diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2e1380282531122ab0d813d32e5dd5bd8ec1fc01 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool3d_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _adaptive_avg_pool3d(const at::Tensor & self, at::IntArrayRef output_size); +TORCH_API at::Tensor _adaptive_avg_pool3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_choose_qparams_per_tensor_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_choose_qparams_per_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d5c44c4287c5ef2ec95b7e14c01799154e3b88a6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_choose_qparams_per_tensor_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 _choose_qparams_per_tensor(const at::Tensor & self, bool reduce_range=false); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convolution_double_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convolution_double_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f750449c0bd42e15bba134c07fd4cfc6af54cf62 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convolution_double_backward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _convolution_double_backward { + using schema = ::std::tuple (const ::std::optional &, const ::std::optional &, const ::std::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, c10::SymIntArrayRef, c10::SymInt, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_convolution_double_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor)") + static ::std::tuple call(const ::std::optional & ggI, const ::std::optional & ggW, const ::std::optional & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const ::std::optional & ggI, const ::std::optional & ggW, const ::std::optional & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search.h new file mode 100644 index 0000000000000000000000000000000000000000..311898b6a5f0601ebe6d0d688dda96724f138b34 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cslt_sparse_mm_search.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cslt_sparse_mm_search(Tensor compressed_A, Tensor dense_B, Tensor? bias=None, Tensor? alpha=None, ScalarType? out_dtype=None, bool transpose_result=False) -> int +inline int64_t _cslt_sparse_mm_search(const at::Tensor & compressed_A, const at::Tensor & dense_B, const ::std::optional & bias={}, const ::std::optional & alpha={}, ::std::optional out_dtype=::std::nullopt, bool transpose_result=false) { + return at::_ops::_cslt_sparse_mm_search::call(compressed_A, dense_B, bias, alpha, out_dtype, transpose_result); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2c3d3dd64fe291131c987a9586a2520ab0f1afea --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cufft_get_plan_cache_max_size_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API int64_t _cufft_get_plan_cache_max_size(at::DeviceIndex device_index); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..658a304f63cdbbd5925c5c13d0078ec4c74e4889 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_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 _fake_quantize_learnable_per_channel_affine { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, int64_t, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_fake_quantize_learnable_per_channel_affine") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_fake_quantize_learnable_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0) -> Tensor") + static at::Tensor call(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); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, 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); +}; + +struct TORCH_API _fake_quantize_learnable_per_channel_affine_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, int64_t, double, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_fake_quantize_learnable_per_channel_affine") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_fake_quantize_learnable_per_channel_affine.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(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, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, 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, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_flash_attention_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_flash_attention_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..9a3a2e6066f32f5eb37fcabaf17d626a5b6707fb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_flash_attention_backward.h @@ -0,0 +1,47 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, Tensor philox_seed, Tensor philox_offset, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _flash_attention_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt) { + return at::_ops::_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset, scale, window_size_left.has_value() ? ::std::make_optional(c10::SymInt(*window_size_left)) : ::std::nullopt, window_size_right.has_value() ? ::std::make_optional(c10::SymInt(*window_size_right)) : ::std::nullopt); +} +namespace symint { + template ::value>> + ::std::tuple _flash_attention_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt) { + return at::_ops::_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset, scale, window_size_left.has_value() ? ::std::make_optional(c10::SymInt(*window_size_left)) : ::std::nullopt, window_size_right.has_value() ? ::std::make_optional(c10::SymInt(*window_size_right)) : ::std::nullopt); + } +} + +// aten::_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, Tensor philox_seed, Tensor philox_offset, *, float? scale=None, SymInt? window_size_left=None, SymInt? window_size_right=None) -> (Tensor, Tensor, Tensor) +inline ::std::tuple _flash_attention_backward_symint(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt) { + return at::_ops::_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset, scale, window_size_left, window_size_right); +} +namespace symint { + template ::value>> + ::std::tuple _flash_attention_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional scale=::std::nullopt, ::std::optional window_size_left=::std::nullopt, ::std::optional window_size_right=::std::nullopt) { + return at::_ops::_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset, scale, window_size_left, window_size_right); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sigmoid_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sigmoid_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b68e7a8e08e3a904427aabc12c4a3ca08c57025c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sigmoid_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_sigmoid(at::TensorList self); +TORCH_API void _foreach_sigmoid_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_tanh.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_tanh.h new file mode 100644 index 0000000000000000000000000000000000000000..e3a0cedeba5d29e499972a11c6b22dbfe70d6bbc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_tanh.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_tanh(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_tanh(at::TensorList self) { + return at::_ops::_foreach_tanh::call(self); +} + +// aten::_foreach_tanh_(Tensor(a!)[] self) -> () +inline void _foreach_tanh_(at::TensorList self) { + return at::_ops::_foreach_tanh_::call(self); +} + +// aten::_foreach_tanh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tanh_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_tanh_out::call(self, out); +} +// aten::_foreach_tanh.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_tanh_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_tanh_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_zero_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_zero_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..242aa56705a2fd2da0051f9a5d2c06e2f2c0f425 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_zero_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 void _foreach_zero_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_sdp_choice_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..99f23759cdf0624396805c487e2d4e1ec56788ee --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_sdp_choice_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 int64_t _fused_sdp_choice(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const ::std::optional & attn_mask={}, double dropout_p=0.0, bool is_causal=false, ::std::optional scale=::std::nullopt, bool enable_gqa=false); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_native.h new file mode 100644 index 0000000000000000000000000000000000000000..8289bec1e05b8e3ca1151768c16715e7cf1f55bc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_log_softmax_backward_data_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_log_softmax_backward_cpu_out : public at::meta::structured__log_softmax_backward_data { +void impl(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, const at::Tensor & out); +}; +struct TORCH_API structured_log_softmax_backward_cuda_out : public at::meta::structured__log_softmax_backward_data { +void impl(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..c37474b69c19d3a4c1c5fc90edaa163bfbaa9bfb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_left_aligned_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _nested_tensor_from_mask_left_aligned { + using schema = bool (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::_nested_tensor_from_mask_left_aligned") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_nested_tensor_from_mask_left_aligned(Tensor t, Tensor mask) -> bool") + static bool call(const at::Tensor & t, const at::Tensor & mask); + static bool redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & t, const at::Tensor & mask); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_native.h new file mode 100644 index 0000000000000000000000000000000000000000..886edb0166a9b6b6c79ed27da1069be53ff416ad --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_tensor_from_mask_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _nested_tensor_from_mask_out(const at::Tensor & t, const at::Tensor & mask, bool mask_check, at::Tensor & out); +TORCH_API at::Tensor NestedTensor_nested_tensor_from_mask(const at::Tensor & t, const at::Tensor & mask, bool mask_check=true); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_view_from_jagged_copy.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_view_from_jagged_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..b2697c5213bdc933dd41258f47d28aef973acd55 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_nested_view_from_jagged_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_nested_view_from_jagged_copy(Tensor self, Tensor offsets, Tensor dummy, Tensor? lengths=None, int ragged_idx=1, Tensor? min_seqlen=None, Tensor? max_seqlen=None) -> Tensor +inline at::Tensor _nested_view_from_jagged_copy(const at::Tensor & self, const at::Tensor & offsets, const at::Tensor & dummy, const ::std::optional & lengths={}, int64_t ragged_idx=1, const ::std::optional & min_seqlen={}, const ::std::optional & max_seqlen={}) { + return at::_ops::_nested_view_from_jagged_copy::call(self, offsets, dummy, lengths, ragged_idx, min_seqlen, max_seqlen); +} + +// aten::_nested_view_from_jagged_copy.out(Tensor self, Tensor offsets, Tensor dummy, Tensor? lengths=None, int ragged_idx=1, Tensor? min_seqlen=None, Tensor? max_seqlen=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_view_from_jagged_copy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & offsets, const at::Tensor & dummy, const ::std::optional & lengths={}, int64_t ragged_idx=1, const ::std::optional & min_seqlen={}, const ::std::optional & max_seqlen={}) { + return at::_ops::_nested_view_from_jagged_copy_out::call(self, offsets, dummy, lengths, ragged_idx, min_seqlen, max_seqlen, out); +} +// aten::_nested_view_from_jagged_copy.out(Tensor self, Tensor offsets, Tensor dummy, Tensor? lengths=None, int ragged_idx=1, Tensor? min_seqlen=None, Tensor? max_seqlen=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _nested_view_from_jagged_copy_outf(const at::Tensor & self, const at::Tensor & offsets, const at::Tensor & dummy, const ::std::optional & lengths, int64_t ragged_idx, const ::std::optional & min_seqlen, const ::std::optional & max_seqlen, at::Tensor & out) { + return at::_ops::_nested_view_from_jagged_copy_out::call(self, offsets, dummy, lengths, ragged_idx, min_seqlen, max_seqlen, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_safe_softmax_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_safe_softmax_native.h new file mode 100644 index 0000000000000000000000000000000000000000..47de636aa39e01096251d7d30b535a255b62dabc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_safe_softmax_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 _safe_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sobol_engine_draw_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sobol_engine_draw_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3b1d51c88ce564156b690bc5131cca98ec083d53 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sobol_engine_draw_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 ::std::tuple _sobol_engine_draw(const at::Tensor & quasi, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated, ::std::optional dtype); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f1aad6347a39ba43ce172957454d24f57ca9495f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _sparse_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor _sparse_softmax(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unsafe_masked_index.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unsafe_masked_index.h new file mode 100644 index 0000000000000000000000000000000000000000..855d2e085fca22de704d73f238225fbdb4eac805 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unsafe_masked_index.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::_unsafe_masked_index(Tensor self, Tensor mask, Tensor?[] indices, Scalar fill) -> Tensor +inline at::Tensor _unsafe_masked_index(const at::Tensor & self, const at::Tensor & mask, const c10::List<::std::optional> & indices, const at::Scalar & fill) { + return at::_ops::_unsafe_masked_index::call(self, mask, indices, fill); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..486bb5435f1160c7e2cd75d7f5c1feedf314ac6b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor _upsample_nearest_exact2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors); +TORCH_API at::Tensor _upsample_nearest_exact2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional> scale_factors); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a20631e1888ce0e6c409f24451cbbc2e3eb76b9b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact2d_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _upsample_nearest_exact2d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact2d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & _upsample_nearest_exact2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight.h new file mode 100644 index 0000000000000000000000000000000000000000..a51b2bfa2c4003b2629f6b4fe73ebcd3205e7068 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_use_cudnn_rnn_flatten_weight() -> bool +inline bool _use_cudnn_rnn_flatten_weight() { + return at::_ops::_use_cudnn_rnn_flatten_weight::call(); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_native.h new file mode 100644 index 0000000000000000000000000000000000000000..417426f595f74a4ca28d0bf553f8cdc10501b8b9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_use_cudnn_rnn_flatten_weight_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API bool _use_cudnn_rnn_flatten_weight(); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..28271e862247c03094fe1df2a898864502e3c246 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_validate_sparse_csc_tensor_args_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API void _validate_sparse_csc_tensor_args(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool2d.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool2d.h new file mode 100644 index 0000000000000000000000000000000000000000..6bb8e6e21454535c2f5febef758a59cf7a19ceb7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool2d.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::adaptive_max_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple adaptive_max_pool2d_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_max_pool2d_out::call(self, output_size, out, indices); +} +// aten::adaptive_max_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple adaptive_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices) { + return at::_ops::adaptive_max_pool2d_out::call(self, output_size, out, indices); +} + +// aten::adaptive_max_pool2d(Tensor self, int[2] output_size) -> (Tensor, Tensor) +inline ::std::tuple adaptive_max_pool2d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_max_pool2d::call(self, output_size); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/and.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/and.h new file mode 100644 index 0000000000000000000000000000000000000000..587ecb8b07038883a108d64bd5a503d66d9654ac --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/and.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::__and__.Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor __and__(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::__and___Scalar::call(self, other); +} + +// aten::__and__.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor __and__(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::__and___Tensor::call(self, other); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/any_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/any_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d1c89b9aa8374aeb2c8d6ddaba291c8493ab26ec --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/any_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor any(const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, bool keepdim=false); +TORCH_API at::Tensor & any_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_not_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_not_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..97f3942329d44568fc5a3b9ed43ed61fbeb7573e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_not_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_not(const at::Tensor & self); +TORCH_API at::Tensor & bitwise_not_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & bitwise_not_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & bitwise_not_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ceil_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ceil_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6aa7c3b7db566cd77b44bfa15d56fcbb83cdfbee --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/ceil_native.h @@ -0,0 +1,29 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_ceil_out : public at::meta::structured_ceil { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +TORCH_API at::Tensor ceil_sparse(const at::Tensor & self); +TORCH_API at::Tensor & ceil_sparse_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & ceil_sparse_(at::Tensor & self); +TORCH_API at::Tensor ceil_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & ceil_sparse_csr_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & ceil_sparse_csr_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cholesky_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cholesky_native.h new file mode 100644 index 0000000000000000000000000000000000000000..3009a7cc4bb9fd37197c44c3c28e98f95cfc80dc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cholesky_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 cholesky(const at::Tensor & self, bool upper=false); +TORCH_API at::Tensor & cholesky_out(const at::Tensor & self, bool upper, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/clamp_max_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/clamp_max_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..9222a0677b2f10ad9545dbc1eb85272f8a522757 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/clamp_max_meta.h @@ -0,0 +1,32 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_clamp_max : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Scalar & max); +}; +struct TORCH_API structured_clamp_max_Tensor : public TensorIteratorBase { + + + void meta(const at::Tensor & self, const at::Tensor & max); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/combinations_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/combinations_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6f57c07e72733fcbdaacb98be9ffdf164b9f9276 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/combinations_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor combinations(const at::Tensor & self, int64_t r=2, bool with_replacement=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conj_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conj_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e82fa6f8a1e55202fd6e364a439ac50a580e5f44 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conj_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 conj { + 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::conj") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "conj(Tensor(a) self) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conv3d_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conv3d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..64b7291acfa1d49b9dc8f02c046ce6cff84728d9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conv3d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1); +TORCH_API at::Tensor conv3d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1); +TORCH_API at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation=1, int64_t groups=1); +TORCH_API at::Tensor conv3d_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/copy_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/copy_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6d7715af79952163406a5cd244df28fe0a883de6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/copy_meta_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor copy(const at::Tensor & self, const at::Tensor & src, bool non_blocking=false); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cudnn_convolution.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cudnn_convolution.h new file mode 100644 index 0000000000000000000000000000000000000000..ae6ca4f90efb5a311f50dd518b59829878407ed4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/cudnn_convolution.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::cudnn_convolution(Tensor self, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor +inline at::Tensor cudnn_convolution(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32); +} +namespace symint { + template ::value>> + at::Tensor cudnn_convolution(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32); + } +} + +// aten::cudnn_convolution(Tensor self, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor +inline at::Tensor cudnn_convolution_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution::call(self, weight, padding, stride, dilation, groups, benchmark, deterministic, allow_tf32); +} +namespace symint { + template ::value>> + at::Tensor cudnn_convolution(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution::call(self, weight, padding, stride, dilation, groups, benchmark, deterministic, allow_tf32); + } +} + +// aten::cudnn_convolution.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32, out); +} +namespace symint { + template ::value>> + at::Tensor & cudnn_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32, out); + } +} + +// aten::cudnn_convolution.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { + return at::_ops::cudnn_convolution_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32, out); +} +namespace symint { + template ::value>> + at::Tensor & cudnn_convolution_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { + return at::_ops::cudnn_convolution_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, benchmark, deterministic, allow_tf32, out); + } +} + +// aten::cudnn_convolution.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_out::call(self, weight, padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); +} +namespace symint { + template ::value>> + at::Tensor & cudnn_convolution_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32) { + return at::_ops::cudnn_convolution_out::call(self, weight, padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); + } +} + +// aten::cudnn_convolution.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] stride, SymInt[] dilation, SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cudnn_convolution_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { + return at::_ops::cudnn_convolution_out::call(self, weight, padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); +} +namespace symint { + template ::value>> + at::Tensor & cudnn_convolution_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { + return at::_ops::cudnn_convolution_out::call(self, weight, padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/embedding_bag_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/embedding_bag_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2ea5b25febb839c271efbf93be21431be2c53051 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/embedding_bag_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const ::std::optional & per_sample_weights={}, bool include_last_offset=false); +TORCH_API ::std::tuple embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional & per_sample_weights, bool include_last_offset, ::std::optional padding_idx); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/equal_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/equal_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9e7c2b1123c911dc6fd0dc2a2ca7cbfd3ac884fb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/equal_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API bool equal(const at::Tensor & self, const at::Tensor & other); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/erfc_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/erfc_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4c354c0ff55279981692258d623216cdd47653d7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/erfc_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_erfc_out : public at::meta::structured_erfc { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/exponential_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/exponential_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..603d07f70ae0a0f996c35959d245fd6d360346e8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/exponential_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & exponential_(at::Tensor & self, double lambd=1, ::std::optional generator=::std::nullopt); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_irfftn_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_irfftn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..13a43872c762c04bdbb33792f030db558cf07011 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_irfftn_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fft_irfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_irfftn_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f929359e59d88df1c8aea0c520645cab7cea50d5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fractional_max_pool2d_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 fractional_max_pool2d_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, 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::fractional_max_pool2d_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "grad_input") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input); +}; + +struct TORCH_API fractional_max_pool2d_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, 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::fractional_max_pool2d_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fractional_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/geqrf_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/geqrf_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..80fb5deda707de5d7377460bf0ba574bfd4081e2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/geqrf_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API geqrf_a { + using schema = ::std::tuple (const at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::geqrf") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "a") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau)") + static ::std::tuple call(const at::Tensor & self, at::Tensor & a, at::Tensor & tau); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & a, at::Tensor & tau); +}; + +struct TORCH_API geqrf { + using schema = ::std::tuple (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::geqrf") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "geqrf(Tensor self) -> (Tensor a, Tensor tau)") + static ::std::tuple call(const at::Tensor & self); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ff0bee174df9953475548362155a2aa9c37049e8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/grid_sampler_2d_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 grid_sampler_2d_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::grid_sampler_2d_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask); +}; + +struct TORCH_API grid_sampler_2d_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, ::std::array, 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::grid_sampler_2d_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/histogram_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/histogram_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a0f90ac5c6d585da6d5ac008dbd5575ea11ad8c8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/histogram_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 histogram(const at::Tensor & self, const at::Tensor & bins, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_out(at::Tensor & hist, at::Tensor & bin_edges, const at::Tensor & self, const at::Tensor & bins, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_outf(const at::Tensor & self, const at::Tensor & bins, const ::std::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); +TORCH_API ::std::tuple histogram(const at::Tensor & self, int64_t bins=100, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_out(at::Tensor & hist, at::Tensor & bin_edges, const at::Tensor & self, int64_t bins=100, ::std::optional> range=::std::nullopt, const ::std::optional & weight={}, bool density=false); +TORCH_API ::std::tuple histogram_outf(const at::Tensor & self, int64_t bins, ::std::optional> range, const ::std::optional & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hypot_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hypot_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f27289ec82f4195ebf69d70e25ec00049604d21d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hypot_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_hypot_out : public at::meta::structured_hypot { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_put_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_put_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..deb926b732562a2743b39fc3c9a404f91b074159 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_put_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 index_put_ { + using schema = at::Tensor & (at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::index_put_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "index_put_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate); +}; + +struct TORCH_API index_put { + using schema = at::Tensor (const at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::index_put") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "index_put(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate); +}; + +struct TORCH_API index_put_out { + using schema = at::Tensor & (const at::Tensor &, const c10::List<::std::optional> &, const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::index_put") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "index_put.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<::std::optional> & indices, const at::Tensor & values, bool accumulate, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_select_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_select_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7add774680483876342f5803f760aa1c9851c794 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/index_select_ops.h @@ -0,0 +1,61 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API index_select_out { + using schema = at::Tensor & (const at::Tensor &, int64_t, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::index_select") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "index_select.out(Tensor self, int dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t dim, const at::Tensor & index, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, at::Tensor & out); +}; + +struct TORCH_API index_select { + using schema = at::Tensor (const at::Tensor &, int64_t, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::index_select") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "index_select(Tensor self, int dim, Tensor index) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index); +}; + +struct TORCH_API index_select_dimname_out { + using schema = at::Tensor & (const at::Tensor &, at::Dimname, 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::index_select") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dimname_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "index_select.dimname_out(Tensor self, Dimname dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, at::Tensor & out); +}; + +struct TORCH_API index_select_dimname { + using schema = at::Tensor (const at::Tensor &, at::Dimname, 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::index_select") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dimname") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "index_select.dimname(Tensor self, Dimname dim, Tensor index) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_inv_ex_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_inv_ex_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ca902f8f5b869ea54fc1e7a13324af3b4d779f7a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_inv_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_inv_ex(const at::Tensor & A, bool check_errors=false); +TORCH_API ::std::tuple linalg_inv_ex_out(at::Tensor & inverse, at::Tensor & info, const at::Tensor & A, bool check_errors=false); +TORCH_API ::std::tuple linalg_inv_ex_outf(const at::Tensor & A, bool check_errors, at::Tensor & inverse, at::Tensor & info); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log10_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log10_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2a5a4ed2cd42bb566686587854c7db097215ff0e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log10_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 log10 { + 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::log10") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "log10(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API log10_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::log10_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "log10_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API log10_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::log10") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "log10.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logical_and_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logical_and_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a899a2f167d74ffb533cef846c0ec4e4ef1ba688 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/logical_and_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 logical_and(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_and_(at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & logical_and_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool3d_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool3d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cb106bc85639df0a72a06927a60a95d2d0990068 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/max_pool3d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/maximum.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/maximum.h new file mode 100644 index 0000000000000000000000000000000000000000..c597facaeb1e264687d6d848b154ae8132f162a7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/maximum.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::maximum(Tensor self, Tensor other) -> Tensor +inline at::Tensor maximum(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::maximum::call(self, other); +} + +// aten::maximum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & maximum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::maximum_out::call(self, other, out); +} +// aten::maximum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & maximum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::maximum_out::call(self, other, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nanmean.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nanmean.h new file mode 100644 index 0000000000000000000000000000000000000000..db72c8a09e883bf25e06eb610b150320b8bfba7e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nanmean.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::nanmean(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor nanmean(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::nanmean::call(self, dim, keepdim, dtype); +} + +// aten::nanmean.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanmean_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt, bool keepdim=false, ::std::optional dtype=::std::nullopt) { + return at::_ops::nanmean_out::call(self, dim, keepdim, dtype, out); +} +// aten::nanmean.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & nanmean_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::nanmean_out::call(self, dim, keepdim, dtype, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_batch_norm_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_batch_norm_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..71cdf55b97eb8094ce793d4eb1501c700c185622 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_batch_norm_backward_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple native_batch_norm_backward_out(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +TORCH_API ::std::tuple batch_norm_backward_cpu(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); +TORCH_API ::std::tuple batch_norm_backward_cuda(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); +TORCH_API ::std::tuple mkldnn_batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_invstd, bool train, double eps, ::std::array output_mask); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randn_like_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randn_like_native.h new file mode 100644 index 0000000000000000000000000000000000000000..1d66f5cf89091b274a6ff49bdbe32b720fc91613 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/randn_like_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 randn_like(const at::Tensor & self, ::std::optional dtype={}, ::std::optional layout={}, ::std::optional device={}, ::std::optional pin_memory={}, ::std::optional memory_format=::std::nullopt); +TORCH_API at::Tensor & randn_like_out(const at::Tensor & self, ::std::optional memory_format, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/range_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/range_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..386df50b9d57a359e608ca6536dc2c98fd9ff0ed --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/range_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor & range_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step); +TORCH_API at::Tensor & range_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/scatter_add_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/scatter_add_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a780dc6f767eead2f1c02e1a54219d7e2f150bdf --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/scatter_add_meta_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor scatter_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_add_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_add_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out); +TORCH_API at::Tensor & scatter_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/searchsorted_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/searchsorted_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..953754acf5ee9bd6dd1eabdf49d8ddcaf6f24636 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/searchsorted_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 searchsorted_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool, ::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::searchsorted") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "searchsorted.Tensor(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor") + static at::Tensor call(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter); +}; + +struct TORCH_API searchsorted_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, bool, bool, ::std::optional, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::searchsorted") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "searchsorted.Tensor_out(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter, at::Tensor & out); +}; + +struct TORCH_API searchsorted_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, bool, bool, ::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::searchsorted") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "searchsorted.Scalar(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor") + static at::Tensor call(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter); +}; + +struct TORCH_API searchsorted_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, bool, bool, ::std::optional, const ::std::optional &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::searchsorted") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "searchsorted.Scalar_out(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, ::std::optional side, const ::std::optional & sorter, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, 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 at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sigmoid_backward_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sigmoid_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..53a0b4584cdc3f1db237364867ab4ec98e60f980 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sigmoid_backward_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor sigmoid_backward(const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & sigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output); +TORCH_API at::Tensor & sigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sign_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sign_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3d605ef2f75847ff2abde3b46f835b71062df23b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sign_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 sign(const at::Tensor & self); +TORCH_API at::Tensor & sign_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sign_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sign_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sign_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sign_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..b9de77de8b87bb24b9ea621a42b55a1b2c7fd9fa --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sign_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_sign : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slow_conv3d_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slow_conv3d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6bd7dcb56576b37affefe43bc0d0ada04c5f3109 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/slow_conv3d_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 slow_conv3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0); +TORCH_API at::Tensor & slow_conv3d_out(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sort_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sort_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6ac7fdb526fffeafaf69c2fb19c48b422bafac4c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sort_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 sort(const at::Tensor & self, ::std::optional stable, int64_t dim=-1, bool descending=false); +TORCH_API ::std::tuple sort_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, ::std::optional stable, int64_t dim=-1, bool descending=false); +TORCH_API ::std::tuple sort_outf(const at::Tensor & self, ::std::optional stable, int64_t dim, bool descending, at::Tensor & values, at::Tensor & indices); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_csc_tensor.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_csc_tensor.h new file mode 100644 index 0000000000000000000000000000000000000000..1f0fd883ecf1203a4c396c2e5a83a6d7ac6fe138 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_csc_tensor.h @@ -0,0 +1,43 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::sparse_csc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options) { + return at::_ops::sparse_csc_tensor_ccol_row_value_size::call(ccol_indices, row_indices, values, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::sparse_csc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::sparse_csc_tensor_ccol_row_value_size::call(ccol_indices, row_indices, values, size, dtype, layout, device, pin_memory); +} + +// aten::sparse_csc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::TensorOptions options) { + return at::_ops::sparse_csc_tensor_ccol_row_value::call(ccol_indices, row_indices, values, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::sparse_csc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor +inline at::Tensor sparse_csc_tensor(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory) { + return at::_ops::sparse_csc_tensor_ccol_row_value::call(ccol_indices, row_indices, values, dtype, layout, device, pin_memory); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_bessel_y1_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_bessel_y1_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5d3dfa23d14597b21155b15f3f962addd085d9df --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_bessel_y1_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor special_bessel_y1(const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0af5f7cc42dd8905566a2f5154093b6fcc898dd4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor special_modified_bessel_i0(const at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sub_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sub_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1cf0632494db529e8da505da5b4491c05f83e253 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sub_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sub_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +}; + +struct TORCH_API sub_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub__Tensor { + using schema = at::Tensor & (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::sub_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub__Scalar { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &, 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::sub_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha); +}; + +struct TORCH_API sub_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sub") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sum_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sum_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9af8e2db94e8df30fe643848fc7c3d7cdebc5b07 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sum_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor sum(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & sum_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, ::std::optional dtype=::std::nullopt); +TORCH_API at::Tensor & sum_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, ::std::optional dtype, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_stride_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_stride_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..852beb2ea721d6cf85119b176e0451b0d712d27f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sym_stride_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sym_stride_int { + using schema = c10::SymInt (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sym_stride") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "int") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sym_stride.int(Tensor self, int dim) -> SymInt") + static c10::SymInt call(const at::Tensor & self, int64_t dim); + static c10::SymInt redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/to.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/to.h new file mode 100644 index 0000000000000000000000000000000000000000..2d02b52f1992faa1be9845a68ca1439d509c77b4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/to.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/trace_backward_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trace_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5e95242aa2af6716eb71736e1bc4211e34276502 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trace_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor trace_backward(const at::Tensor & grad, at::IntArrayRef sizes); +TORCH_API at::Tensor trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trapezoid.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trapezoid.h new file mode 100644 index 0000000000000000000000000000000000000000..d397589ded6dd2d59c60aba62335d0a849e63a58 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/trapezoid.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::trapezoid.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor +inline at::Tensor trapezoid(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1) { + return at::_ops::trapezoid_x::call(y, x, dim); +} + +// aten::trapezoid.dx(Tensor y, *, Scalar dx=1, int dim=-1) -> Tensor +inline at::Tensor trapezoid(const at::Tensor & y, const at::Scalar & dx=1, int64_t dim=-1) { + return at::_ops::trapezoid_dx::call(y, dx, dim); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5c7631d959379b79e62aab544b2303a8fab5fdb5 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor upsample_bicubic2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bicubic2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bicubic2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h=::std::nullopt, ::std::optional scales_w=::std::nullopt); +TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional scales_h, ::std::optional scales_w, at::Tensor & grad_input); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/where_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/where_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2fc12a4f533c1e12792cb24d441294e4f942f084 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/where_native.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor where(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & where_self_out(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor NestedTensor_where(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor where(const at::Tensor & condition, const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor where(const at::Tensor & condition, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor where(const at::Tensor & condition, const at::Scalar & self, const at::Scalar & other); +TORCH_API ::std::vector where(const at::Tensor & condition); +} // namespace native +} // namespace at