diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..98424bedb1da9767cef26fc0e6514ac8f7c98070 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_tensor_affine_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _fake_quantize_learnable_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fft_c2r.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fft_c2r.h new file mode 100644 index 0000000000000000000000000000000000000000..e2ff7ef5514b5a2a3c056bbc44fbb0aa9ad345b8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fft_c2r.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template ::value>> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r(Tensor self, int[] dim, int normalization, SymInt last_dim_size) -> Tensor +inline at::Tensor _fft_c2r_symint(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); +} +namespace symint { + template ::value>> + at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r::call(self, dim, normalization, last_dim_size); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +// aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, SymInt last_dim_size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fft_c2r_symint_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); +} +namespace symint { + template ::value>> + at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, c10::SymInt last_dim_size, at::Tensor & out) { + return at::_ops::_fft_c2r_out::call(self, dim, normalization, last_dim_size, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_flash_attention_backward_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_flash_attention_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e18a48ae2ba7343ae80c6336b87195f15ee3a354 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_flash_attention_backward_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _flash_attention_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt); +TORCH_API ::std::tuple _flash_attention_backward_symint(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_addcdiv_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_addcdiv_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f8c313caf0df2af155ab3a31a2e1914efd4cedb5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_addcdiv_compositeexplicitautograd_dispatch.h @@ -0,0 +1,34 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_addcdiv(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcdiv_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcdiv_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); +TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_erf.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_erf.h new file mode 100644 index 0000000000000000000000000000000000000000..b790fb66899d058b1f6d5c95104d00d71ca58d03 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_erf.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_erf(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_erf(at::TensorList self) { + return at::_ops::_foreach_erf::call(self); +} + +// aten::_foreach_erf_(Tensor(a!)[] self) -> () +inline void _foreach_erf_(at::TensorList self) { + return at::_ops::_foreach_erf_::call(self); +} + +// aten::_foreach_erf.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erf_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_erf_out::call(self, out); +} +// aten::_foreach_erf.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erf_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_erf_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_minimum.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_minimum.h new file mode 100644 index 0000000000000000000000000000000000000000..115cbfcb2d6a8e81c7d6a2f38ec6ba73e86e3ea5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_minimum.h @@ -0,0 +1,82 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] +inline ::std::vector _foreach_minimum(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_minimum_Scalar::call(self, scalar); +} + +// aten::_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () +inline void _foreach_minimum_(at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_minimum__Scalar::call(self, scalar); +} + +// aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] +inline ::std::vector _foreach_minimum(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_minimum_List::call(self, other); +} + +// aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () +inline void _foreach_minimum_(at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_minimum__List::call(self, other); +} + +// aten::_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] +inline ::std::vector _foreach_minimum(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_minimum_ScalarList::call(self, scalars); +} + +// aten::_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () +inline void _foreach_minimum_(at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_minimum__ScalarList::call(self, scalars); +} + +// aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar) { + return at::_ops::_foreach_minimum_Scalar_out::call(self, scalar, out); +} +// aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { + return at::_ops::_foreach_minimum_Scalar_out::call(self, scalar, out); +} + +// aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_out(at::TensorList out, at::TensorList self, at::TensorList other) { + return at::_ops::_foreach_minimum_List_out::call(self, other, out); +} +// aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_outf(at::TensorList self, at::TensorList other, at::TensorList out) { + return at::_ops::_foreach_minimum_List_out::call(self, other, out); +} + +// aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars) { + return at::_ops::_foreach_minimum_ScalarList_out::call(self, scalars, out); +} +// aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () +inline void _foreach_minimum_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out) { + return at::_ops::_foreach_minimum_ScalarList_out::call(self, scalars, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sin.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sin.h new file mode 100644 index 0000000000000000000000000000000000000000..6de1076a058eb2c58fddfee6eaaddecbfe4d8dab --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sin.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_sin(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_sin(at::TensorList self) { + return at::_ops::_foreach_sin::call(self); +} + +// aten::_foreach_sin_(Tensor(a!)[] self) -> () +inline void _foreach_sin_(at::TensorList self) { + return at::_ops::_foreach_sin_::call(self); +} + +// aten::_foreach_sin.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sin_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_sin_out::call(self, out); +} +// aten::_foreach_sin.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_sin_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_sin_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_trunc.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_trunc.h new file mode 100644 index 0000000000000000000000000000000000000000..92f2b8258a41e5daf605c280300502e3515c496f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_trunc.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_trunc(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_trunc(at::TensorList self) { + return at::_ops::_foreach_trunc::call(self); +} + +// aten::_foreach_trunc_(Tensor(a!)[] self) -> () +inline void _foreach_trunc_(at::TensorList self) { + return at::_ops::_foreach_trunc_::call(self); +} + +// aten::_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_trunc_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_trunc_out::call(self, out); +} +// aten::_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_trunc_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_trunc_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_index_put_impl.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_index_put_impl.h new file mode 100644 index 0000000000000000000000000000000000000000..e39a4391ab0642afc5ca1ce28ae2ea3a419ca1e8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_index_put_impl.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_index_put_impl_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor(a!) +inline at::Tensor & _index_put_impl_(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false) { + return at::_ops::_index_put_impl_::call(self, indices, values, accumulate, unsafe); +} + +// aten::_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _index_put_impl_out(at::Tensor & out, const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false) { + return at::_ops::_index_put_impl_out::call(self, indices, values, accumulate, unsafe, out); +} +// aten::_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _index_put_impl_outf(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, bool unsafe, at::Tensor & out) { + return at::_ops::_index_put_impl_out::call(self, indices, values, accumulate, unsafe, out); +} + +// aten::_index_put_impl(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor +inline at::Tensor _index_put_impl(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false) { + return at::_ops::_index_put_impl::call(self, indices, values, accumulate, unsafe); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_native_multi_head_attention.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_native_multi_head_attention.h new file mode 100644 index 0000000000000000000000000000000000000000..c63c504d3678ce1163a8394f6ce8ba7bfa148c9c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_native_multi_head_attention.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::_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor) +inline ::std::tuple _native_multi_head_attention(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask={}, bool need_weights=true, bool average_attn_weights=true, ::std::optional mask_type=::std::nullopt) { + return at::_ops::_native_multi_head_attention::call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type); +} + +// aten::_native_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _native_multi_head_attention_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask={}, bool need_weights=true, bool average_attn_weights=true, ::std::optional mask_type=::std::nullopt) { + return at::_ops::_native_multi_head_attention_out::call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type, out0, out1); +} +// aten::_native_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _native_multi_head_attention_outf(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const ::std::optional & mask, bool need_weights, bool average_attn_weights, ::std::optional mask_type, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_native_multi_head_attention_out::call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type, out0, out1); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b2bd6e4689c9ea5bc8cecdf67ab7e14db29a19f1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _nested_tensor_from_mask_out(at::Tensor & out, const at::Tensor & t, const at::Tensor & mask, bool mask_check=true); +TORCH_API at::Tensor & _nested_tensor_from_mask_outf(const at::Tensor & t, const at::Tensor & mask, bool mask_check, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d702cc8299be5f37e1d50dafb3232ea5b82170bc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _nested_tensor_storage_offsets_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor _nested_tensor_storage_offsets(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..36ca51f9fb8160e696c9bf5ffc33b875c4e600a7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _nested_view_from_buffer(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_print_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_print_native.h new file mode 100644 index 0000000000000000000000000000000000000000..c956ce8abf198faa36c4d2427e9de99468b9db08 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_print_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 void _print(c10::string_view s); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_remove_batch_dim.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_remove_batch_dim.h new file mode 100644 index 0000000000000000000000000000000000000000..3fefc660c1cdd7d881f6abf19f263e2787c8e071 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_remove_batch_dim.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::_remove_batch_dim(Tensor self, int level, int batch_size, int out_dim) -> Tensor +inline at::Tensor _remove_batch_dim(const at::Tensor & self, int64_t level, int64_t batch_size, int64_t out_dim) { + return at::_ops::_remove_batch_dim::call(self, level, batch_size, out_dim); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_safe_softmax_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_safe_softmax_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ef81051455f530278645610beb06cd3944cf1649 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_safe_softmax_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor _safe_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3235e31b96c02066365a5e9843abf7e4e9d87811 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe_compositeimplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor _sparse_compressed_tensor_unsafe_symint(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor _sparse_compressed_tensor_unsafe_symint(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_csr_sum.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_csr_sum.h new file mode 100644 index 0000000000000000000000000000000000000000..5f3e342c6dc786b75e77110ea8aafd6a9b679e6e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_csr_sum.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::_sparse_csr_sum.dim_dtype(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor _sparse_csr_sum(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::_sparse_csr_sum_dim_dtype::call(self, dim, keepdim, dtype); +} + +// aten::_sparse_csr_sum.dim_dtype_out(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_csr_sum_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::_sparse_csr_sum_dim_dtype_out::call(self, dim, keepdim, dtype, out); +} +// aten::_sparse_csr_sum.dim_dtype_out(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_csr_sum_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::_sparse_csr_sum_dim_dtype_out::call(self, dim, keepdim, dtype, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm.h new file mode 100644 index 0000000000000000000000000000000000000000..e825a080a64d4127541dcf51e590b7218545e00c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_semi_structured_addmm(Tensor input, Tensor mat1, Tensor mat1_meta, Tensor mat2, *, Scalar alpha=1, Scalar beta=1, ScalarType? out_dtype=None) -> Tensor +inline at::Tensor _sparse_semi_structured_addmm(const at::Tensor & input, const at::Tensor & mat1, const at::Tensor & mat1_meta, const at::Tensor & mat2, const at::Scalar & alpha=1, const at::Scalar & beta=1, ::std::optional out_dtype=::std::nullopt) { + return at::_ops::_sparse_semi_structured_addmm::call(input, mat1, mat1_meta, mat2, alpha, beta, out_dtype); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e48eff11de11887a825beda2870c365632bd2a21 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_semi_structured_addmm_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _sparse_semi_structured_addmm(const at::Tensor & input, const at::Tensor & mat1, const at::Tensor & mat1_meta, const at::Tensor & mat2, const at::Scalar & alpha=1, const at::Scalar & beta=1, ::std::optional out_dtype=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..54541bdd4d80434b13aeb7d4e75aa08fd230912e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax_backward_data_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_softmax_backward_data { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_softmax_backward_data") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_softmax_backward_data(Tensor grad_output, Tensor output, int dim, Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); +}; + +struct TORCH_API _sparse_softmax_backward_data_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, 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::_sparse_softmax_backward_data") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_warn_in_autograd_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_warn_in_autograd_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d0c32b164f807a89f6ca6c37b7bf2c2a78176505 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_warn_in_autograd_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _test_warn_in_autograd(const at::Tensor & self); +TORCH_API at::Tensor & _test_warn_in_autograd_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..80dcbae65ad5952997140ca0dbc25facb143aaa4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_thnn_fused_gru_cell_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_thnn_fused_gru_cell_backward(Tensor grad_hy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple _thnn_fused_gru_cell_backward(const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias) { + return at::_ops::_thnn_fused_gru_cell_backward::call(grad_hy, workspace, has_bias); +} + +// aten::_thnn_fused_gru_cell_backward.out(Tensor grad_hy, Tensor workspace, bool has_bias, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _thnn_fused_gru_cell_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias) { + return at::_ops::_thnn_fused_gru_cell_backward_out::call(grad_hy, workspace, has_bias, out0, out1, out2, out3, out4); +} +// aten::_thnn_fused_gru_cell_backward.out(Tensor grad_hy, Tensor workspace, bool has_bias, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) +inline ::std::tuple _thnn_fused_gru_cell_backward_outf(const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { + return at::_ops::_thnn_fused_gru_cell_backward_out::call(grad_hy, workspace, has_bias, out0, out1, out2, out3, out4); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_bsr_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_bsr_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1c8477a19422c4610a64d5dddf80174cc6e90f1b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_sparse_bsr_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 _to_sparse_bsr { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_to_sparse_bsr") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim); +}; + +struct TORCH_API _to_sparse_bsr_out { + using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_to_sparse_bsr") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fec042e1effaa81f6c65e0b212f372e3a42a45e8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention_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 _triton_scaled_dot_attention { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_triton_scaled_dot_attention") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_triton_scaled_dot_attention(Tensor q, Tensor k, Tensor v, float dropout_p=0.0) -> Tensor") + static at::Tensor call(const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p); +}; + +struct TORCH_API _triton_scaled_dot_attention_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_triton_scaled_dot_attention") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_triton_scaled_dot_attention.out(Tensor q, Tensor k, Tensor v, float dropout_p=0.0, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unique2_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unique2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..411eb56ba422e990cb56314f0b04bbcac97f43ed --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unique2_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _unique2_out(const at::Tensor & self, bool sorted, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple _unique2_cpu(const at::Tensor & self, bool sorted=true, bool return_inverse=false, bool return_counts=false); +TORCH_API ::std::tuple _unique2_cuda(const at::Tensor & self, bool sorted=true, bool return_inverse=false, bool return_counts=false); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..1ce9eef997db9bcaf956504610ba214ebc75f57e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_backward.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bicubic2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bicubic2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bicubic2d_aa_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bicubic2d_aa_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bicubic2d_aa_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bicubic2d_aa_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & _upsample_bicubic2d_aa_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & _upsample_bicubic2d_aa_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::_upsample_bicubic2d_aa_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_bicubic2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bicubic2d_aa_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor _upsample_bicubic2d_aa_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w); + } +} + +// aten::_upsample_bicubic2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor _upsample_bicubic2d_aa_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor _upsample_bicubic2d_aa_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::_upsample_bicubic2d_aa_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..78a8b439b7da53f7b76d5d9d1528695abc9931de --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _upsample_nearest_exact2d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact2d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & _upsample_nearest_exact2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1f1c406e0d3a9b7faba34a3719dbc00791991870 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor _upsample_nearest_exact3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact3d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & _upsample_nearest_exact3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact3d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/affine_grid_generator.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/affine_grid_generator.h new file mode 100644 index 0000000000000000000000000000000000000000..f734807f5a57fd81bcc36729549f608bbb44fc2a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/affine_grid_generator.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::affine_grid_generator(Tensor theta, SymInt[] size, bool align_corners) -> Tensor +inline at::Tensor affine_grid_generator(const at::Tensor & theta, at::IntArrayRef size, bool align_corners) { + return at::_ops::affine_grid_generator::call(theta, c10::fromIntArrayRefSlow(size), align_corners); +} +namespace symint { + template ::value>> + at::Tensor affine_grid_generator(const at::Tensor & theta, at::IntArrayRef size, bool align_corners) { + return at::_ops::affine_grid_generator::call(theta, c10::fromIntArrayRefSlow(size), align_corners); + } +} + +// aten::affine_grid_generator(Tensor theta, SymInt[] size, bool align_corners) -> Tensor +inline at::Tensor affine_grid_generator_symint(const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners) { + return at::_ops::affine_grid_generator::call(theta, size, align_corners); +} +namespace symint { + template ::value>> + at::Tensor affine_grid_generator(const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners) { + return at::_ops::affine_grid_generator::call(theta, size, align_corners); + } +} + +// aten::affine_grid_generator.out(Tensor theta, SymInt[] size, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & affine_grid_generator_out(at::Tensor & out, const at::Tensor & theta, at::IntArrayRef size, bool align_corners) { + return at::_ops::affine_grid_generator_out::call(theta, c10::fromIntArrayRefSlow(size), align_corners, out); +} +namespace symint { + template ::value>> + at::Tensor & affine_grid_generator_out(at::Tensor & out, const at::Tensor & theta, at::IntArrayRef size, bool align_corners) { + return at::_ops::affine_grid_generator_out::call(theta, c10::fromIntArrayRefSlow(size), align_corners, out); + } +} + +// aten::affine_grid_generator.out(Tensor theta, SymInt[] size, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & affine_grid_generator_outf(const at::Tensor & theta, at::IntArrayRef size, bool align_corners, at::Tensor & out) { + return at::_ops::affine_grid_generator_out::call(theta, c10::fromIntArrayRefSlow(size), align_corners, out); +} +namespace symint { + template ::value>> + at::Tensor & affine_grid_generator_outf(const at::Tensor & theta, at::IntArrayRef size, bool align_corners, at::Tensor & out) { + return at::_ops::affine_grid_generator_out::call(theta, c10::fromIntArrayRefSlow(size), align_corners, out); + } +} + +// aten::affine_grid_generator.out(Tensor theta, SymInt[] size, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & affine_grid_generator_symint_out(at::Tensor & out, const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners) { + return at::_ops::affine_grid_generator_out::call(theta, size, align_corners, out); +} +namespace symint { + template ::value>> + at::Tensor & affine_grid_generator_out(at::Tensor & out, const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners) { + return at::_ops::affine_grid_generator_out::call(theta, size, align_corners, out); + } +} + +// aten::affine_grid_generator.out(Tensor theta, SymInt[] size, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & affine_grid_generator_symint_outf(const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners, at::Tensor & out) { + return at::_ops::affine_grid_generator_out::call(theta, size, align_corners, out); +} +namespace symint { + template ::value>> + at::Tensor & affine_grid_generator_outf(const at::Tensor & theta, c10::SymIntArrayRef size, bool align_corners, at::Tensor & out) { + return at::_ops::affine_grid_generator_out::call(theta, size, align_corners, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/align_tensors_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/align_tensors_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b039c5f6beb132596ff1d5ae9c302878ab95ac59 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/align_tensors_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API align_tensors { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::align_tensors") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "align_tensors(Tensor[] tensors) -> Tensor[]") + static ::std::vector call(at::TensorList tensors); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/all_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/all_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0313b4e988d4f288d7dc6bb10212608dcb92f673 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/all_cuda_dispatch.h @@ -0,0 +1,31 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor all(const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API at::Tensor & all_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false); +TORCH_API at::Tensor & all_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor all(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & all_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & all_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, at::Tensor & out); +TORCH_API at::Tensor all(const at::Tensor & self); +TORCH_API at::Tensor & all_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & all_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/binary_cross_entropy.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/binary_cross_entropy.h new file mode 100644 index 0000000000000000000000000000000000000000..8c405caaf5327d9f3b97be71dd80c2895a7c3302 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/binary_cross_entropy.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::binary_cross_entropy(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean) -> Tensor +inline at::Tensor binary_cross_entropy(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::binary_cross_entropy::call(self, target, weight, reduction); +} + +// aten::binary_cross_entropy.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & binary_cross_entropy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::binary_cross_entropy_out::call(self, target, weight, reduction, out); +} +// aten::binary_cross_entropy.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & binary_cross_entropy_outf(const at::Tensor & self, const at::Tensor & target, const ::std::optional & weight, int64_t reduction, at::Tensor & out) { + return at::_ops::binary_cross_entropy_out::call(self, target, weight, reduction, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_xor_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_xor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c4d99b4af816a7cf2c8c607bad2177b8e28558ac --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_xor_ops.h @@ -0,0 +1,105 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API bitwise_xor_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bitwise_xor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bitwise_xor.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API bitwise_xor_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::bitwise_xor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bitwise_xor.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +struct TORCH_API bitwise_xor_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::bitwise_xor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bitwise_xor.Scalar(Tensor self, Scalar other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API bitwise_xor_Scalar_Tensor { + using schema = at::Tensor (const at::Scalar &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bitwise_xor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bitwise_xor.Scalar_Tensor(Scalar self, Tensor other) -> Tensor") + static at::Tensor call(const at::Scalar & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other); +}; + +struct TORCH_API bitwise_xor_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bitwise_xor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bitwise_xor.Tensor(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API bitwise_xor__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bitwise_xor_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bitwise_xor_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API bitwise_xor__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bitwise_xor_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bitwise_xor_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API bitwise_xor_Scalar_Tensor_out { + using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bitwise_xor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bitwise_xor.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/clip_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/clip_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..40d9c6ae679f663ef4334d3d10d7dc00f2cfde94 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/clip_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API clip { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::clip") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "clip(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max); +}; + +struct TORCH_API clip_Tensor { + using schema = at::Tensor (const at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::clip") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "clip.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max); +}; + +struct TORCH_API clip_ { + using schema = at::Tensor & (at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::clip_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "clip_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const ::std::optional & min, const ::std::optional & max); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const ::std::optional & min, const ::std::optional & max); +}; + +struct TORCH_API clip__Tensor { + using schema = at::Tensor & (at::Tensor &, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::clip_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "clip_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const ::std::optional & min, const ::std::optional & max); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const ::std::optional & min, const ::std::optional & max); +}; + +struct TORCH_API clip_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::clip") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "clip.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); +}; + +struct TORCH_API clip_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const ::std::optional &, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::clip") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "clip.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & min, const ::std::optional & max, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conv1d_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conv1d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8783db0a485627344c365449fe97d6adc8e1e4f4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conv1d_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 conv1d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1); +TORCH_API at::Tensor conv1d_padding_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::string_view padding="valid", c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cummax.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cummax.h new file mode 100644 index 0000000000000000000000000000000000000000..0ac8aa2e4b0bc868c329eaa1905ddbc25deb4cd8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cummax.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::cummax(Tensor self, int dim) -> (Tensor values, Tensor indices) +inline ::std::tuple cummax(const at::Tensor & self, int64_t dim) { + return at::_ops::cummax::call(self, dim); +} + +// aten::cummax.out(Tensor self, int dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple cummax_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim) { + return at::_ops::cummax_out::call(self, dim, values, indices); +} +// aten::cummax.out(Tensor self, int dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple cummax_outf(const at::Tensor & self, int64_t dim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::cummax_out::call(self, dim, values, indices); +} + +// aten::cummax.dimname(Tensor self, Dimname dim) -> (Tensor values, Tensor indices) +inline ::std::tuple cummax(const at::Tensor & self, at::Dimname dim) { + return at::_ops::cummax_dimname::call(self, dim); +} + +// aten::cummax.dimname_out(Tensor self, Dimname dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple cummax_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim) { + return at::_ops::cummax_dimname_out::call(self, dim, values, indices); +} +// aten::cummax.dimname_out(Tensor self, Dimname dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) +inline ::std::tuple cummax_outf(const at::Tensor & self, at::Dimname dim, at::Tensor & values, at::Tensor & indices) { + return at::_ops::cummax_dimname_out::call(self, dim, values, indices); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cumprod_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cumprod_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..86ad6ba180bfb3f549700d4ae4f5be839a398c01 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cumprod_backward_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor cumprod_backward(const at::Tensor & grad, const at::Tensor & input, int64_t dim, const at::Tensor & output); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/dot_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/dot_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5b1afbaf3fad2ce3d9412807d2725e44663d2471 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/dot_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor dot(const at::Tensor & self, const at::Tensor & tensor); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/eye_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/eye_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..92f79da163d3c0d4c1cdc9b05e5ec4c0855ad15f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/eye_compositeexplicitautograd_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor eye(int64_t n, at::TensorOptions options={}); +TORCH_API at::Tensor eye(int64_t n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor eye_symint(c10::SymInt n, at::TensorOptions options={}); +TORCH_API at::Tensor eye_symint(c10::SymInt n, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor eye(int64_t n, int64_t m, at::TensorOptions options={}); +TORCH_API at::Tensor eye(int64_t n, int64_t m, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor eye_symint(c10::SymInt n, c10::SymInt m, at::TensorOptions options={}); +TORCH_API at::Tensor eye_symint(c10::SymInt n, c10::SymInt m, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_irfft2_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_irfft2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9cdd34a375d24c3375907d638e1bfa599020a0b3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_irfft2_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_irfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_irfft2_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fill_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fill_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b46052ac3289a071d001349bee519394aec60b34 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fill_native.h @@ -0,0 +1,33 @@ +#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 fill(const at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_Scalar_out(const at::Tensor & self, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & fill_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_nested_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_sparse_csr_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_meta_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_quantized_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor fill(const at::Tensor & self, const at::Tensor & value); +TORCH_API at::Tensor & fill_Tensor_out(const at::Tensor & self, const at::Tensor & value, at::Tensor & out); +TORCH_API at::Tensor & fill_(at::Tensor & self, const at::Tensor & value); +TORCH_API at::Tensor & fill_nested_(at::Tensor & self, const at::Tensor & value); +TORCH_API at::Tensor & fill_meta_(at::Tensor & self, const at::Tensor & value); +TORCH_API at::Tensor & fill_quantized_(at::Tensor & self, const at::Tensor & value); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/full_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/full_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2e714be1dea653028f78c0bf47652c23b6d420e5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/full_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & full_names_out(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional names, at::Tensor & out); +TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & full_out(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/grid_sampler_2d.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/grid_sampler_2d.h new file mode 100644 index 0000000000000000000000000000000000000000..899b6a2c78281409fd2170b755b76e1c49eefdda --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/grid_sampler_2d.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::grid_sampler_2d(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor +inline at::Tensor grid_sampler_2d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) { + return at::_ops::grid_sampler_2d::call(input, grid, interpolation_mode, padding_mode, align_corners); +} + +// aten::grid_sampler_2d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & grid_sampler_2d_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) { + return at::_ops::grid_sampler_2d_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out); +} +// aten::grid_sampler_2d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & grid_sampler_2d_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out) { + return at::_ops::grid_sampler_2d_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardshrink_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardshrink_native.h new file mode 100644 index 0000000000000000000000000000000000000000..dd66907d167f44ea1372dbbc8f5c395b38aa86db --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardshrink_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_hardshrink_out : public at::meta::structured_hardshrink { +void impl(const at::Tensor & self, const at::Scalar & lambd, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardswish_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardswish_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..65d3357987502c73e8ab39babc5f318e57eff3dc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardswish_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::hardswish_backward(Tensor grad_output, Tensor self) -> Tensor +inline at::Tensor hardswish_backward(const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::hardswish_backward::call(grad_output, self); +} + +// aten::hardswish_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hardswish_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self) { + return at::_ops::hardswish_backward_out::call(grad_output, self, out); +} +// aten::hardswish_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hardswish_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out) { + return at::_ops::hardswish_backward_out::call(grad_output, self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lift_fresh.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lift_fresh.h new file mode 100644 index 0000000000000000000000000000000000000000..10a92525a97a43f129cb6339c3d7b99c27000668 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lift_fresh.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::lift_fresh(Tensor(a) self) -> Tensor(a) +inline at::Tensor lift_fresh(const at::Tensor & self) { + return at::_ops::lift_fresh::call(self); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigh_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7e7544d0dfcd9a985ec03f215abc571599cec646 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigh_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_eigh { + using schema = ::std::tuple (const at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_eigh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_eigh(Tensor self, str UPLO=\"L\") -> (Tensor eigenvalues, Tensor eigenvectors)") + static ::std::tuple call(const at::Tensor & self, c10::string_view UPLO); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view UPLO); +}; + +struct TORCH_API linalg_eigh_eigvals { + using schema = ::std::tuple (const at::Tensor &, c10::string_view, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_eigh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "eigvals") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_eigh.eigvals(Tensor self, str UPLO=\"L\", *, Tensor(a!) eigvals, Tensor(b!) eigvecs) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors)") + static ::std::tuple call(const at::Tensor & self, c10::string_view UPLO, at::Tensor & eigvals, at::Tensor & eigvecs); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view UPLO, at::Tensor & eigvals, at::Tensor & eigvecs); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linear_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linear_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b89506d8e1fce5f99e4079c2a1e08c54d10d2887 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linear_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 linear(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log2_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7ecf57adf7a6ee88ce14dbb2909a5b6a4d2db8a8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log2_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 log2(const at::Tensor & self); +TORCH_API at::Tensor & log2_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & log2_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & log2_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log_sigmoid_forward_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log_sigmoid_forward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e091a8b009506eedddc0ec194bd8dfe99422605f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log_sigmoid_forward_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple log_sigmoid_forward(const at::Tensor & self); +TORCH_API ::std::tuple log_sigmoid_forward_out(at::Tensor & output, at::Tensor & buffer, const at::Tensor & self); +TORCH_API ::std::tuple log_sigmoid_forward_outf(const at::Tensor & self, at::Tensor & output, at::Tensor & buffer); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp2_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..175d42d9973e19b376104b3804796f04468beb27 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logaddexp2_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API logaddexp2_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::logaddexp2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logaddexp2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API logaddexp2 { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::logaddexp2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logaddexp2(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/matrix_exp_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/matrix_exp_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..10e184c5a7292d6d56b022a19d861b05b6e13e12 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/matrix_exp_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 matrix_exp(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_rnn_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_rnn_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..1bb184b9331050b4d6b48b76aada66c58cfcdb59 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_rnn_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::miopen_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[]) +inline ::std::tuple> miopen_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::miopen_rnn_backward::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); +} + +// aten::miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void miopen_rnn_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask) { + return at::_ops::miopen_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); +} +// aten::miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () +inline void miopen_rnn_backward_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const ::std::optional & cx, const at::Tensor & output, const ::std::optional & grad_output, const ::std::optional & grad_hy, const ::std::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const ::std::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3) { + return at::_ops::miopen_rnn_backward_out::call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mul_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mul_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d782ab7eb92a28508672316dfe4485a83af2be80 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mul_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 mul(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & mul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & mul_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d72644e71a34d84ade1a655fec17d322a6acf263 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_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 multi_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional & weight, int64_t reduction, at::Tensor & grad_input); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_group_norm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_group_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..7d6cd1847f4532737f64e90a01cf71e9c34e833f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_group_norm.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::native_group_norm(Tensor input, Tensor? weight, Tensor? bias, SymInt N, SymInt C, SymInt HxW, int group, float eps) -> (Tensor, Tensor, Tensor) +inline ::std::tuple native_group_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps) { + return at::_ops::native_group_norm::call(input, weight, bias, N, C, HxW, group, eps); +} +namespace symint { + template ::value>> + ::std::tuple native_group_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps) { + return at::_ops::native_group_norm::call(input, weight, bias, N, C, HxW, group, eps); + } +} + +// aten::native_group_norm(Tensor input, Tensor? weight, Tensor? bias, SymInt N, SymInt C, SymInt HxW, int group, float eps) -> (Tensor, Tensor, Tensor) +inline ::std::tuple native_group_norm_symint(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps) { + return at::_ops::native_group_norm::call(input, weight, bias, N, C, HxW, group, eps); +} +namespace symint { + template ::value>> + ::std::tuple native_group_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps) { + return at::_ops::native_group_norm::call(input, weight, bias, N, C, HxW, group, eps); + } +} + +// aten::native_group_norm.out(Tensor input, Tensor? weight, Tensor? bias, SymInt N, SymInt C, SymInt HxW, int group, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_group_norm_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps) { + return at::_ops::native_group_norm_out::call(input, weight, bias, N, C, HxW, group, eps, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple native_group_norm_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps) { + return at::_ops::native_group_norm_out::call(input, weight, bias, N, C, HxW, group, eps, out0, out1, out2); + } +} + +// aten::native_group_norm.out(Tensor input, Tensor? weight, Tensor? bias, SymInt N, SymInt C, SymInt HxW, int group, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_group_norm_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_group_norm_out::call(input, weight, bias, N, C, HxW, group, eps, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple native_group_norm_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_group_norm_out::call(input, weight, bias, N, C, HxW, group, eps, out0, out1, out2); + } +} + +// aten::native_group_norm.out(Tensor input, Tensor? weight, Tensor? bias, SymInt N, SymInt C, SymInt HxW, int group, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_group_norm_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps) { + return at::_ops::native_group_norm_out::call(input, weight, bias, N, C, HxW, group, eps, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple native_group_norm_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps) { + return at::_ops::native_group_norm_out::call(input, weight, bias, N, C, HxW, group, eps, out0, out1, out2); + } +} + +// aten::native_group_norm.out(Tensor input, Tensor? weight, Tensor? bias, SymInt N, SymInt C, SymInt HxW, int group, float eps, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple native_group_norm_symint_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_group_norm_out::call(input, weight, bias, N, C, HxW, group, eps, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple native_group_norm_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, c10::SymInt N, c10::SymInt C, c10::SymInt HxW, int64_t group, double eps, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::native_group_norm_out::call(input, weight, bias, N, C, HxW, group, eps, out0, out1, out2); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/norm_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/norm_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..fa9e054b024dd06798871c43c726486072f64958 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/norm_meta.h @@ -0,0 +1,32 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_norm_ScalarOpt_dim_dtype : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::OptionalScalarRef p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); +}; +struct TORCH_API structured_norm_ScalarOpt_dim : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::OptionalScalarRef p, at::IntArrayRef dim, bool keepdim); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/one_hot.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/one_hot.h new file mode 100644 index 0000000000000000000000000000000000000000..04c2eea21912f73e546bf73615ef9889b878bed5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/one_hot.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::one_hot(Tensor self, int num_classes=-1) -> Tensor +inline at::Tensor one_hot(const at::Tensor & self, int64_t num_classes=-1) { + return at::_ops::one_hot::call(self, num_classes); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/outer_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/outer_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b1ca274d9d70c879ebc8a9109f67b41edd21e90a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/outer_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 outer { + 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::outer") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "outer(Tensor self, Tensor vec2) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & vec2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2); +}; + +struct TORCH_API outer_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::outer") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "outer.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/pow_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/pow_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7eecf48fbdeed02fbd22e146fbd676dc1695379b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/pow_cuda_dispatch.h @@ -0,0 +1,33 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor pow(const at::Tensor & self, const at::Tensor & exponent); +TORCH_API at::Tensor & pow_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & exponent); +TORCH_API at::Tensor & pow_outf(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out); +TORCH_API at::Tensor & pow_(at::Tensor & self, const at::Tensor & exponent); +TORCH_API at::Tensor pow(const at::Scalar & self, const at::Tensor & exponent); +TORCH_API at::Tensor & pow_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & exponent); +TORCH_API at::Tensor & pow_outf(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out); +TORCH_API at::Tensor pow(const at::Tensor & self, const at::Scalar & exponent); +TORCH_API at::Tensor & pow_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & exponent); +TORCH_API at::Tensor & pow_outf(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out); +TORCH_API at::Tensor & pow_(at::Tensor & self, const at::Scalar & exponent); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/softshrink_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/softshrink_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..caebd9a5cee5115a09a8fc5da811f14d691f24c0 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/softshrink_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 softshrink(const at::Tensor & self, const at::Scalar & lambd=0.5); +TORCH_API at::Tensor & softshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5); +TORCH_API at::Tensor & softshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sort_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sort_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f8c4a69ed9551e6eb1c20614a9c4d9874442bf23 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sort_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_sort_stable : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, ::std::optional stable, int64_t dim, bool descending); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_csr_tensor_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_csr_tensor_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f3972d9fae14032193f67bbc6f3ed8491d13d309 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_csr_tensor_compositeimplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options); +TORCH_API at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::TensorOptions options); +TORCH_API at::Tensor sparse_csr_tensor(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_airy_ai_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_airy_ai_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cbb15b64c2b26514a8cfc53d1b15bd0e597e602c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_airy_ai_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_airy_ai(const at::Tensor & x); +TORCH_API at::Tensor & special_airy_ai_out(at::Tensor & out, const at::Tensor & x); +TORCH_API at::Tensor & special_airy_ai_outf(const at::Tensor & x, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_i1e.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_i1e.h new file mode 100644 index 0000000000000000000000000000000000000000..ac9970207d431ceb9d1e7bd7f593bd76ddd6e465 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_i1e.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_i1e(Tensor self) -> Tensor +inline at::Tensor special_i1e(const at::Tensor & self) { + return at::_ops::special_i1e::call(self); +} + +// aten::special_i1e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_i1e_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_i1e_out::call(self, out); +} +// aten::special_i1e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_i1e_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_i1e_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3e47a58cd693667194f5e024df2dc3ceb38a08e7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_modified_bessel_i1_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_special_modified_bessel_i1_out : public at::meta::structured_special_modified_bessel_i1 { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_xlogy_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_xlogy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2e42fd18640399d9513ce1a6a958f4b9bffc21dc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_xlogy_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor special_xlogy(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & special_xlogy_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor special_xlogy(const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & special_xlogy_out(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor special_xlogy(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & special_xlogy_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..02d75128fe129f8183a83afcdd13c5b0bead9acd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_constrain_range_for_size_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sym_constrain_range_for_size { + using schema = void (const at::Scalar &, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sym_constrain_range_for_size") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sym_constrain_range_for_size(Scalar size, *, int? min=None, int? max=None) -> ()") + static void call(const at::Scalar & size, ::std::optional min, ::std::optional max); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & size, ::std::optional min, ::std::optional max); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/triangular_solve_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/triangular_solve_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..824ad9b94f95cf2b4f9e204e8e28d9e6d26efafb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/triangular_solve_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API triangular_solve_X { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, bool, bool, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::triangular_solve") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "X") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "triangular_solve.X(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False, *, Tensor(a!) X, Tensor(b!) M) -> (Tensor(a!) solution, Tensor(b!) cloned_coefficient)") + static ::std::tuple call(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M); +}; + +struct TORCH_API triangular_solve { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::triangular_solve") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "triangular_solve(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False) -> (Tensor solution, Tensor cloned_coefficient)") + static ::std::tuple call(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..24ef0cd05e00fc138610130bbfc9d1289fd4f785 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::upsample_nearest3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & upsample_nearest3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & upsample_nearest3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & upsample_nearest3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & upsample_nearest3d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); +} +namespace symint { + template ::value>> + at::Tensor & upsample_nearest3d_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input) { + return at::_ops::upsample_nearest3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::upsample_nearest3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_nearest3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor upsample_nearest3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w); + } +} + +// aten::upsample_nearest3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline at::Tensor upsample_nearest3d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor upsample_nearest3d_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales_d=::std::nullopt, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt) { + return at::_ops::upsample_nearest3d_backward::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/values_copy_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/values_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d1a2d836f39ae8b6cd48e32fde91d07b2c7e1e4d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/values_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & values_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & values_copy_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_as_complex_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_as_complex_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f1e571fcf2c497f02a4942aea90d55dfcf34bf74 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_as_complex_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor view_as_complex(const at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_as_complex_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_as_complex_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5c16c2886f0937900f171c8db992520237426334 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_as_complex_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 view_as_complex(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_copy_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7827b3e7ad7c2aae9690cb28e325c447effc406b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/view_copy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor & view_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & view_copy_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size); +TORCH_API at::Tensor & view_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, at::ScalarType dtype); +TORCH_API at::Tensor & view_copy_outf(const at::Tensor & self, at::ScalarType dtype, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at