diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_conv_depthwise2d.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_conv_depthwise2d.h new file mode 100644 index 0000000000000000000000000000000000000000..94baa7798be159736f43e065a928cdfd4927aba2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_conv_depthwise2d.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::_conv_depthwise2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, SymInt[2] dilation, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & _conv_depthwise2d_out(const at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation) { + return at::_ops::_conv_depthwise2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template ::value>> + const at::Tensor & _conv_depthwise2d_out(const at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation) { + return at::_ops::_conv_depthwise2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::_conv_depthwise2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, SymInt[2] dilation, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & _conv_depthwise2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, const at::Tensor & out) { + return at::_ops::_conv_depthwise2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); +} +namespace symint { + template ::value>> + const at::Tensor & _conv_depthwise2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, const at::Tensor & out) { + return at::_ops::_conv_depthwise2d_out::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), out); + } +} + +// aten::_conv_depthwise2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, SymInt[2] dilation, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & _conv_depthwise2d_symint_out(const at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation) { + return at::_ops::_conv_depthwise2d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); +} +namespace symint { + template ::value>> + const at::Tensor & _conv_depthwise2d_out(const at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation) { + return at::_ops::_conv_depthwise2d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); + } +} + +// aten::_conv_depthwise2d.out(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, SymInt[2] dilation, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & _conv_depthwise2d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, const at::Tensor & out) { + return at::_ops::_conv_depthwise2d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); +} +namespace symint { + template ::value>> + const at::Tensor & _conv_depthwise2d_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, const at::Tensor & out) { + return at::_ops::_conv_depthwise2d_out::call(self, weight, kernel_size, bias, stride, padding, dilation, out); + } +} + +// aten::_conv_depthwise2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, SymInt[2] dilation) -> Tensor +inline at::Tensor _conv_depthwise2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation) { + return at::_ops::_conv_depthwise2d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation)); +} +namespace symint { + template ::value>> + at::Tensor _conv_depthwise2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation) { + return at::_ops::_conv_depthwise2d::call(self, weight, c10::fromIntArrayRefSlow(kernel_size), bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation)); + } +} + +// aten::_conv_depthwise2d(Tensor self, Tensor weight, SymInt[2] kernel_size, Tensor? bias, SymInt[2] stride, SymInt[2] padding, SymInt[2] dilation) -> Tensor +inline at::Tensor _conv_depthwise2d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation) { + return at::_ops::_conv_depthwise2d::call(self, weight, kernel_size, bias, stride, padding, dilation); +} +namespace symint { + template ::value>> + at::Tensor _conv_depthwise2d(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation) { + return at::_ops::_conv_depthwise2d::call(self, weight, kernel_size, bias, stride, padding, dilation); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convert_indices_from_coo_to_csr_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convert_indices_from_coo_to_csr_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4ae163a4737fa1338fc539276669624987037885 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convert_indices_from_coo_to_csr_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor _convert_indices_from_coo_to_csr(const at::Tensor & self, int64_t size, bool out_int32=false); +TORCH_API at::Tensor & _convert_indices_from_coo_to_csr_out(at::Tensor & out, const at::Tensor & self, int64_t size, bool out_int32=false); +TORCH_API at::Tensor & _convert_indices_from_coo_to_csr_outf(const at::Tensor & self, int64_t size, bool out_int32, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4c67167b10c5c244d2b11a84b69b784010892548 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cslt_sparse_mm_search { + using schema = int64_t (const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, ::std::optional, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cslt_sparse_mm_search") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cslt_sparse_mm_search(Tensor compressed_A, Tensor dense_B, Tensor? bias=None, Tensor? alpha=None, ScalarType? out_dtype=None, bool transpose_result=False) -> int") + static int64_t call(const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias, const ::std::optional & alpha, ::std::optional out_dtype, bool transpose_result); + static int64_t redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias, const ::std::optional & alpha, ::std::optional out_dtype, bool transpose_result); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..340a05df41f78efb7dc504f0ef8d7bec77ac2109 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_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 _embedding_bag_backward_symint(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, int64_t padding_idx=-1); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..038d80f96d37cb279eb5599dfe06f76ca68efbe5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_backward_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _fake_quantize_learnable_per_channel_affine_backward(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_flash_attention_forward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_flash_attention_forward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c1ca7d808ee98e6b2462ba364b65bfdfea36c574 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_flash_attention_forward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _flash_attention_forward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, c10::SymInt, c10::SymInt, double, bool, bool, ::std::optional, ::std::optional, ::std::optional, 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::_flash_attention_forward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? cum_seq_q, Tensor? cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, bool return_debug_mask, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None, Tensor? seqused_k=None, Tensor? alibi_slopes=None) -> (Tensor output, Tensor softmax_logsumexp, Tensor philox_seed, Tensor philox_offset, Tensor debug_attn_mask)") + static ::std::tuple call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right, const ::std::optional & seqused_k, const ::std::optional & alibi_slopes); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & cum_seq_q, const ::std::optional & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, bool return_debug_mask, ::std::optional scale, ::std::optional window_size_left, ::std::optional window_size_right, const ::std::optional & seqused_k, const ::std::optional & alibi_slopes); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_clamp_min_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_clamp_min_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..02ac86a70b8a5adde7363e6e9b4c5edb302ebe9f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_clamp_min_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_clamp_min(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_min_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_clamp_min_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_clamp_min_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_clamp_min(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_min_out(at::TensorList out, at::TensorList self, at::TensorList other); +TORCH_API void _foreach_clamp_min_outf(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void _foreach_clamp_min_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_clamp_min(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_min_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_clamp_min_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_clamp_min_(at::TensorList self, at::ArrayRef scalars); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_div_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_div_native.h new file mode 100644 index 0000000000000000000000000000000000000000..566d54a7111eb5045c2ed07921c90c0715d03748 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_div_native.h @@ -0,0 +1,40 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_div_scalar_kernel_slow(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_Scalar_out(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void foreach_tensor_div_scalar_kernel_slow_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_div_scalar_kernel_cuda(at::TensorList self, const at::Scalar & scalar); +TORCH_API void foreach_tensor_div_scalar_kernel_cuda_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector foreach_tensor_div_list_kernel_slow(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_List_out(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void foreach_tensor_div_list_kernel_slow_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_div_list_kernel_cuda(at::TensorList self, at::TensorList other); +TORCH_API void foreach_tensor_div_list_kernel_cuda_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector foreach_tensor_div_scalarlist_kernel_slow(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_ScalarList_out(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void foreach_tensor_div_scalarlist_kernel_slow_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_div_scalarlist_kernel_cuda(at::TensorList self, at::ArrayRef scalars); +TORCH_API void foreach_tensor_div_scalarlist_kernel_cuda_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector foreach_tensor_div_tensor_kernel_slow(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_Tensor_out(at::TensorList self, const at::Tensor & other, at::TensorList out); +TORCH_API void foreach_tensor_div_tensor_kernel_slow_(at::TensorList self, const at::Tensor & other); +TORCH_API ::std::vector foreach_tensor_div_tensor_kernel_cuda(at::TensorList self, const at::Tensor & other); +TORCH_API void foreach_tensor_div_tensor_kernel_cuda_(at::TensorList self, const at::Tensor & other); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_expm1_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_expm1_native.h new file mode 100644 index 0000000000000000000000000000000000000000..aacd9e5c7524ec8b3e85ce449042ba1ab9dd20df --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_expm1_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_expm1_slow(at::TensorList self); +TORCH_API void _foreach_expm1_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_expm1_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_expm1_cuda(at::TensorList self); +TORCH_API void foreach_tensor_expm1_cuda_(at::TensorList self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log10_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log10_native.h new file mode 100644 index 0000000000000000000000000000000000000000..26edf334ef599f2f3d20c6274175ee7a5c39cbdc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_log10_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_log10_slow(at::TensorList self); +TORCH_API void _foreach_log10_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_log10_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_log10_cuda(at::TensorList self); +TORCH_API void foreach_tensor_log10_cuda_(at::TensorList self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_reciprocal.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_reciprocal.h new file mode 100644 index 0000000000000000000000000000000000000000..b20311848a3e2dda6a3c8f61e8ad3678d95b51f7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_reciprocal.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_reciprocal(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_reciprocal(at::TensorList self) { + return at::_ops::_foreach_reciprocal::call(self); +} + +// aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () +inline void _foreach_reciprocal_(at::TensorList self) { + return at::_ops::_foreach_reciprocal_::call(self); +} + +// aten::_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_reciprocal_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_reciprocal_out::call(self, out); +} +// aten::_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_reciprocal_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_reciprocal_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_solve_ex_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_solve_ex_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b2532ae7e83b02e9937df89a033fad310bace609 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_solve_ex_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple _linalg_solve_ex(const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false); +TORCH_API ::std::tuple _linalg_solve_ex_out(at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info, const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false); +TORCH_API ::std::tuple _linalg_solve_ex_outf(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ec6e5481eae2f8a2ef8cb37dbec58f22669767d8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_native_batch_norm_legit_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple _native_batch_norm_legit_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple _native_batch_norm_legit_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); +TORCH_API ::std::tuple _native_batch_norm_legit(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps); +TORCH_API ::std::tuple _native_batch_norm_legit(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, bool training, double momentum, double eps); +TORCH_API ::std::tuple _native_batch_norm_legit_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, bool training, double momentum, double eps); +TORCH_API ::std::tuple _native_batch_norm_legit_outf(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nnpack_available_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nnpack_available_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bff83d424f68893804b769008362bd60948aa01c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nnpack_available_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API bool _nnpack_available(); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nnz.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nnz.h new file mode 100644 index 0000000000000000000000000000000000000000..6d4e4d54c1d318391a9d717c0933c0e24a61deda --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nnz.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_reshape_copy_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_reshape_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a377faa66cc7c3c47f50be88e9dc8d5c9c31f3fd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_reshape_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 _reshape_copy(const at::Tensor & self, at::IntArrayRef size); +TORCH_API at::Tensor _reshape_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_reshape_copy_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_reshape_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ec9b77a0e21ca36de0b10d3bac907ff1a5f02dd1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_reshape_copy_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _reshape_copy { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_reshape_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_reshape_copy(Tensor self, SymInt[] size) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_addmm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_addmm.h new file mode 100644 index 0000000000000000000000000000000000000000..d785331a9732e73beb34e12b92e16e2e7e03bba2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_addmm.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_addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor +inline at::Tensor _sparse_addmm(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::_sparse_addmm::call(self, mat1, mat2, beta, alpha); +} + +// aten::_sparse_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_addmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::_sparse_addmm_out::call(self, mat1, mat2, beta, alpha, out); +} +// aten::_sparse_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_addmm_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { + return at::_ops::_sparse_addmm_out::call(self, mat1, mat2, beta, alpha, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..87a19490246e32a018e7feb708af386ba430ef7c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _sparse_coo_tensor_with_dims_out(at::Tensor & out, int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size); +TORCH_API at::Tensor & _sparse_coo_tensor_with_dims_outf(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_log_softmax_backward_data.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_log_softmax_backward_data.h new file mode 100644 index 0000000000000000000000000000000000000000..41f3eed237864b269383685b38c933e5035c87fd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_log_softmax_backward_data.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_log_softmax_backward_data(Tensor grad_output, Tensor output, int dim, Tensor self) -> Tensor +inline at::Tensor _sparse_log_softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self) { + return at::_ops::_sparse_log_softmax_backward_data::call(grad_output, output, dim, self); +} + +// aten::_sparse_log_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_log_softmax_backward_data_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self) { + return at::_ops::_sparse_log_softmax_backward_data_out::call(grad_output, output, dim, self, out); +} +// aten::_sparse_log_softmax_backward_data.out(Tensor grad_output, Tensor output, int dim, Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_log_softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self, at::Tensor & out) { + return at::_ops::_sparse_log_softmax_backward_data_out::call(grad_output, output, dim, self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_dense_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_dense_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ab23699eed31210c2aca7bd89ef7674e7ff43a9c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_to_dense_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_dense { + using schema = at::Tensor (const at::Tensor &, ::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::_to_dense") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_to_dense(Tensor self, ScalarType? dtype=None, bool? masked_grad=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad); +}; + +struct TORCH_API _to_dense_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_to_dense") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_to_dense.out(Tensor self, ScalarType? dtype=None, bool? masked_grad=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f57c06bfd59ac248fa8ba3e178cb5e7a8b6afeea --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_transformer_encoder_layer_fwd_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 _transformer_encoder_layer_fwd(const at::Tensor & src, int64_t embed_dim, int64_t num_heads, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, bool use_gelu, bool norm_first, double eps, const at::Tensor & norm_weight_1, const at::Tensor & norm_bias_1, const at::Tensor & norm_weight_2, const at::Tensor & norm_bias_2, const at::Tensor & ffn_weight_1, const at::Tensor & ffn_bias_1, const at::Tensor & ffn_weight_2, const at::Tensor & ffn_bias_2, const ::std::optional & mask={}, ::std::optional mask_type=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..c2eb6ba863f352332f838820579ad2809ad665ab --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_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_nearest_exact3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::_upsample_nearest_exact3d_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_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) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_nearest_exact3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::_upsample_nearest_exact3d_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_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) { + return at::_ops::_upsample_nearest_exact3d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_nearest_exact3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::_upsample_nearest_exact3d_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_nearest_exact3d_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_nearest_exact3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_nearest_exact3d_backward.grad_input(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline 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) { + return at::_ops::_upsample_nearest_exact3d_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_nearest_exact3d_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_nearest_exact3d_backward_grad_input::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w, grad_input); + } +} + +// aten::_upsample_nearest_exact3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline 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) { + return at::_ops::_upsample_nearest_exact3d_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_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) { + return at::_ops::_upsample_nearest_exact3d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales_d, scales_h, scales_w); + } +} + +// aten::_upsample_nearest_exact3d_backward(Tensor grad_output, SymInt[3] output_size, SymInt[5] input_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor +inline 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) { + return at::_ops::_upsample_nearest_exact3d_backward::call(grad_output, output_size, input_size, scales_d, scales_h, scales_w); +} +namespace symint { + template ::value>> + at::Tensor _upsample_nearest_exact3d_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_nearest_exact3d_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/_upsample_nearest_exact3d_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..76805b0560d0addc44fe35de8e3813db16e73ae0 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact3d_backward_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured__upsample_nearest_exact3d_backward_out_cpu : public at::meta::structured__upsample_nearest_exact3d_backward { +void impl(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & grad_input); +}; +struct TORCH_API structured__upsample_nearest_exact3d_backward_out_cuda : public at::meta::structured__upsample_nearest_exact3d_backward { +void impl(const at::Tensor & grad_output, at::ArrayRef output_size, at::ArrayRef input_size, ::std::optional scales_d, ::std::optional scales_h, ::std::optional scales_w, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_norm_interface_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_norm_interface_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7c176e3be86dc464965287b2939b7e7a3fde3920 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_norm_interface_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple _weight_norm_interface_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & v, const at::Tensor & g, int64_t dim=0); +TORCH_API ::std::tuple _weight_norm_interface_outf(const at::Tensor & v, const at::Tensor & g, int64_t dim, at::Tensor & out0, at::Tensor & out1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/addbmm_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/addbmm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9149d75e1d5c56f5c1aa0c3ee9e38e0cdb598256 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/addbmm_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 addbmm(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addbmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); +TORCH_API at::Tensor & addbmm_outf(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & addbmm_(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/addmv.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/addmv.h new file mode 100644 index 0000000000000000000000000000000000000000..079b2ac61ee23065659ad7b91086306d68ce945c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/addmv.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::addmv(Tensor self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1) -> Tensor +inline at::Tensor addmv(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::addmv::call(self, mat, vec, beta, alpha); +} + +// aten::addmv_(Tensor(a!) self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!) +inline at::Tensor & addmv_(at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::addmv_::call(self, mat, vec, beta, alpha); +} + +// aten::addmv.out(Tensor self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & addmv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::addmv_out::call(self, mat, vec, beta, alpha, out); +} +// aten::addmv.out(Tensor self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & addmv_outf(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { + return at::_ops::addmv_out::call(self, mat, vec, beta, alpha, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/alias_copy_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/alias_copy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..91a30e97276ae5688ad401101304851f9d7b6de0 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/alias_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 & alias_copy_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & alias_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/amin_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/amin_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..070e076deefdb32f9536eec9cbe1ec2a3d4e77d2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/amin_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_amin : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::IntArrayRef dim, bool keepdim); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/as_strided_copy_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/as_strided_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..76f60122ce47d81cc25802c6fb7eb27f7877b41e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/as_strided_copy_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API as_strided_copy { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::as_strided_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "as_strided_copy(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset); +}; + +struct TORCH_API as_strided_copy_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::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::as_strided_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional storage_offset, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan.h new file mode 100644 index 0000000000000000000000000000000000000000..2af744ea516f39d0917ef39cbe2841095d6002a7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::atan(Tensor self) -> Tensor +inline at::Tensor atan(const at::Tensor & self) { + return at::_ops::atan::call(self); +} + +// aten::atan_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & atan_(at::Tensor & self) { + return at::_ops::atan_::call(self); +} + +// aten::atan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atan_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::atan_out::call(self, out); +} +// aten::atan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & atan_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::atan_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan2_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan2_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..f135a917b01a1ab9aef62d485c03cfadbc8c71d8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan2_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_atan2 : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & other); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/binomial.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/binomial.h new file mode 100644 index 0000000000000000000000000000000000000000..366dd2ddd7d96862c746452900427f1ce8fe5608 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/binomial.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::binomial(Tensor count, Tensor prob, Generator? generator=None) -> Tensor +inline at::Tensor binomial(const at::Tensor & count, const at::Tensor & prob, ::std::optional generator=::std::nullopt) { + return at::_ops::binomial::call(count, prob, generator); +} + +// aten::binomial.out(Tensor count, Tensor prob, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & binomial_out(at::Tensor & out, const at::Tensor & count, const at::Tensor & prob, ::std::optional generator=::std::nullopt) { + return at::_ops::binomial_out::call(count, prob, generator, out); +} +// aten::binomial.out(Tensor count, Tensor prob, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & binomial_outf(const at::Tensor & count, const at::Tensor & prob, ::std::optional generator, at::Tensor & out) { + return at::_ops::binomial_out::call(count, prob, generator, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/binomial_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/binomial_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..887c594703b20258d2a1227d605763e296503435 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/binomial_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 binomial { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::binomial") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "binomial(Tensor count, Tensor prob, Generator? generator=None) -> Tensor") + static at::Tensor call(const at::Tensor & count, const at::Tensor & prob, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & count, const at::Tensor & prob, ::std::optional generator); +}; + +struct TORCH_API binomial_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::binomial") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "binomial.out(Tensor count, Tensor prob, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & count, const at::Tensor & prob, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & count, const at::Tensor & prob, ::std::optional generator, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_or_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_or_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..810b8552c3c244ef801aa5dcea6e1c0d528aea21 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_or_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor bitwise_or(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_or_(at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/blackman_window_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/blackman_window_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f2f77f6d1a3c589e2f239fc84213251daa955798 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/blackman_window_ops.h @@ -0,0 +1,61 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API blackman_window { + using schema = at::Tensor (int64_t, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::blackman_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "blackman_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API blackman_window_periodic { + using schema = at::Tensor (int64_t, bool, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::blackman_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "periodic") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "blackman_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API blackman_window_out { + using schema = at::Tensor & (int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::blackman_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "blackman_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(int64_t window_length, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, at::Tensor & out); +}; + +struct TORCH_API blackman_window_periodic_out { + using schema = at::Tensor & (int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::blackman_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "periodic_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "blackman_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(int64_t window_length, bool periodic, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bucketize.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bucketize.h new file mode 100644 index 0000000000000000000000000000000000000000..14c2b82548395e0e1218c688ea8f45d0288d044b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bucketize.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::bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor +inline at::Tensor bucketize(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false) { + return at::_ops::bucketize_Tensor::call(self, boundaries, out_int32, right); +} + +// aten::bucketize.Tensor_out(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bucketize_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false) { + return at::_ops::bucketize_Tensor_out::call(self, boundaries, out_int32, right, out); +} +// aten::bucketize.Tensor_out(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bucketize_outf(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out) { + return at::_ops::bucketize_Tensor_out::call(self, boundaries, out_int32, right, out); +} + +// aten::bucketize.Scalar(Scalar self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor +inline at::Tensor bucketize(const at::Scalar & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false) { + return at::_ops::bucketize_Scalar::call(self, boundaries, out_int32, right); +} + +// aten::bucketize.Scalar_out(Scalar self, Tensor boundaries, *, bool out_int32=False, bool right=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bucketize_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false) { + return at::_ops::bucketize_Scalar_out::call(self, boundaries, out_int32, right, out); +} +// aten::bucketize.Scalar_out(Scalar self, Tensor boundaries, *, bool out_int32=False, bool right=False, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bucketize_outf(const at::Scalar & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out) { + return at::_ops::bucketize_Scalar_out::call(self, boundaries, out_int32, right, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/chunk_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/chunk_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..aac9df715b55ef802e9a9bfed2a30d89ca82ad78 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/chunk_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API chunk { + using schema = ::std::vector (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::chunk") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "chunk(Tensor(a -> *) self, int chunks, int dim=0) -> Tensor(a)[]") + static ::std::vector call(const at::Tensor & self, int64_t chunks, int64_t dim); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t chunks, int64_t dim); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/coalesce_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/coalesce_native.h new file mode 100644 index 0000000000000000000000000000000000000000..64541e8abae75ab0a0d7d8915109cfb485668dc3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/coalesce_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 coalesce(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/div_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/div_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ec2a958cac6475218d6eeca2dea5ba07abc760b2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/div_cpu_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 cpu { + +TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out); +TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/divide_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/divide_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..3cd3b2b5371d5d6e9f7ed210e1c8cff6a90c508b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/divide_ops.h @@ -0,0 +1,127 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API divide_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::divide") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide.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 divide__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::divide_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide_.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 divide_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::divide") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide.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 divide_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::divide") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide.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 divide__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::divide_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide_.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 divide_Tensor_mode { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::divide") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_mode") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide.Tensor_mode(Tensor self, Tensor other, *, str? rounding_mode) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +}; + +struct TORCH_API divide__Tensor_mode { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::divide_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_mode") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide_.Tensor_mode(Tensor(a!) self, Tensor other, *, str? rounding_mode) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode); +}; + +struct TORCH_API divide_out_mode { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::divide") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out_mode") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide.out_mode(Tensor self, Tensor other, *, str? rounding_mode, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, ::std::optional rounding_mode, at::Tensor & out); +}; + +struct TORCH_API divide_Scalar_mode { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::divide") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_mode") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide.Scalar_mode(Tensor self, Scalar other, *, str? rounding_mode) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); +}; + +struct TORCH_API divide__Scalar_mode { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::divide_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_mode") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "divide_.Scalar_mode(Tensor(a!) self, Scalar other, *, str? rounding_mode) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other, ::std::optional rounding_mode); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/empty_permuted_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/empty_permuted_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..958c685cc2650f6273cf8cc8d322ffa294aed4bb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/empty_permuted_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 empty_permuted(at::IntArrayRef size, at::IntArrayRef physical_layout, at::TensorOptions options={}); +TORCH_API at::Tensor empty_permuted(at::IntArrayRef size, at::IntArrayRef physical_layout, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor empty_permuted_symint(c10::SymIntArrayRef size, at::IntArrayRef physical_layout, at::TensorOptions options={}); +TORCH_API at::Tensor empty_permuted_symint(c10::SymIntArrayRef size, at::IntArrayRef physical_layout, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +TORCH_API at::Tensor & empty_permuted_out(at::Tensor & out, at::IntArrayRef size, at::IntArrayRef physical_layout); +TORCH_API at::Tensor & empty_permuted_outf(at::IntArrayRef size, at::IntArrayRef physical_layout, at::Tensor & out); +TORCH_API at::Tensor & empty_permuted_symint_out(at::Tensor & out, c10::SymIntArrayRef size, at::IntArrayRef physical_layout); +TORCH_API at::Tensor & empty_permuted_symint_outf(c10::SymIntArrayRef size, at::IntArrayRef physical_layout, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/empty_permuted_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/empty_permuted_native.h new file mode 100644 index 0000000000000000000000000000000000000000..09ebd73cb99e5eddc7d24bba771e0dd80c594fe6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/empty_permuted_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 empty_permuted_symint(c10::SymIntArrayRef size, at::IntArrayRef physical_layout, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}); +TORCH_API at::Tensor & empty_permuted_out_symint(c10::SymIntArrayRef size, at::IntArrayRef physical_layout, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/eye_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/eye_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d720fde72796a593add5ddcfeda51ce8dcb532f8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/eye_cpu_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 cpu { + +TORCH_API at::Tensor & eye_out(at::Tensor & out, int64_t n); +TORCH_API at::Tensor & eye_outf(int64_t n, at::Tensor & out); +TORCH_API at::Tensor & eye_symint_out(at::Tensor & out, c10::SymInt n); +TORCH_API at::Tensor & eye_symint_outf(c10::SymInt n, at::Tensor & out); +TORCH_API at::Tensor & eye_out(at::Tensor & out, int64_t n, int64_t m); +TORCH_API at::Tensor & eye_outf(int64_t n, int64_t m, at::Tensor & out); +TORCH_API at::Tensor & eye_symint_out(at::Tensor & out, c10::SymInt n, c10::SymInt m); +TORCH_API at::Tensor & eye_symint_outf(c10::SymInt n, c10::SymInt m, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/feature_alpha_dropout.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/feature_alpha_dropout.h new file mode 100644 index 0000000000000000000000000000000000000000..13e1ea8d3a1f3c0ed65735eae424b098fd18bf91 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/feature_alpha_dropout.h @@ -0,0 +1,35 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::feature_alpha_dropout(Tensor input, float p, bool train) -> Tensor +inline at::Tensor feature_alpha_dropout(const at::Tensor & input, double p, bool train) { + return at::_ops::feature_alpha_dropout::call(input, p, train); +} + +// aten::feature_alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) +inline at::Tensor & feature_alpha_dropout_(at::Tensor & self, double p, bool train) { + return at::_ops::feature_alpha_dropout_::call(self, p, train); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gru_cell_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gru_cell_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..67e4fb6c879917e1394cf4ce10d21544f958d8bd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gru_cell_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 gru_cell { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const 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::gru_cell") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional & b_ih, const ::std::optional & b_hh); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional & b_ih, const ::std::optional & b_hh); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/histogramdd_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/histogramdd_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..232d6bc84949ceca5a52cfb46454227362799d65 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/histogramdd_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API histogramdd { + using schema = ::std::tuple> (const at::Tensor &, at::IntArrayRef, ::std::optional>, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::histogramdd") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "histogramdd(Tensor self, int[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges)") + static ::std::tuple> call(const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density); + static ::std::tuple> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef bins, ::std::optional> range, const ::std::optional & weight, bool density); +}; + +struct TORCH_API histogramdd_int_bins { + using schema = ::std::tuple> (const at::Tensor &, int64_t, ::std::optional>, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::histogramdd") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "int_bins") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "histogramdd.int_bins(Tensor self, int bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges)") + static ::std::tuple> call(const at::Tensor & self, int64_t bins, ::std::optional> range, const ::std::optional & weight, bool density); + static ::std::tuple> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t bins, ::std::optional> range, const ::std::optional & weight, bool density); +}; + +struct TORCH_API histogramdd_TensorList_bins { + using schema = ::std::tuple> (const at::Tensor &, at::TensorList, ::std::optional>, const ::std::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::histogramdd") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "TensorList_bins") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "histogramdd.TensorList_bins(Tensor self, Tensor[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges)") + static ::std::tuple> call(const at::Tensor & self, at::TensorList bins, ::std::optional> range, const ::std::optional & weight, bool density); + static ::std::tuple> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList bins, ::std::optional> range, const ::std::optional & weight, bool density); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_copy_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8840e6f40e210e20efc16443bc127ae901101f5a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor index_copy(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); +TORCH_API at::Tensor & index_copy_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/int_repr.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/int_repr.h new file mode 100644 index 0000000000000000000000000000000000000000..3d515e3aed167767d246dbe1694b086152b6d9ea --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/int_repr.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::int_repr(Tensor self) -> Tensor +inline at::Tensor int_repr(const at::Tensor & self) { + return at::_ops::int_repr::call(self); +} + +// aten::int_repr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & int_repr_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::int_repr_out::call(self, out); +} +// aten::int_repr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & int_repr_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::int_repr_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/is_same_size_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/is_same_size_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1c7b8206515af1375770ce99df6ac17821cc3dd7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/is_same_size_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API bool is_same_size(const at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/le_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/le_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..447d73bd4d2726489ba9dc5ad9cdb053330c09cb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/le_cuda_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor le(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & le_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & le_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & le_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor le(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & le_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & le_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & le_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cond_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cond_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..181f054a40539308fa9c8a402bd1dc192534fe41 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_cond_ops.h @@ -0,0 +1,61 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_cond { + using schema = at::Tensor (const at::Tensor &, 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::linalg_cond") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_cond(Tensor self, Scalar? p=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, const ::std::optional & p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p); +}; + +struct TORCH_API linalg_cond_out { + using schema = at::Tensor & (const at::Tensor &, 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::linalg_cond") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_cond.out(Tensor self, Scalar? p=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const ::std::optional & p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional & p, at::Tensor & out); +}; + +struct TORCH_API linalg_cond_p_str { + using schema = at::Tensor (const at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_cond") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "p_str") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_cond.p_str(Tensor self, str p) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::string_view p); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view p); +}; + +struct TORCH_API linalg_cond_p_str_out { + using schema = at::Tensor & (const at::Tensor &, c10::string_view, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_cond") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "p_str_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_cond.p_str_out(Tensor self, str p, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::string_view p, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view p, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigvals_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigvals_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e0e67196e7e99e572bfb56ca7ed2fe4020d5303a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigvals_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor linalg_eigvals(const at::Tensor & self); +TORCH_API at::Tensor & linalg_eigvals_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/linalg_householder_product_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_householder_product_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ec9f3d689bcfe46ba0984437e4c33c91370f47a4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_householder_product_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 linalg_householder_product(const at::Tensor & input, const at::Tensor & tau); +TORCH_API at::Tensor & linalg_householder_product_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & tau); +TORCH_API at::Tensor & linalg_householder_product_outf(const at::Tensor & input, const at::Tensor & tau, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_vander_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_vander_native.h new file mode 100644 index 0000000000000000000000000000000000000000..82bd09f87c838d3b9b2d1248f4221c3e2baae79a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_vander_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor linalg_vander_symint(const at::Tensor & x, ::std::optional N=::std::nullopt); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e6895456452f63e0a29d93c384a7ed6dff5e0b25 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log_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 log(const at::Tensor & self); +TORCH_API at::Tensor & log_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & log_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & log_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/minimum.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/minimum.h new file mode 100644 index 0000000000000000000000000000000000000000..aa40802df29f1cb8c90a354bff289c4b6c02150b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/minimum.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::minimum(Tensor self, Tensor other) -> Tensor +inline at::Tensor minimum(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::minimum::call(self, other); +} + +// aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & minimum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::minimum_out::call(self, other, out); +} +// aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & minimum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::minimum_out::call(self, other, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..214c2f2f306ec300ef4cf4b87e61542fbca6e0d4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_convolution_transpose_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & miopen_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor & miopen_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out); +TORCH_API at::Tensor & miopen_convolution_transpose_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor & miopen_convolution_transpose_symint_outf(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..ad67fea0315fd9d5afab36ac64affed1b671456f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss.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::multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multi_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multi_margin_loss_out::call(self, target, p, margin, weight, reduction, out); +} +// aten::multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & multi_margin_loss_outf(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 & out) { + return at::_ops::multi_margin_loss_out::call(self, target, p, margin, weight, reduction, out); +} + +// aten::multi_margin_loss(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean) -> Tensor +inline at::Tensor multi_margin_loss(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional & weight={}, int64_t reduction=at::Reduction::Mean) { + return at::_ops::multi_margin_loss::call(self, target, p, margin, weight, reduction); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/new_empty_strided.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/new_empty_strided.h new file mode 100644 index 0000000000000000000000000000000000000000..64d1582d91ed68c60a74d95df9884d1d8ebb3145 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/new_empty_strided.h @@ -0,0 +1,97 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +namespace symint { + template ::value>> + at::Tensor new_empty_strided(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, at::TensorOptions options={}) { + return at::_ops::new_empty_strided::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +namespace symint { + template ::value>> + at::Tensor new_empty_strided(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::new_empty_strided::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), dtype, layout, device, pin_memory); + } +} + +namespace symint { + template ::value>> + at::Tensor new_empty_strided(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::TensorOptions options={}) { + return at::_ops::new_empty_strided::call(self, size, stride, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +namespace symint { + template ::value>> + at::Tensor new_empty_strided(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::new_empty_strided::call(self, size, stride, dtype, layout, device, pin_memory); + } +} + +// aten::new_empty_strided.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_empty_strided_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::new_empty_strided_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & new_empty_strided_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::new_empty_strided_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::new_empty_strided.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_empty_strided_outf(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::new_empty_strided_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & new_empty_strided_outf(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::new_empty_strided_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::new_empty_strided.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_empty_strided_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::new_empty_strided_out::call(self, size, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & new_empty_strided_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::new_empty_strided_out::call(self, size, stride, out); + } +} + +// aten::new_empty_strided.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & new_empty_strided_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::new_empty_strided_out::call(self, size, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & new_empty_strided_outf(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::new_empty_strided_out::call(self, size, stride, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nonzero_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nonzero_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80a2822eae34421ac1a5ccaedfa5157ae3e57017 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nonzero_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API nonzero_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nonzero") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nonzero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API nonzero { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::nonzero") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "nonzero(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/polar_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/polar_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b20e365abf3feee7e1a3e4b4c8269b01a09b0ff7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/polar_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 polar(const at::Tensor & abs, const at::Tensor & angle); +TORCH_API at::Tensor & polar_out(const at::Tensor & abs, const at::Tensor & angle, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_max_pool1d_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_max_pool1d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d537b59bf7f3455659542d6bb3e33ee614e47a12 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/quantized_max_pool1d_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 & quantized_max_pool1d_out(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out); +TORCH_API at::Tensor quantized_max_pool1d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reflection_pad1d.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reflection_pad1d.h new file mode 100644 index 0000000000000000000000000000000000000000..57867d25ab4e2ce7905f8ca8431bff2ac3b0b9fe --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reflection_pad1d.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & reflection_pad1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::reflection_pad1d_out::call(self, c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template ::value>> + at::Tensor & reflection_pad1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::reflection_pad1d_out::call(self, c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & reflection_pad1d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::reflection_pad1d_out::call(self, c10::fromIntArrayRefSlow(padding), out); +} +namespace symint { + template ::value>> + at::Tensor & reflection_pad1d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out) { + return at::_ops::reflection_pad1d_out::call(self, c10::fromIntArrayRefSlow(padding), out); + } +} + +// aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & reflection_pad1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::reflection_pad1d_out::call(self, padding, out); +} +namespace symint { + template ::value>> + at::Tensor & reflection_pad1d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::reflection_pad1d_out::call(self, padding, out); + } +} + +// aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & reflection_pad1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::reflection_pad1d_out::call(self, padding, out); +} +namespace symint { + template ::value>> + at::Tensor & reflection_pad1d_outf(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { + return at::_ops::reflection_pad1d_out::call(self, padding, out); + } +} + +// aten::reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor +inline at::Tensor reflection_pad1d(const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::reflection_pad1d::call(self, c10::fromIntArrayRefSlow(padding)); +} +namespace symint { + template ::value>> + at::Tensor reflection_pad1d(const at::Tensor & self, at::IntArrayRef padding) { + return at::_ops::reflection_pad1d::call(self, c10::fromIntArrayRefSlow(padding)); + } +} + +// aten::reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor +inline at::Tensor reflection_pad1d_symint(const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::reflection_pad1d::call(self, padding); +} +namespace symint { + template ::value>> + at::Tensor reflection_pad1d(const at::Tensor & self, c10::SymIntArrayRef padding) { + return at::_ops::reflection_pad1d::call(self, padding); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/searchsorted_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/searchsorted_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..60577dfea4d273c0d89161d15d2a154b9892936a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/searchsorted_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor searchsorted(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}); +TORCH_API at::Tensor & searchsorted_out(at::Tensor & out, const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}); +TORCH_API at::Tensor & searchsorted_outf(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter, at::Tensor & out); +TORCH_API at::Tensor searchsorted(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}); +TORCH_API at::Tensor & searchsorted_out(at::Tensor & out, const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32=false, bool right=false, ::std::optional side=::std::nullopt, const ::std::optional & sorter={}); +TORCH_API at::Tensor & searchsorted_outf(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sinc_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sinc_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4add03076f24177f3151d7d7b1b59f7d1dbbe9c1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sinc_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor sinc(const at::Tensor & self); +TORCH_API at::Tensor & sinc_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sinc_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sinc_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slice_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slice_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80ccc2fa5c388d12d9bd0454c617dfe981e69eb4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slice_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API slice_backward { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, int64_t, c10::SymInt, c10::SymInt, c10::SymInt); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slice_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slice_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt start, SymInt end, SymInt step) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step); +}; + +struct TORCH_API slice_backward_out { + using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, int64_t, c10::SymInt, c10::SymInt, c10::SymInt, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::slice_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "slice_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt start, SymInt end, SymInt step, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t dim, c10::SymInt start, c10::SymInt end, c10::SymInt step, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..6a274db6916adc22092f4aa037130278cba9779e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_laguerre_polynomial_l_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_special_laguerre_polynomial_l : public TensorIteratorBase { + + + void meta(const at::Tensor & x, const at::Tensor & n); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_zeta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_zeta.h new file mode 100644 index 0000000000000000000000000000000000000000..b34f5351554f185cee4b36b419ecb4f95536a8bf --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_zeta.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_zeta(Tensor self, Tensor other) -> Tensor +inline at::Tensor special_zeta(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_zeta::call(self, other); +} + +// aten::special_zeta.self_scalar(Scalar self, Tensor other) -> Tensor +inline at::Tensor special_zeta(const at::Scalar & self, const at::Tensor & other) { + return at::_ops::special_zeta_self_scalar::call(self, other); +} + +// aten::special_zeta.other_scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor special_zeta(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::special_zeta_other_scalar::call(self, other); +} + +// aten::special_zeta.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::special_zeta_out::call(self, other, out); +} +// aten::special_zeta.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_zeta_out::call(self, other, out); +} + +// aten::special_zeta.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::special_zeta_self_scalar_out::call(self, other, out); +} +// aten::special_zeta.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::special_zeta_self_scalar_out::call(self, other, out); +} + +// aten::special_zeta.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::special_zeta_other_scalar_out::call(self, other, out); +} +// aten::special_zeta.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_zeta_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::special_zeta_other_scalar_out::call(self, other, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/square_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/square_native.h new file mode 100644 index 0000000000000000000000000000000000000000..95d6c1f7ad700a1f6939f6060d7e0e91d5ec6ed1 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/square_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor square(const at::Tensor & self); +TORCH_API at::Tensor & square_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & square_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sspaddmm.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sspaddmm.h new file mode 100644 index 0000000000000000000000000000000000000000..d0d42132b318da628cea85c23320a45f13b66ae8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sspaddmm.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::sspaddmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor +inline at::Tensor sspaddmm(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::sspaddmm::call(self, mat1, mat2, beta, alpha); +} + +// aten::sspaddmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sspaddmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::sspaddmm_out::call(self, mat1, mat2, beta, alpha, out); +} +// aten::sspaddmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sspaddmm_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { + return at::_ops::sspaddmm_out::call(self, mat1, mat2, beta, alpha, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/stride_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/stride_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b4f39154a6b864c53b967283a8006c08e4fd0b7c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/stride_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API int64_t stride(const at::Tensor & self, int64_t dim); +TORCH_API int64_t stride(const at::Tensor & self, at::Dimname dim); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_stride.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_stride.h new file mode 100644 index 0000000000000000000000000000000000000000..13c9edd8304a654a1ad78d50ef166a44628f6755 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_stride.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::sym_stride.int(Tensor self, int dim) -> SymInt +inline c10::SymInt __dispatch_sym_stride(const at::Tensor & self, int64_t dim) { + return at::_ops::sym_stride_int::call(self, dim); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold.h new file mode 100644 index 0000000000000000000000000000000000000000..e1a8e367c7d9ea1e9e76e822c731dc584bda3d5a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/threshold.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::threshold(Tensor self, Scalar threshold, Scalar value) -> Tensor +inline at::Tensor threshold(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value) { + return at::_ops::threshold::call(self, threshold, value); +} + +// aten::threshold_(Tensor(a!) self, Scalar threshold, Scalar value) -> Tensor(a!) +inline at::Tensor & threshold_(at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value) { + return at::_ops::threshold_::call(self, threshold, value); +} + +// aten::threshold.out(Tensor self, Scalar threshold, Scalar value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & threshold_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value) { + return at::_ops::threshold_out::call(self, threshold, value, out); +} +// aten::threshold.out(Tensor self, Scalar threshold, Scalar value, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & threshold_outf(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, at::Tensor & out) { + return at::_ops::threshold_out::call(self, threshold, value, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trace_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trace_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fb8066ac50c9c6ee8d2282caf1c8502259e1a29a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trace_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 trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes); +} // namespace native +} // namespace at