int64_t n, int64_t m) { + return at::_ops::eye_m_out::call(n, m, out); +} +namespace symint { + template ::value>> + at::Tensor & eye_out(at::Tensor & out, int64_t n, int64_t m) { + return at::_ops::eye_m_out::call(n, m, out); + } +} + +// aten::eye.m_out(SymInt n, SymInt m, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_outf(int64_t n, int64_t m, at::Tensor & out) { + return at::_ops::eye_m_out::call(n, m, out); +} +namespace symint { + template ::value>> + at::Tensor & eye_outf(int64_t n, int64_t m, at::Tensor & out) { + return at::_ops::eye_m_out::call(n, m, out); + } +} + +// aten::eye.m_out(SymInt n, SymInt m, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_symint_out(at::Tensor & out, c10::SymInt n, c10::SymInt m) { + return at::_ops::eye_m_out::call(n, m, out); +} +namespace symint { + template ::value>> + at::Tensor & eye_out(at::Tensor & out, c10::SymInt n, c10::SymInt m) { + return at::_ops::eye_m_out::call(n, m, out); + } +} + +// aten::eye.m_out(SymInt n, SymInt m, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & eye_symint_outf(c10::SymInt n, c10::SymInt m, at::Tensor & out) { + return at::_ops::eye_m_out::call(n, m, out); +} +namespace symint { + template ::value>> + at::Tensor & eye_outf(c10::SymInt n, c10::SymInt m, at::Tensor & out) { + return at::_ops::eye_m_out::call(n, m, out); + } +} + +} diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..736b3a01243df69a4b70d24d09617290e3753d6b --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight.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::fbgemm_linear_quantize_weight(Tensor input) -> (Tensor, Tensor, float, int) +inline ::std::tuple fbgemm_linear_quantize_weight(const at::Tensor & input) { + return at::_ops::fbgemm_linear_quantize_weight::call(input); +} + +} diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fft_ifft2_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fft_ifft2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1b98ee4b7d3f0b62f86698103a57efcfa27a2de4 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fft_ifft2_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_ifft2 { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fft_ifft2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ifft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm); +}; + +struct TORCH_API fft_ifft2_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fft_ifft2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fft_ifft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fft_irfft_native.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fft_irfft_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cb5fbe2fd42160a74fd6a7c28925c3b2f0fa3fae --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fft_irfft_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fft_irfft_symint(const at::Tensor & self, c10::optional n=c10::nullopt, int64_t dim=-1, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_irfft_symint_out(const at::Tensor & self, c10::optional n, int64_t dim, c10::optional norm, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fmax_cpu_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fmax_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ecc15bf7ab06a46aa2e290a333d93d0d41671a92 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/fmax_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 fmax(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmax_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/frac_meta_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/frac_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..48ceec3d83c5563c6075c3c55e913287a091e9cf --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/frac_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor frac(const at::Tensor & self); +TORCH_API at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & frac_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_3d_compositeexplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_3d_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6455a6cee6b06135ac38ff201b2b5c6d06edda89 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_3d_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & grid_sampler_3d_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +TORCH_API at::Tensor & grid_sampler_3d_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/gru_cell_compositeimplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/gru_cell_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..24777c6952927f7b3856beee681ff6d9e5c15982 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/gru_cell_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const c10::optional & b_ih={}, const c10::optional & b_hh={}); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/gt_cuda_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/gt_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5ff67ef575640c5baa83463aef7c3e4bb0904923 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/gt_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 at::Tensor gt(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor gt(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/histogram_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/histogram_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..d590f4f9d779741173dcd79a18fc8d2e4d07e5a5 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/histogram_ops.h @@ -0,0 +1,61 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API histogram_bins_tensor_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, 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::histogram") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "bins_tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "histogram.bins_tensor_out(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges)") + static ::std::tuple call(const at::Tensor & self, const at::Tensor & bins, const c10::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & bins, const c10::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); +}; + +struct TORCH_API histogram_bins_tensor { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::histogram") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "bins_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "histogram.bins_tensor(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges)") + static ::std::tuple call(const at::Tensor & self, const at::Tensor & bins, const c10::optional & weight, bool density); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & bins, const c10::optional & weight, bool density); +}; + +struct TORCH_API histogram_bin_ct_out { + using schema = ::std::tuple (const at::Tensor &, int64_t, c10::optional>, const c10::optional &, 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::histogram") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "bin_ct_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "histogram.bin_ct_out(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges)") + static ::std::tuple call(const at::Tensor & self, int64_t bins, c10::optional> range, const c10::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t bins, c10::optional> range, const c10::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); +}; + +struct TORCH_API histogram_bin_ct { + using schema = ::std::tuple (const at::Tensor &, int64_t, c10::optional>, const c10::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::histogram") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "bin_ct") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "histogram.bin_ct(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges)") + static ::std::tuple call(const at::Tensor & self, int64_t bins, c10::optional> range, const c10::optional & weight, bool density); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t bins, c10::optional> range, const c10::optional & weight, bool density); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/histogramdd_compositeimplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/histogramdd_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a608c04a32c1332d2699020d43d10d6c1b702aee --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/histogramdd_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> histogramdd(const at::Tensor & self, at::IntArrayRef bins, c10::optional> range=c10::nullopt, const c10::optional & weight={}, bool density=false); +TORCH_API ::std::tuple> histogramdd(const at::Tensor & self, int64_t bins, c10::optional> range=c10::nullopt, const c10::optional & weight={}, bool density=false); +TORCH_API ::std::tuple> histogramdd(const at::Tensor & self, at::TensorList bins, c10::optional> range=c10::nullopt, const c10::optional & weight={}, bool density=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/hsplit_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/hsplit_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..72acce599b2bb8d0616f4f7e45eca601a8e58c4a --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/hsplit_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 hsplit_int { + using schema = ::std::vector (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::hsplit") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "int") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "hsplit.int(Tensor(a -> *) self, int sections) -> Tensor(a)[]") + static ::std::vector call(const at::Tensor & self, int64_t sections); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t sections); +}; + +struct TORCH_API hsplit_array { + using schema = ::std::vector (const at::Tensor &, at::IntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::hsplit") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "array") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "hsplit.array(Tensor(a -> *) self, int[] indices) -> Tensor(a)[]") + static ::std::vector call(const at::Tensor & self, at::IntArrayRef indices); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef indices); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/is_pinned_cuda_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/is_pinned_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a03dba23eb5f05492cfee92a5a6f0fd3be83501f --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/is_pinned_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API bool is_pinned(const at::Tensor & self, c10::optional device=c10::nullopt); + +} // namespace cuda +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_det_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_det_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0c72b00f4c4a749ce66b01b43b6eb42626830519 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_det_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_det { + 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::linalg_det") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_det(Tensor A) -> Tensor") + static at::Tensor call(const at::Tensor & A); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A); +}; + +struct TORCH_API linalg_det_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::linalg_det") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_det.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & A, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_solve_native.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_solve_native.h new file mode 100644 index 0000000000000000000000000000000000000000..88023ef2acc71c74c0db122fc7f686c0d567a9fc --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_solve_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor linalg_solve(const at::Tensor & A, const at::Tensor & B, bool left=true); +TORCH_API at::Tensor & linalg_solve_out(const at::Tensor & A, const at::Tensor & B, bool left, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp_native.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp_native.h new file mode 100644 index 0000000000000000000000000000000000000000..641306ff680c0e24511b642a01ef3aaf9cadb6aa --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp_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_logaddexp_out : public at::meta::structured_logaddexp { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/lu_unpack_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/lu_unpack_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..87e98c03f6048f6e24c9378434ad3c4243273d37 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/lu_unpack_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 lu_unpack { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lu_unpack") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lu_unpack(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True) -> (Tensor P, Tensor L, Tensor U)") + static ::std::tuple call(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots); +}; + +struct TORCH_API lu_unpack_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, bool, 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::lu_unpack") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True, *, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U)") + static ::std::tuple call(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots, at::Tensor & P, at::Tensor & L, at::Tensor & U); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots, at::Tensor & P, at::Tensor & L, at::Tensor & U); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f6756336099b540fda563bf8111d0496c778309c --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_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 miopen_depthwise_convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::miopen_depthwise_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); +}; + +struct TORCH_API miopen_depthwise_convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::miopen_depthwise_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_cpu_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6334f19fdf81fd82e7b906485a044ed75231e1fc --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/mse_loss_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 mse_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API at::Tensor & mse_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API at::Tensor & mse_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cuda_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/multinomial_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f0a1f10a46a03d544a331e7795f66503a1e825d8 --- /dev/null +++ b/venv/lib/python3.10/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, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, int64_t num_samples, bool replacement=false, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & multinomial_outf(const at::Tensor & self, int64_t num_samples, bool replacement, c10::optional generator, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/nested_to_padded_tensor_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/nested_to_padded_tensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5156e5464b02597672915dcc0311292337011dc4 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/nested_to_padded_tensor_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API nested_to_padded_tensor { + using schema = at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nested_to_padded_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nested_to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, double padding, at::OptionalIntArrayRef output_size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double padding, at::OptionalIntArrayRef output_size); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/nextafter.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/nextafter.h new file mode 100644 index 0000000000000000000000000000000000000000..7b47456139a5f79fbdc464886f6a0ba65c676d53 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/nextafter.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::nextafter.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nextafter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::nextafter_out::call(self, other, out); +} +// aten::nextafter.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nextafter_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::nextafter_out::call(self, other, out); +} + +// aten::nextafter(Tensor self, Tensor other) -> Tensor +inline at::Tensor nextafter(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::nextafter::call(self, other); +} + +} diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/nuclear_norm_compositeimplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/nuclear_norm_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f97a30b1b4f0e09f07f50c4f1991ede9ad24592b --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/nuclear_norm_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor nuclear_norm(const at::Tensor & self, bool keepdim=false); +TORCH_API at::Tensor & nuclear_norm_out(at::Tensor & out, const at::Tensor & self, bool keepdim=false); +TORCH_API at::Tensor & nuclear_norm_outf(const at::Tensor & self, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor nuclear_norm(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & nuclear_norm_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & nuclear_norm_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/polygamma_cpu_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/polygamma_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1a3aa0135ad01aba1e00ab2dbe1192f6547d2c63 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/polygamma_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 polygamma(int64_t n, const at::Tensor & self); +TORCH_API at::Tensor & polygamma_out(at::Tensor & out, int64_t n, const at::Tensor & self); +TORCH_API at::Tensor & polygamma_outf(int64_t n, const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_compositeexplicitautogradnonfunctional_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e1eeafc52b837e26baef8f39c6b65726f835bee3 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad1d_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor replication_pad1d(const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor replication_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/rot90_compositeexplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/rot90_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..56228fe257c6204106610b4ae8242c3db76e98d0 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/rot90_compositeexplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor rot90(const at::Tensor & self, int64_t k=1, at::IntArrayRef dims={0,1}); +TORCH_API at::Tensor & rot90_out(at::Tensor & out, const at::Tensor & self, int64_t k=1, at::IntArrayRef dims={0,1}); +TORCH_API at::Tensor & rot90_outf(const at::Tensor & self, int64_t k, at::IntArrayRef dims, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/round_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/round_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9bbeaafa3c77e61db5aa07001e76226a7840e2c1 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/round_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 round { + 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::round") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "round(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API round_ { + 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::round_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "round_(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 round_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::round") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "round.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 round_decimals { + using schema = at::Tensor (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::round") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "decimals") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "round.decimals(Tensor self, *, int decimals) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t decimals); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t decimals); +}; + +struct TORCH_API round__decimals { + using schema = at::Tensor & (at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::round_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "decimals") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "round_.decimals(Tensor(a!) self, *, int decimals) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, int64_t decimals); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t decimals); +}; + +struct TORCH_API round_decimals_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::round") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "decimals_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "round.decimals_out(Tensor self, *, int decimals, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t decimals, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t decimals, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/sinc_meta_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/sinc_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fb29448070f8236a7714864cb707b6b254475943 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/sinc_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor sinc(const at::Tensor & self); +TORCH_API at::Tensor & sinc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sinc_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinc_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_j1_meta.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_j1_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..289177d095be6207bcc5cf24fd7d1c69ec609bd7 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_j1_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_bessel_j1 : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..921752fe249a75b96dae7e0b9cb20f8c87b65d74 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_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_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_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_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_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_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "x_scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_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_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_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "n_scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_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_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_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_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_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_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_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_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_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_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/python3.10/site-packages/torch/include/ATen/ops/special_entr.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_entr.h new file mode 100644 index 0000000000000000000000000000000000000000..94878770890d10713bd14094b3bf5055127b13b4 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_entr.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_entr(Tensor self) -> Tensor +inline at::Tensor special_entr(const at::Tensor & self) { + return at::_ops::special_entr::call(self); +} + +// aten::special_entr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_entr_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_entr_out::call(self, out); +} +// aten::special_entr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_entr_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_entr_out::call(self, out); +} + +} diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_ndtri_cpu_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_ndtri_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5da764dd6d02ad1b00e6defe500e874ed1e9d3d3 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_ndtri_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_ndtri(const at::Tensor & self); +TORCH_API at::Tensor & special_ndtri_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_ndtri_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_native.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_native.h new file mode 100644 index 0000000000000000000000000000000000000000..04478ef2bc0dde3cbee259990137bee646965c97 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_native.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_special_shifted_chebyshev_polynomial_t_out : public at::meta::structured_special_shifted_chebyshev_polynomial_t { +void impl(const at::Tensor & x, const at::Tensor & n, const at::Tensor & out); +}; +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_t(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_out(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_t(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_out(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_sinc_compositeimplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_sinc_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..74445dc75e6b7d73b60b78926c9fd2551de451c2 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/special_sinc_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor special_sinc(const at::Tensor & self); +TORCH_API at::Tensor & special_sinc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_sinc_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/split.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/split.h new file mode 100644 index 0000000000000000000000000000000000000000..887106b0d5f56ed39bb0ee1ee92f76768d56dbc0 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/split.h @@ -0,0 +1,69 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[] +inline ::std::vector split(const at::Tensor & self, int64_t split_size, int64_t dim=0) { + return at::_ops::split_Tensor::call(self, split_size, dim); +} +namespace symint { + template ::value>> + ::std::vector split(const at::Tensor & self, int64_t split_size, int64_t dim=0) { + return at::_ops::split_Tensor::call(self, split_size, dim); + } +} + +// aten::split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[] +inline ::std::vector split_symint(const at::Tensor & self, c10::SymInt split_size, int64_t dim=0) { + return at::_ops::split_Tensor::call(self, split_size, dim); +} +namespace symint { + template ::value>> + ::std::vector split(const at::Tensor & self, c10::SymInt split_size, int64_t dim=0) { + return at::_ops::split_Tensor::call(self, split_size, dim); + } +} + +// aten::split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[] +inline ::std::vector split(const at::Tensor & self, at::IntArrayRef split_size, int64_t dim=0) { + return at::_ops::split_sizes::call(self, c10::fromIntArrayRefSlow(split_size), dim); +} +namespace symint { + template ::value>> + ::std::vector split(const at::Tensor & self, at::IntArrayRef split_size, int64_t dim=0) { + return at::_ops::split_sizes::call(self, c10::fromIntArrayRefSlow(split_size), dim); + } +} + +// aten::split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[] +inline ::std::vector split_symint(const at::Tensor & self, c10::SymIntArrayRef split_size, int64_t dim=0) { + return at::_ops::split_sizes::call(self, split_size, dim); +} +namespace symint { + template ::value>> + ::std::vector split(const at::Tensor & self, c10::SymIntArrayRef split_size, int64_t dim=0) { + return at::_ops::split_sizes::call(self, split_size, dim); + } +} + +} diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/stft_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/stft_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bc89fd02c6ff051fd2d00c5e1a2df0104b3f5d47 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/stft_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 stft { + using schema = at::Tensor (const at::Tensor &, int64_t, c10::optional, c10::optional, const c10::optional &, bool, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::stft") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "stft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool normalized=False, bool? onesided=None, bool? return_complex=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t n_fft, c10::optional hop_length, c10::optional win_length, const c10::optional & window, bool normalized, c10::optional onesided, c10::optional return_complex); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n_fft, c10::optional hop_length, c10::optional win_length, const c10::optional & window, bool normalized, c10::optional onesided, c10::optional return_complex); +}; + +struct TORCH_API stft_center { + using schema = at::Tensor (const at::Tensor &, int64_t, c10::optional, c10::optional, const c10::optional &, bool, c10::string_view, bool, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::stft") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "center") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "stft.center(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool center=True, str pad_mode=\"reflect\", bool normalized=False, bool? onesided=None, bool? return_complex=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t n_fft, c10::optional hop_length, c10::optional win_length, const c10::optional & window, bool center, c10::string_view pad_mode, bool normalized, c10::optional onesided, c10::optional return_complex); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n_fft, c10::optional hop_length, c10::optional win_length, const c10::optional & window, bool center, c10::string_view pad_mode, bool normalized, c10::optional onesided, c10::optional return_complex); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f28095cff8865335712fdbfcdd4c06dfc57e5543 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/swapdims_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor swapdims(const at::Tensor & self, int64_t dim0, int64_t dim1); +TORCH_API at::Tensor & swapdims_(at::Tensor & self, int64_t dim0, int64_t dim1); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_native.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6694c8cfd7f987271d1f6775e7b21431e1ce5879 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor to_sparse_csc(const at::Tensor & self, c10::optional dense_dim=c10::nullopt); +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_ops.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8dbd174fcf8c1ff25f05dc26291129278b8892ef --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_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 trunc { + 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::trunc") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "trunc(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API trunc_ { + 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::trunc_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "trunc_(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 trunc_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::trunc") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_cpu_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b2b3f1af6969a6804f12cde6b2ab2dc24b1fc4b9 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor upsample_nearest2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor upsample_nearest2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_nearest2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_meta.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..df2813236356f394861bcbb2b3df47986a7e622c --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_upsample_nearest2d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::ArrayRef output_size, c10::optional scales_h, c10::optional scales_w); +}; + +} // namespace native +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/var_compositeimplicitautograd_dispatch.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/var_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5901a19ac52ebf08e2b5811f505c525c6eb375f4 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/var_compositeimplicitautograd_dispatch.h @@ -0,0 +1,32 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor var(const at::Tensor & self, bool unbiased); +TORCH_API at::Tensor var(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim=false); +TORCH_API at::Tensor & var_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim=false); +TORCH_API at::Tensor & var_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor var(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim=false); +TORCH_API at::Tensor & var_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim=false); +TORCH_API at::Tensor & var_outf(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor var(const at::Tensor & self, at::DimnameList dim, const c10::optional & correction=c10::nullopt, bool keepdim=false); +TORCH_API at::Tensor & var_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, const c10::optional & correction=c10::nullopt, bool keepdim=false); +TORCH_API at::Tensor & var_outf(const at::Tensor & self, at::DimnameList dim, const c10::optional & correction, bool keepdim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/venv/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_native.h b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7351d65e60247d5ad979d40ca9496839c5d34e68 --- /dev/null +++ b/venv/lib/python3.10/site-packages/torch/include/ATen/ops/vdot_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 & vdot_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor vdot(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor vdot_cuda(const at::Tensor & self, const at::Tensor & other); +} // namespace native +} // namespace at