diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Half_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Half_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6c3997286c4a13c6581a44716ca189eed858c975 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Half_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 _cast_Half(const at::Tensor & self, bool non_blocking=false); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_compute_linear_combination_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_compute_linear_combination_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cbdbbb92d888e58d4aca42dcfb2fe480428b7847 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_compute_linear_combination_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 _compute_linear_combination(const at::Tensor & input, const at::Tensor & coefficients); +TORCH_API at::Tensor & _compute_linear_combination_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & coefficients); +TORCH_API at::Tensor & _compute_linear_combination_outf(const at::Tensor & input, const at::Tensor & coefficients, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h new file mode 100644 index 0000000000000000000000000000000000000000..72401ff1ef78002e8d4c6e8957eeecb3568298fd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_empty_affine_quantized.h @@ -0,0 +1,113 @@ +#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::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template ::value>> + at::Tensor _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory, scale, zero_point, memory_format); +} +namespace symint { + template ::value>> + at::Tensor _empty_affine_quantized(at::IntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory, scale, zero_point, memory_format); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized_symint(c10::SymIntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); +} +namespace symint { + template ::value>> + at::Tensor _empty_affine_quantized(c10::SymIntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), scale, zero_point, c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format)); + } +} + +// aten::_empty_affine_quantized(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format) -> Tensor +inline at::Tensor _empty_affine_quantized_symint(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(size, dtype, layout, device, pin_memory, scale, zero_point, memory_format); +} +namespace symint { + template ::value>> + at::Tensor _empty_affine_quantized(c10::SymIntArrayRef size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, double scale, int64_t zero_point, ::std::optional memory_format) { + return at::_ops::_empty_affine_quantized::call(size, dtype, layout, device, pin_memory, scale, zero_point, memory_format); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & _empty_affine_quantized_out(at::Tensor & out, at::IntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_outf(at::IntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & _empty_affine_quantized_outf(at::IntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(c10::fromIntArrayRefSlow(size), scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_symint_out(at::Tensor & out, c10::SymIntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & _empty_affine_quantized_out(at::Tensor & out, c10::SymIntArrayRef size, double scale=1, int64_t zero_point=0, ::std::optional memory_format=c10::MemoryFormat::Contiguous) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); + } +} + +// aten::_empty_affine_quantized.out(SymInt[] size, *, float scale=1, int zero_point=0, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _empty_affine_quantized_symint_outf(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); +} +namespace symint { + template ::value>> + at::Tensor & _empty_affine_quantized_outf(c10::SymIntArrayRef size, double scale, int64_t zero_point, ::std::optional memory_format, at::Tensor & out) { + return at::_ops::_empty_affine_quantized_out::call(size, scale, zero_point, memory_format, out); + } +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_ceil_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_ceil_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bfd3e0005d275acc723524d8c73dcc96ffabd6f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_ceil_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_ceil(at::TensorList self); +TORCH_API void _foreach_ceil_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_ceil_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_ceil_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7882582cb50b0c02f5360033df1e81b11fd63e4d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_ceil_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_ceil_slow(at::TensorList self); +TORCH_API void _foreach_ceil_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_ceil_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_ceil_cuda(at::TensorList self); +TORCH_API void foreach_tensor_ceil_cuda_(at::TensorList self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_exp_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_exp_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6ada08c0324ad57f25b8ab5bb48bce1e94334acd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_exp_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_exp(at::TensorList self); +TORCH_API void _foreach_exp_out(at::TensorList out, at::TensorList self); +TORCH_API void _foreach_exp_outf(at::TensorList self, at::TensorList out); +TORCH_API void _foreach_exp_(at::TensorList self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_neg_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_neg_native.h new file mode 100644 index 0000000000000000000000000000000000000000..2be7b2c5e80005bacb776dfeb538807fc0de818d --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_neg_native.h @@ -0,0 +1,25 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::vector foreach_tensor_neg_slow(at::TensorList self); +TORCH_API void _foreach_neg_out(at::TensorList self, at::TensorList out); +TORCH_API void foreach_tensor_neg_slow_(at::TensorList self); +TORCH_API ::std::vector foreach_tensor_neg_cuda(at::TensorList self); +TORCH_API void foreach_tensor_neg_cuda_(at::TensorList self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_norm_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_norm_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f0c7911584c2ca594fe0227be726a49c0ad45be9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_norm_compositeexplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::vector _foreach_norm(at::TensorList self, const at::Scalar & ord=2, ::std::optional dtype=::std::nullopt); +TORCH_API void _foreach_norm_out(at::TensorList out, at::TensorList self, const at::Scalar & ord=2, ::std::optional dtype=::std::nullopt); +TORCH_API void _foreach_norm_outf(at::TensorList self, const at::Scalar & ord, ::std::optional dtype, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sigmoid_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sigmoid_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..48b70d4178d7dced50beb195e77473a872e03e46 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sigmoid_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_sigmoid { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_sigmoid") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sigmoid(Tensor[] self) -> Tensor[]") + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sigmoid_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_sigmoid_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sigmoid_(Tensor(a!)[] self) -> ()") + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sigmoid_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_sigmoid") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sigmoid.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sinh_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sinh_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..00360daac7ed49fbf5745313dcfea321c0fd3a87 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_sinh_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_sinh(at::TensorList self); +TORCH_API void _foreach_sinh_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_dropout.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_dropout.h new file mode 100644 index 0000000000000000000000000000000000000000..f032737f9228b7262e69301fe98fa540d09dfe90 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_dropout.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::_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor) +inline ::std::tuple _fused_dropout(const at::Tensor & self, double p, ::std::optional generator=::std::nullopt) { + return at::_ops::_fused_dropout::call(self, p, generator); +} + +// aten::_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _fused_dropout_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, double p, ::std::optional generator=::std::nullopt) { + return at::_ops::_fused_dropout_out::call(self, p, generator, out0, out1); +} +// aten::_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _fused_dropout_outf(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_fused_dropout_out::call(self, p, generator, out0, out1); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_dropout_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_dropout_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..05a4014030d2a1186a5681545ca4678b32936186 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fused_dropout_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _fused_dropout { + using schema = ::std::tuple (const at::Tensor &, double, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_fused_dropout") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & self, double p, ::std::optional generator); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, ::std::optional generator); +}; + +struct TORCH_API _fused_dropout_out { + using schema = ::std::tuple (const at::Tensor &, double, ::std::optional, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_fused_dropout") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") + static ::std::tuple call(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out0, at::Tensor & out1); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out0, at::Tensor & out1); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fw_primal_copy_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fw_primal_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f46e559186543cee851c4547255e18965f87142a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fw_primal_copy_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 & _fw_primal_copy_out(const at::Tensor & self, int64_t level, at::Tensor & out); +TORCH_API at::Tensor _fw_primal_copy(const at::Tensor & self, int64_t level); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_det_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_det_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ad36b303793b9cde7e3a4c67f3746080a4678ba4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_det_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_det(const at::Tensor & A); +TORCH_API ::std::tuple _linalg_det_out(at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, const at::Tensor & A); +TORCH_API ::std::tuple _linalg_det_outf(const at::Tensor & A, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2f520c20339deaff2caf76b6d588aecf678f1d2c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_make_per_channel_quantized_tensor_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 _make_per_channel_quantized_tensor(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_compositeexplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1c981a72d87e66778d19138ae9cda88798e3e71a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_mps_convolution_transpose_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor & _mps_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups); +TORCH_API at::Tensor & _mps_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out); +TORCH_API at::Tensor & _mps_convolution_transpose_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups); +TORCH_API at::Tensor & _mps_convolution_transpose_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_safe_softmax_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_safe_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ce4ec8d7cea61595c81a67bd5a75d521f492a093 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_safe_softmax_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 _safe_softmax { + using schema = at::Tensor (const at::Tensor &, int64_t, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_safe_softmax") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_safe_softmax(Tensor self, int dim, ScalarType? dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim, ::std::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, ::std::optional dtype); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_for_cpu_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_for_cpu_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..1bc8658b8542f0f4ee70e4604603fd2ebd4d74bb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_for_cpu_backward.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_scaled_dot_product_flash_attention_for_cpu_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, float dropout_p, bool is_causal, *, Tensor? attn_mask=None, float? scale=None) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value) +inline ::std::tuple _scaled_dot_product_flash_attention_for_cpu_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, double dropout_p, bool is_causal, const ::std::optional & attn_mask={}, ::std::optional scale=::std::nullopt) { + return at::_ops::_scaled_dot_product_flash_attention_for_cpu_backward::call(grad_out, query, key, value, out, logsumexp, dropout_p, is_causal, attn_mask, scale); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0672af2c7d3653a9824658c6c5d5fb23014f12b3 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch.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::_test_autograd_multiple_dispatch.fullcoverage(Tensor self) -> Tensor +inline at::Tensor _test_autograd_multiple_dispatch(const at::Tensor & self) { + return at::_ops::_test_autograd_multiple_dispatch_fullcoverage::call(self); +} + +// aten::_test_autograd_multiple_dispatch.ntonly(Tensor self, bool b) -> Tensor +inline at::Tensor _test_autograd_multiple_dispatch(const at::Tensor & self, bool b) { + return at::_ops::_test_autograd_multiple_dispatch_ntonly::call(self, b); +} + +// aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_autograd_multiple_dispatch_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::_test_autograd_multiple_dispatch_fullcoverage_out::call(self, out); +} +// aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _test_autograd_multiple_dispatch_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::_test_autograd_multiple_dispatch_fullcoverage_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..aba9833ebcebc86aff330796d313bf92b99ac2d9 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_test_autograd_multiple_dispatch_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 _test_autograd_multiple_dispatch_fullcoverage { + 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::_test_autograd_multiple_dispatch") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "fullcoverage") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_autograd_multiple_dispatch.fullcoverage(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 _test_autograd_multiple_dispatch_ntonly { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_test_autograd_multiple_dispatch") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "ntonly") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_autograd_multiple_dispatch.ntonly(Tensor self, bool b) -> Tensor") + static at::Tensor call(const at::Tensor & self, bool b); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool b); +}; + +struct TORCH_API _test_autograd_multiple_dispatch_fullcoverage_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::_test_autograd_multiple_dispatch") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "fullcoverage_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_test_autograd_multiple_dispatch.fullcoverage_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/_upsample_nearest_exact1d_backward_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b67995ede42ef9fdc4e54e0638b379f7b3ec173f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _upsample_nearest_exact1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional scales, at::Tensor & grad_input); +TORCH_API at::Tensor & _upsample_nearest_exact1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales=::std::nullopt); +TORCH_API at::Tensor & _upsample_nearest_exact1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional scales, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3bf4513ea18d921aee0981445262b57ec421aeab --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_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_exact1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional> scale_factors); +TORCH_API at::Tensor _upsample_nearest_exact1d_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/_validate_sparse_bsc_tensor_args_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_validate_sparse_bsc_tensor_args_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3a97f582d8b31b0df20969f78c05cdb66098c2b2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_validate_sparse_bsc_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_bsc_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/addcdiv_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/addcdiv_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3ad933aa205ae5be495d8df2166ec176fcf56880 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/addcdiv_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 addcdiv(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); +TORCH_API at::Tensor & addcdiv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); +TORCH_API at::Tensor & addcdiv_outf(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & addcdiv_(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/alpha_dropout.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/alpha_dropout.h new file mode 100644 index 0000000000000000000000000000000000000000..55e9e061eea7ba1b943edb0c6b9282438fdcbeb4 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/alpha_dropout.h @@ -0,0 +1,35 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::alpha_dropout(Tensor input, float p, bool train) -> Tensor +inline at::Tensor alpha_dropout(const at::Tensor & input, double p, bool train) { + return at::_ops::alpha_dropout::call(input, p, train); +} + +// aten::alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) +inline at::Tensor & alpha_dropout_(at::Tensor & self, double p, bool train) { + return at::_ops::alpha_dropout_::call(self, p, train); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/arccosh.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/arccosh.h new file mode 100644 index 0000000000000000000000000000000000000000..4b93a251b0ac711f4cdfb4fe013d400029d1d1fb --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/arccosh.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::arccosh(Tensor self) -> Tensor +inline at::Tensor arccosh(const at::Tensor & self) { + return at::_ops::arccosh::call(self); +} + +// aten::arccosh_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & arccosh_(at::Tensor & self) { + return at::_ops::arccosh_::call(self); +} + +// aten::arccosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arccosh_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::arccosh_out::call(self, out); +} +// aten::arccosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & arccosh_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::arccosh_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2429ecf6be19d32a6f7dd85bbfc725389e501b74 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/atan_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 atan(const at::Tensor & self); +TORCH_API at::Tensor & atan_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & atan_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & atan_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bilinear_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bilinear_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..72982391a915acbcefd93a573db180385653538a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bilinear_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 bilinear(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & weight, const ::std::optional & bias={}); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/can_cast_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/can_cast_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a6c34a7e0dc998f75b8fc0ac67e5a13f6b9a67c8 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/can_cast_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API bool can_cast(at::ScalarType from_, at::ScalarType to); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/chunk.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/chunk.h new file mode 100644 index 0000000000000000000000000000000000000000..f6ebb47904da0e0650378cca19ea01689bc3673f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/chunk.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::chunk(Tensor(a -> *) self, int chunks, int dim=0) -> Tensor(a)[] +inline ::std::vector chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0) { + return at::_ops::chunk::call(self, chunks, dim); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/convolution_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/convolution_native.h new file mode 100644 index 0000000000000000000000000000000000000000..846ea5ebebbbbc085c19926338488ef895d8ee02 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/convolution_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 convolution(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups); +TORCH_API at::Tensor & convolution_out_symint(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/erfc_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/erfc_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..66216294b4a2b8ae7c43534fe54d2070853c8565 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/erfc_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor erfc(const at::Tensor & self); +TORCH_API at::Tensor & erfc_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ifftn_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ifftn_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3875596f6b5650bf5837bf033a5a678e4e0339c2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ifftn_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor fft_ifftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor fft_ifftn_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_ifftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_ifftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); +TORCH_API at::Tensor & fft_ifftn_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional norm=::std::nullopt); +TORCH_API at::Tensor & fft_ifftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional norm, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ifftshift.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ifftshift.h new file mode 100644 index 0000000000000000000000000000000000000000..be7c0d8bf1a5f0e0ff480aa97fd4d3d97320cc21 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fft_ifftshift.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::fft_ifftshift(Tensor self, int[1]? dim=None) -> Tensor +inline at::Tensor fft_ifftshift(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt) { + return at::_ops::fft_ifftshift::call(self, dim); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fill_diagonal.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fill_diagonal.h new file mode 100644 index 0000000000000000000000000000000000000000..652218250c9f0896c9a9e64580456ba4fe4ff5dd --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/fill_diagonal.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/gcd_meta_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gcd_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b4da98875bd67285dcbe23e315738679c527937e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gcd_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 gcd(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & gcd_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & gcd_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & gcd_(at::Tensor & self, const at::Tensor & other); + +} // namespace meta +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/huber_loss_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/huber_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a5d021d1717508b6f610b14d75ec8f84f98ef97c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/huber_loss_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 huber_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0); +TORCH_API at::Tensor & huber_loss_out(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/igamma_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/igamma_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..993156e810d1e7fb1576fda00cf1855602473f28 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/igamma_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor igamma(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igamma_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/infinitely_differentiable_gelu_backward_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/infinitely_differentiable_gelu_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..871c17558c0f6df3a8ff83aa71ed7d92ba2d48e2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/infinitely_differentiable_gelu_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor infinitely_differentiable_gelu_backward(const at::Tensor & grad, const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/instance_norm_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/instance_norm_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c31900a681b5ac51d5378d0c895118ccc4683618 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/instance_norm_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 instance_norm(const at::Tensor & input, const ::std::optional & weight, const ::std::optional & bias, const ::std::optional & running_mean, const ::std::optional & running_var, bool use_input_stats, double momentum, double eps, bool cudnn_enabled); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/kaiser_window_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/kaiser_window_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5ed1e3b1af506d4148892e6751fc77b8b422e07e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/kaiser_window_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 kaiser_window { + using schema = at::Tensor (int64_t, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::kaiser_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "kaiser_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API kaiser_window_periodic { + using schema = at::Tensor (int64_t, bool, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::kaiser_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "periodic") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "kaiser_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API kaiser_window_beta { + using schema = at::Tensor (int64_t, bool, double, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::kaiser_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "beta") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "kaiser_window.beta(int window_length, bool periodic, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(int64_t window_length, bool periodic, double beta, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double beta, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API kaiser_window_out { + using schema = at::Tensor & (int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::kaiser_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "kaiser_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(int64_t window_length, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, at::Tensor & out); +}; + +struct TORCH_API kaiser_window_periodic_out { + using schema = at::Tensor & (int64_t, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::kaiser_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "periodic_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "kaiser_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(int64_t window_length, bool periodic, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, at::Tensor & out); +}; + +struct TORCH_API kaiser_window_beta_out { + using schema = at::Tensor & (int64_t, bool, 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::kaiser_window") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "beta_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "kaiser_window.beta_out(int window_length, bool periodic, float beta, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(int64_t window_length, bool periodic, double beta, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double beta, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/leaky_relu_backward_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/leaky_relu_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8bd257b124e91c289c6103716780a26926147928 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/leaky_relu_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor leaky_relu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lgamma_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lgamma_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..14cf4924390f80c65aebb2f8a1d38254c6eac96a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lgamma_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_lgamma : 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/linalg_det.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_det.h new file mode 100644 index 0000000000000000000000000000000000000000..58855136350795d6c4c473cd74975dde70a0d3ea --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_det.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linalg_det(Tensor A) -> Tensor +inline at::Tensor linalg_det(const at::Tensor & A) { + return at::_ops::linalg_det::call(A); +} + +// aten::linalg_det.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_det_out(at::Tensor & out, const at::Tensor & A) { + return at::_ops::linalg_det_out::call(A, out); +} +// aten::linalg_det.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_det_outf(const at::Tensor & A, at::Tensor & out) { + return at::_ops::linalg_det_out::call(A, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigvals_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigvals_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..754d80abf4172a02c003350772771ca01b441a64 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_eigvals_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor & linalg_eigvals_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & linalg_eigvals_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_inv_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_inv_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b6327ea0294cb9d1834af9ac0b19a6f522fab99b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_inv_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_inv { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_inv") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_inv(Tensor A) -> Tensor") + static at::Tensor call(const at::Tensor & A); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A); +}; + +struct TORCH_API linalg_inv_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_inv") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_inv.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & A, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_meta.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..516271a86276590fbfe15c72a66593448eed1e07 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_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_linalg_lu : public at::impl::MetaBase { + + + void meta(const at::Tensor & A, bool pivot); +}; + +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_solve_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_solve_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7527f49e800f4d06551c206df56f2b32deaaa8c7 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_solve_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 linalg_lu_solve(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left=true, bool adjoint=false); +TORCH_API at::Tensor & linalg_lu_solve_out(at::Tensor & out, const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left=true, bool adjoint=false); +TORCH_API at::Tensor & linalg_lu_solve_outf(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left, bool adjoint, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linear_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linear_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..08c2da14ad151a60c1d88aa87c8396ed012a3cf2 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linear_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linear_backward(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple linear_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask) { + return at::_ops::linear_backward::call(self, grad_output, weight, output_mask); +} + +// aten::linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple linear_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask) { + return at::_ops::linear_backward_out::call(self, grad_output, weight, output_mask, out0, out1, out2); +} +// aten::linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple linear_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::linear_backward_out::call(self, grad_output, weight, output_mask, out0, out1, out2); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log_softmax.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log_softmax.h new file mode 100644 index 0000000000000000000000000000000000000000..91845ed3aa3a51e7af4a4e9db51115b7e688af8f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/log_softmax.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::log_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor +inline at::Tensor log_softmax(const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::log_softmax_int::call(self, dim, dtype); +} + +// aten::log_softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & log_softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::log_softmax_int_out::call(self, dim, dtype, out); +} +// aten::log_softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & log_softmax_outf(const at::Tensor & self, int64_t dim, ::std::optional dtype, at::Tensor & out) { + return at::_ops::log_softmax_int_out::call(self, dim, dtype, out); +} + +// aten::log_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor +inline at::Tensor log_softmax(const at::Tensor & self, at::Dimname dim, ::std::optional dtype=::std::nullopt) { + return at::_ops::log_softmax_Dimname::call(self, dim, dtype); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_batch_norm_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_batch_norm_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..af42972f9e52d914d948c9b40e6cc8734e649740 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_batch_norm_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 miopen_batch_norm_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::miopen_batch_norm_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "miopen_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon) -> (Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon); +}; + +struct TORCH_API miopen_batch_norm_backward_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, double, 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::miopen_batch_norm_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "miopen_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3f4afa486b40929a96500dc9b7d3ef3ad7aa55d6 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor miopen_depthwise_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_linear_backward.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_linear_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..5cdcfb4bd09398bbdd56c7b135d5dc7d281b5e32 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mkldnn_linear_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::mkldnn_linear_backward(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask) -> (Tensor, Tensor, Tensor) +inline ::std::tuple mkldnn_linear_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask) { + return at::_ops::mkldnn_linear_backward::call(self, grad_output, weight, output_mask); +} + +// aten::mkldnn_linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple mkldnn_linear_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask) { + return at::_ops::mkldnn_linear_backward_out::call(self, grad_output, weight, output_mask, out0, out1, out2); +} +// aten::mkldnn_linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple mkldnn_linear_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::mkldnn_linear_backward_out::call(self, grad_output, weight, output_mask, out0, out1, out2); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nan_to_num_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nan_to_num_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..56c34fcc0b682c45a6aee98e17ac9cb3241c845a --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nan_to_num_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 & nan_to_num_out(at::Tensor & out, const at::Tensor & self, ::std::optional nan=::std::nullopt, ::std::optional posinf=::std::nullopt, ::std::optional neginf=::std::nullopt); +TORCH_API at::Tensor & nan_to_num_outf(const at::Tensor & self, ::std::optional nan, ::std::optional posinf, ::std::optional neginf, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..780cef22d8a893fbddc59ba98278afd7d9db45ae --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/narrow_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 narrow(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, int64_t length); +TORCH_API at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nextafter_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nextafter_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..02645788b0b8eebe115c6b41a78f7553b4ad7e7c --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nextafter_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 nextafter(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & nextafter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & nextafter_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & nextafter_(at::Tensor & self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/polygamma_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/polygamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..76f8045fc928132c6e03d2b045102282ae8c8486 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/polygamma_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 polygamma_out { + using schema = 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::polygamma") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "polygamma.out(int n, Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(int64_t n, const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, const at::Tensor & self, at::Tensor & out); +}; + +struct TORCH_API polygamma { + using schema = 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::polygamma") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "polygamma(int n, Tensor self) -> Tensor") + static at::Tensor call(int64_t n, const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, const at::Tensor & self); +}; + +struct TORCH_API polygamma_ { + using schema = at::Tensor & (at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::polygamma_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "polygamma_(Tensor(a!) self, int n) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, int64_t n); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t n); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/q_scale_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/q_scale_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f494443543046695b27af70d48722a679ffa6f51 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/q_scale_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 double q_scale_quant(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/qscheme.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/qscheme.h new file mode 100644 index 0000000000000000000000000000000000000000..a14248498a9bd9b4d32046cc9d9f978a4a8f4f64 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/qscheme.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/reflection_pad1d_backward_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reflection_pad1d_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ea6238cc626c84eb8569729a2334547aa0643260 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reflection_pad1d_backward_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_reflection_pad1d_backward_out_cpu : public at::meta::structured_reflection_pad1d_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::ArrayRef padding, const at::Tensor & grad_input); +}; +struct TORCH_API structured_reflection_pad1d_backward_out_cuda : public at::meta::structured_reflection_pad1d_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & self, at::ArrayRef padding, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/relu6_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/relu6_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9625e8fb4ea498708a09fb871cc50b55806a7537 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/relu6_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 relu6(const at::Tensor & self); +TORCH_API at::Tensor & relu6_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reshape_compositeimplicitautograd_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reshape_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9a56072b046dfcb38909876ced5c95b76000b285 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/reshape_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 reshape(const at::Tensor & self, at::IntArrayRef shape); +TORCH_API at::Tensor reshape_symint(const at::Tensor & self, c10::SymIntArrayRef shape); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rsqrt_compositeexplicitautogradnonfunctional_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rsqrt_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3e04092b76efe4dd6d012aad0c34c21519a6f36f --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/rsqrt_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor rsqrt(const at::Tensor & self); +TORCH_API at::Tensor & rsqrt_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/scalar_tensor_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/scalar_tensor_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9a8502d99901eed2d1845338672b3e9327c874dc --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/scalar_tensor_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 scalar_tensor { + using schema = at::Tensor (const at::Scalar &, ::std::optional, ::std::optional, ::std::optional, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::scalar_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "scalar_tensor(Scalar s, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(const at::Scalar & s, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & s, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API scalar_tensor_out { + using schema = 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::scalar_tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "scalar_tensor.out(Scalar s, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Scalar & s, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & s, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/silu_backward_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/silu_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..505f27b6861823111cba54240b129dcf36fbf3ca --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/silu_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 silu_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::silu_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "grad_input") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "silu_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); +}; + +struct TORCH_API silu_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::silu_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "silu_backward(Tensor grad_output, Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sin_cpu_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sin_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3e48f8fc83c012f2faf4689c437deb6b813f2552 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sin_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 sin(const at::Tensor & self); +TORCH_API at::Tensor & sin_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & sin_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & sin_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_dim_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_dim_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f1dd8f9c2a0e8a502ad5838bb234aeabe1101d23 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sparse_dim_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 int64_t sparse_dim_default(const at::Tensor & self); +TORCH_API int64_t sparse_dim_sparse(const at::Tensor & self); +TORCH_API int64_t sparse_dim_sparse_csr(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_digamma.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_digamma.h new file mode 100644 index 0000000000000000000000000000000000000000..c4c2bad856134692c93fc0e10e8693ef82aaf924 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_digamma.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::special_digamma(Tensor self) -> Tensor +inline at::Tensor special_digamma(const at::Tensor & self) { + return at::_ops::special_digamma::call(self); +} + +// aten::special_digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_digamma_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::special_digamma_out::call(self, out); +} +// aten::special_digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & special_digamma_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::special_digamma_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_i0_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_i0_native.h new file mode 100644 index 0000000000000000000000000000000000000000..944ab587d90961a263d37fe1ca924dcbde26e64e --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_i0_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 special_i0(const at::Tensor & self); +TORCH_API at::Tensor & special_i0_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_i0e_cuda_dispatch.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_i0e_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eed4e1cff11d87ac33d0b6eb36bddfa644c45f31 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_i0e_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor special_i0e(const at::Tensor & self); +TORCH_API at::Tensor & special_i0e_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_i0e_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_round_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_round_native.h new file mode 100644 index 0000000000000000000000000000000000000000..309ab73393eebbe0a1585dc76a44c99ded69edaf --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/special_round_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 special_round(const at::Tensor & self, int64_t decimals=0); +TORCH_API at::Tensor & special_round_out(const at::Tensor & self, int64_t decimals, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sqrt.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sqrt.h new file mode 100644 index 0000000000000000000000000000000000000000..432568ef4f494f6ad132e4bafbfbea43c6c5bc28 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sqrt.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::sqrt(Tensor self) -> Tensor +inline at::Tensor sqrt(const at::Tensor & self) { + return at::_ops::sqrt::call(self); +} + +// aten::sqrt_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & sqrt_(at::Tensor & self) { + return at::_ops::sqrt_::call(self); +} + +// aten::sqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sqrt_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::sqrt_out::call(self, out); +} +// aten::sqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sqrt_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::sqrt_out::call(self, out); +} + +} diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sqrt_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sqrt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7be1ba026f21fcd83b33a73e364ec3692408636b --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/sqrt_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 sqrt { + 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::sqrt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sqrt(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 sqrt_ { + 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::sqrt_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sqrt_(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 sqrt_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::sqrt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sqrt.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/swapaxes_ops.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/swapaxes_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..234e116ef1d9038331211c49a8d133e82fee0a19 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/swapaxes_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 swapaxes { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::swapaxes") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "swapaxes(Tensor(a) self, int axis0, int axis1) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self, int64_t axis0, int64_t axis1); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t axis0, int64_t axis1); +}; + +struct TORCH_API swapaxes_ { + using schema = at::Tensor & (at::Tensor &, int64_t, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::swapaxes_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "swapaxes_(Tensor(a!) self, int axis0, int axis1) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, int64_t axis0, int64_t axis1); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t axis0, int64_t axis1); +}; + +}} // namespace at::_ops diff --git a/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/zero_native.h b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/zero_native.h new file mode 100644 index 0000000000000000000000000000000000000000..dff55dbc70fd584be1564b0be44e00e7c1d0bd09 --- /dev/null +++ b/.venv/lib/python3.11/site-packages/torch/include/ATen/ops/zero_native.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor zero(const at::Tensor & self); +TORCH_API at::Tensor & zero_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & zero_(at::Tensor & self); +TORCH_API at::Tensor & zero_nested_(at::Tensor & self); +TORCH_API at::Tensor & zero_sparse_(at::Tensor & self); +TORCH_API at::Tensor & zero_sparse_csr_(at::Tensor & self); +TORCH_API at::Tensor & zero_meta_(at::Tensor & self); +TORCH_API at::Tensor & mkldnn_zero_(at::Tensor & self); +} // namespace native +} // namespace at