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a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_async_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_async_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cfdf4be4fa4dead18edb85e332dc3b67a9c09031 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_assert_async_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 _assert_async { + using schema = void (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::_assert_async") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_assert_async(Tensor self) -> ()") + static void call(const at::Tensor & self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API _assert_async_msg { + using schema = void (const at::Tensor &, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_assert_async") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "msg") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_assert_async.msg(Tensor self, str assert_msg) -> ()") + static void call(const at::Tensor & self, c10::string_view assert_msg); + static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view assert_msg); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_native.h new file mode 100644 index 0000000000000000000000000000000000000000..cbfd6224f56fcc13c9702e6c2a0052fff617e085 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API void _cufft_clear_plan_cache(at::DeviceIndex device_index); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5d3a525d7b2de1784f2e850d08778b8cd69edbe0 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_fill_mem_eff_dropout_mask_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 & _fill_mem_eff_dropout_mask_(at::Tensor & self, double dropout_p, int64_t seed, int64_t offset); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_compositeexplicitautograd_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..17366263624bb2174802a181a416237d2f78c3e0 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_compositeexplicitautograd_dispatch.h @@ -0,0 +1,38 @@ +#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_div(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_out(at::TensorList out, at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_outf(at::TensorList self, const at::Scalar & scalar, at::TensorList out); +TORCH_API void _foreach_div_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_out(at::TensorList out, at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_outf(at::TensorList self, at::TensorList other, at::TensorList out); +TORCH_API void _foreach_div_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_out(at::TensorList out, at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_outf(at::TensorList self, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_div_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_div(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_out(at::TensorList out, at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_outf(at::TensorList self, const at::Tensor & other, at::TensorList out); +TORCH_API void _foreach_div_(at::TensorList self, const at::Tensor & other); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_cuda_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..095352971134779f667bda619fcd91c68f059789 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_div_cuda_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_div(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_div_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::TensorList other); +TORCH_API void _foreach_div_(at::TensorList self, at::TensorList other); +TORCH_API ::std::vector _foreach_div(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_div_(at::TensorList self, at::ArrayRef scalars); +TORCH_API ::std::vector _foreach_div(at::TensorList self, const at::Tensor & other); +TORCH_API void _foreach_div_(at::TensorList self, const at::Tensor & other); + +} // namespace cuda +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg.h new file mode 100644 index 0000000000000000000000000000000000000000..9ea6f19a4144f176f27fd98fcfe367627a61034c --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_neg.h @@ -0,0 +1,44 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foreach_neg(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_neg(at::TensorList self) { + return at::_ops::_foreach_neg::call(self); +} + +// aten::_foreach_neg_(Tensor(a!)[] self) -> () +inline void _foreach_neg_(at::TensorList self) { + return at::_ops::_foreach_neg_::call(self); +} + +// aten::_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_neg_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_neg_out::call(self, out); +} +// aten::_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_neg_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_neg_out::call(self, out); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_cuda_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..be94485cbd4d99a4f4ea30e2c47482fe4b517a55 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sub_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 ::std::vector _foreach_sub(at::TensorList self, const at::Scalar & scalar); +TORCH_API void _foreach_sub_(at::TensorList self, const at::Scalar & scalar); +TORCH_API ::std::vector _foreach_sub(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API void _foreach_sub_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); +TORCH_API ::std::vector _foreach_sub(at::TensorList self, at::ArrayRef scalars); +TORCH_API void _foreach_sub_(at::TensorList self, at::ArrayRef scalars); + +} // namespace cuda +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fa769769a3e7e754ef970e0b760368e6a827e00f --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adagrad_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 _fused_adagrad_ { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_fused_adagrad_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_fused_adagrad_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor(d!)[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()") + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +struct TORCH_API _fused_adagrad_out { + using schema = void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, const ::std::optional &, const ::std::optional &, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_fused_adagrad") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_fused_adagrad.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] state_sums, Tensor(d!)[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf, at::TensorList out); +}; + +struct TORCH_API _fused_adagrad { + using schema = ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, bool, const ::std::optional &, const ::std::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_fused_adagrad") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_fused_adagrad(Tensor[] self, Tensor[] grads, Tensor[] state_sums, Tensor[] state_steps, *, float lr, float lr_decay, float weight_decay, float eps, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] state_sums_out, Tensor[] state_steps_out)") + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> call(at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); + static ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector> redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList state_sums, at::TensorList state_steps, double lr, double lr_decay, double weight_decay, double eps, bool maximize, const ::std::optional & grad_scale, const ::std::optional & found_inf); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_slogdet_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_slogdet_native.h new file mode 100644 index 0000000000000000000000000000000000000000..05d92df30daf7040a848b0091b9bef2f078d971f --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_slogdet_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured__linalg_slogdet_out : public at::meta::structured__linalg_slogdet { +void impl(const at::Tensor & A, const at::Tensor & sign, const at::Tensor & logabsdet, const at::Tensor & LU, const at::Tensor & pivots); +}; +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_log_softmax_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_log_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8882cca8009f50385f669ab281f0472b1841b898 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_log_softmax_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 _log_softmax { + using schema = at::Tensor (const at::Tensor &, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_log_softmax") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_log_softmax(Tensor self, int dim, bool half_to_float) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim, bool half_to_float); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float); +}; + +struct TORCH_API _log_softmax_out { + using schema = at::Tensor & (const 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::_log_softmax") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_log_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bf57e1ff83a2b0962e21f817969cb131b545c139 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_tensor_storage_offsets_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 _nested_tensor_storage_offsets { + 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::_nested_tensor_storage_offsets") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_nested_tensor_storage_offsets(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 _nested_tensor_storage_offsets_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::_nested_tensor_storage_offsets") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_nested_tensor_storage_offsets.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/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dc9d5e9c2d0eeed87033ea3bf28add58059e15ed --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_nnpack_spatial_convolution_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _nnpack_spatial_convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_nnpack_spatial_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride); +}; + +struct TORCH_API _nnpack_spatial_convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const ::std::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_nnpack_spatial_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, SymInt[2] stride=1, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_backward_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..4cb993d70d4143aff90075579995dee130b16542 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_backward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_mm_reduce_impl_backward { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const at::Tensor &, ::std::array); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_mm_reduce_impl_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_mm_reduce_impl_backward(Tensor self, Tensor grad_out, Tensor weight, str reduce, Tensor arg_out, bool[2] output_mask) -> (Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & self, const at::Tensor & grad_out, const at::Tensor & weight, c10::string_view reduce, const at::Tensor & arg_out, ::std::array output_mask); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_out, const at::Tensor & weight, c10::string_view reduce, const at::Tensor & arg_out, ::std::array output_mask); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_to_dense.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_to_dense.h new file mode 100644 index 0000000000000000000000000000000000000000..1572846e954f9067ebe591d10f1087f832ef05d1 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_to_dense.h @@ -0,0 +1,34 @@ +#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::_to_dense.out(Tensor self, ScalarType? dtype=None, bool? masked_grad=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_dense_out(at::Tensor & out, const at::Tensor & self, ::std::optional dtype=::std::nullopt, ::std::optional masked_grad=::std::nullopt) { + return at::_ops::_to_dense_out::call(self, dtype, masked_grad, out); +} +// aten::_to_dense.out(Tensor self, ScalarType? dtype=None, bool? masked_grad=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_dense_outf(const at::Tensor & self, ::std::optional dtype, ::std::optional masked_grad, at::Tensor & out) { + return at::_ops::_to_dense_out::call(self, dtype, masked_grad, out); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_bsc.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_bsc.h new file mode 100644 index 0000000000000000000000000000000000000000..1d2ca534f244e75827e92326d3a8b69291f9553e --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_bsc.h @@ -0,0 +1,34 @@ +#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::_to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_bsc_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim=::std::nullopt) { + return at::_ops::_to_sparse_bsc_out::call(self, blocksize, dense_dim, out); +} +// aten::_to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _to_sparse_bsc_outf(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional dense_dim, at::Tensor & out) { + return at::_ops::_to_sparse_bsc_out::call(self, blocksize, dense_dim, out); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr_cuda_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..11d25a7a1364cb3045282e3a6bf3564d93a2b760 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _to_sparse_csr(const at::Tensor & self, ::std::optional dense_dim=::std::nullopt); + +} // namespace cuda +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f59253f640e54b1f0187cf11acc46f070bff1a9c --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _upsample_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 cpu +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d.h new file mode 100644 index 0000000000000000000000000000000000000000..4561b19b04878e9a1aa6ae75781d1fc046f357a5 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_avg_pool1d.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::adaptive_avg_pool1d(Tensor self, int[1] output_size) -> Tensor +inline at::Tensor adaptive_avg_pool1d(const at::Tensor & self, at::IntArrayRef output_size) { + return at::_ops::adaptive_avg_pool1d::call(self, output_size); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool1d_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..296bea9a2405dda5109861ede57bd6ba067756ae --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool1d_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 avg_pool1d { + using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::avg_pool1d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "avg_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, bool ceil_mode=False, bool count_include_pad=True) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/bernoulli_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/bernoulli_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5eeb0e432de70ad6b991f01e1e8e33089aa7b7ad --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/bernoulli_ops.h @@ -0,0 +1,105 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API bernoulli { + using schema = at::Tensor (const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bernoulli") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bernoulli(Tensor self, *, Generator? generator=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional generator); +}; + +struct TORCH_API bernoulli_out { + using schema = at::Tensor & (const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bernoulli") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bernoulli.out(Tensor self, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API bernoulli__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bernoulli_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bernoulli_.Tensor(Tensor(a!) self, Tensor p, *, Generator? generator=None) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & p, ::std::optional generator); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & p, ::std::optional generator); +}; + +struct TORCH_API bernoulli__float { + using schema = at::Tensor & (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::bernoulli_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "float") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bernoulli_.float(Tensor(a!) self, float p=0.5, *, Generator? generator=None) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, double p, ::std::optional generator); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double p, ::std::optional generator); +}; + +struct TORCH_API bernoulli_p { + using schema = at::Tensor (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::bernoulli") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "p") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bernoulli.p(Tensor self, float p, *, Generator? generator=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, double p, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, ::std::optional generator); +}; + +struct TORCH_API bernoulli_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bernoulli") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bernoulli.Tensor_out(Tensor self, Tensor p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & p, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & p, ::std::optional generator, at::Tensor & out); +}; + +struct TORCH_API bernoulli_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, ::std::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bernoulli") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bernoulli.Tensor(Tensor self, Tensor p, *, Generator? generator=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & p, ::std::optional generator); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & p, ::std::optional generator); +}; + +struct TORCH_API bernoulli_float_out { + using schema = at::Tensor & (const at::Tensor &, double, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bernoulli") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "float_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bernoulli.float_out(Tensor self, float p=0.5, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, ::std::optional generator, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift.h new file mode 100644 index 0000000000000000000000000000000000000000..6aec113690257e42bfbd3c69f50a9dc7838396e8 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::bitwise_left_shift.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor bitwise_left_shift(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::bitwise_left_shift_Tensor::call(self, other); +} + +// aten::bitwise_left_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_left_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::bitwise_left_shift_Tensor_out::call(self, other, out); +} +// aten::bitwise_left_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_left_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::bitwise_left_shift_Tensor_out::call(self, other, out); +} + +// aten::bitwise_left_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor bitwise_left_shift(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::bitwise_left_shift_Tensor_Scalar::call(self, other); +} + +// aten::bitwise_left_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_left_shift_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::bitwise_left_shift_Tensor_Scalar_out::call(self, other, out); +} +// aten::bitwise_left_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_left_shift_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::bitwise_left_shift_Tensor_Scalar_out::call(self, other, out); +} + +// aten::bitwise_left_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor +inline at::Tensor bitwise_left_shift(const at::Scalar & self, const at::Tensor & other) { + return at::_ops::bitwise_left_shift_Scalar_Tensor::call(self, other); +} + +// aten::bitwise_left_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_left_shift_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::bitwise_left_shift_Scalar_Tensor_out::call(self, other, out); +} +// aten::bitwise_left_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_left_shift_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::bitwise_left_shift_Scalar_Tensor_out::call(self, other, out); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift_meta_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a932f8ef0efeb98ec395ba59ced02b0c00b726fc --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift_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 bitwise_left_shift(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_left_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_left_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +TORCH_API at::Tensor & bitwise_left_shift_(at::Tensor & self, const at::Tensor & other); + +} // namespace meta +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/chalf_compositeimplicitautograd_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/chalf_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c2b0d79fbe50c0f9aba006c9495b07e3a5b29095 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/chalf_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 chalf(const at::Tensor & self, ::std::optional memory_format=::std::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/clamp_min_meta_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/clamp_min_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9db44acda30f45d2c09b16719feb1f2a8d17e21f --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/clamp_min_meta_dispatch.h @@ -0,0 +1,30 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor clamp_min(const at::Tensor & self, const at::Scalar & min); +TORCH_API at::Tensor & clamp_min_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min); +TORCH_API at::Tensor & clamp_min_outf(const at::Tensor & self, const at::Scalar & min, at::Tensor & out); +TORCH_API at::Tensor & clamp_min_(at::Tensor & self, const at::Scalar & min); +TORCH_API at::Tensor clamp_min(const at::Tensor & self, const at::Tensor & min); +TORCH_API at::Tensor & clamp_min_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & min); +TORCH_API at::Tensor & clamp_min_outf(const at::Tensor & self, const at::Tensor & min, at::Tensor & out); +TORCH_API at::Tensor & clamp_min_(at::Tensor & self, const at::Tensor & min); + +} // namespace meta +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/convolution_backward_overrideable.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/convolution_backward_overrideable.h new file mode 100644 index 0000000000000000000000000000000000000000..4935388f1ddffd8254c8c57b8e6b335bde188568 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/convolution_backward_overrideable.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::convolution_backward_overrideable(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias) +inline ::std::tuple convolution_backward_overrideable(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask); + } +} + +// aten::convolution_backward_overrideable(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias) +inline ::std::tuple convolution_backward_overrideable_symint(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask); + } +} + +// aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple convolution_backward_overrideable_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask, out0, out1, out2); + } +} + +// aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple convolution_backward_overrideable_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), transposed, c10::fromIntArrayRefSlow(output_padding), groups, output_mask, out0, out1, out2); + } +} + +// aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple convolution_backward_overrideable_symint_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); + } +} + +// aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) +inline ::std::tuple convolution_backward_overrideable_symint_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); +} +namespace symint { + template ::value>> + ::std::tuple convolution_backward_overrideable_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { + return at::_ops::convolution_backward_overrideable_out::call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); + } +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/crow_indices.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/crow_indices.h new file mode 100644 index 0000000000000000000000000000000000000000..f50167a832a3808b34033868487c9f6cb2d3172e --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/crow_indices.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/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft2.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft2.h new file mode 100644 index 0000000000000000000000000000000000000000..5eda142008abec89036164dbeee032d5dd2276c3 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fft_hfft2.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::fft_hfft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor +inline at::Tensor fft_hfft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_hfft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm); + } +} + +// aten::fft_hfft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor +inline at::Tensor fft_hfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfft2::call(self, s, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_hfft2(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfft2::call(self, s, dim, norm); + } +} + +// aten::fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_hfft2_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + const at::Tensor & fft_hfft2_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_hfft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_hfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + const at::Tensor & fft_hfft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_hfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out); + } +} + +// aten::fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_hfft2_symint_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfft2_out::call(self, s, dim, norm, out); +} +namespace symint { + template ::value>> + const at::Tensor & fft_hfft2_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional norm=::std::nullopt) { + return at::_ops::fft_hfft2_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline const at::Tensor & fft_hfft2_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_hfft2_out::call(self, s, dim, norm, out); +} +namespace symint { + template ::value>> + const at::Tensor & fft_hfft2_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional norm, const at::Tensor & out) { + return at::_ops::fft_hfft2_out::call(self, s, dim, norm, out); + } +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/flatten_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/flatten_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a982886ce6cc22541980e2755cd531a4e278e2c6 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/flatten_ops.h @@ -0,0 +1,61 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API flatten_using_ints { + 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::flatten") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "using_ints") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "flatten.using_ints(Tensor(a) self, int start_dim=0, int end_dim=-1) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self, int64_t start_dim, int64_t end_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t start_dim, int64_t end_dim); +}; + +struct TORCH_API flatten_named_out_dim { + using schema = at::Tensor (const at::Tensor &, int64_t, int64_t, at::Dimname); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::flatten") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "named_out_dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "flatten.named_out_dim(Tensor(a) self, int start_dim, int end_dim, Dimname out_dim) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self, int64_t start_dim, int64_t end_dim, at::Dimname out_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t start_dim, int64_t end_dim, at::Dimname out_dim); +}; + +struct TORCH_API flatten_using_names { + using schema = at::Tensor (const at::Tensor &, at::Dimname, at::Dimname, at::Dimname); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::flatten") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "using_names") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "flatten.using_names(Tensor(a) self, Dimname start_dim, Dimname end_dim, Dimname out_dim) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self, at::Dimname start_dim, at::Dimname end_dim, at::Dimname out_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname start_dim, at::Dimname end_dim, at::Dimname out_dim); +}; + +struct TORCH_API flatten_DimnameList { + using schema = at::Tensor (const at::Tensor &, at::DimnameList, at::Dimname); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::flatten") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "DimnameList") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "flatten.DimnameList(Tensor(a) self, Dimname[] dims, Dimname out_dim) -> Tensor(a)") + static at::Tensor call(const at::Tensor & self, at::DimnameList dims, at::Dimname out_dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dims, at::Dimname out_dim); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/float_power.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/float_power.h new file mode 100644 index 0000000000000000000000000000000000000000..45085b194a5b02fd63b48ddb32ca47a60a358203 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/float_power.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & exponent) { + return at::_ops::float_power_Tensor_Tensor_out::call(self, exponent, out); +} +// aten::float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_outf(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out) { + return at::_ops::float_power_Tensor_Tensor_out::call(self, exponent, out); +} + +// aten::float_power.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor +inline at::Tensor float_power(const at::Tensor & self, const at::Tensor & exponent) { + return at::_ops::float_power_Tensor_Tensor::call(self, exponent); +} + +// aten::float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & exponent) { + return at::_ops::float_power_Scalar_out::call(self, exponent, out); +} +// aten::float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_outf(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out) { + return at::_ops::float_power_Scalar_out::call(self, exponent, out); +} + +// aten::float_power.Scalar(Scalar self, Tensor exponent) -> Tensor +inline at::Tensor float_power(const at::Scalar & self, const at::Tensor & exponent) { + return at::_ops::float_power_Scalar::call(self, exponent); +} + +// aten::float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & exponent) { + return at::_ops::float_power_Tensor_Scalar_out::call(self, exponent, out); +} +// aten::float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & float_power_outf(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out) { + return at::_ops::float_power_Tensor_Scalar_out::call(self, exponent, out); +} + +// aten::float_power.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor +inline at::Tensor float_power(const at::Tensor & self, const at::Scalar & exponent) { + return at::_ops::float_power_Tensor_Scalar::call(self, exponent); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/frac_cuda_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/frac_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1145715947f92322b84af159b27065a9398f89b8 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/frac_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 frac(const at::Tensor & self); +TORCH_API at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & frac_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fractional_max_pool2d_meta.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fractional_max_pool2d_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..42f87f37ee585e96452dbaa3f1443798d7cb115c --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/fractional_max_pool2d_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_fractional_max_pool2d : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); +}; + +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/from_file_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/from_file_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e1eb56399283e8beeb6acc4478294c37fc2c7af0 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/from_file_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 from_file { + using schema = at::Tensor (c10::string_view, ::std::optional, ::std::optional, ::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::from_file") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "from_file(str filename, bool? shared=None, int? size=0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::string_view filename, ::std::optional shared, ::std::optional size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view filename, ::std::optional shared, ::std::optional size, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory); +}; + +struct TORCH_API from_file_out { + using schema = at::Tensor & (c10::string_view, ::std::optional, ::std::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::from_file") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "from_file.out(str filename, bool? shared=None, int? size=0, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::string_view filename, ::std::optional shared, ::std::optional size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view filename, ::std::optional shared, ::std::optional size, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/geometric_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/geometric_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f0e4c91614cb3efd3276c809bf44f3cd17dca6fd --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/geometric_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 & geometric_(at::Tensor & self, double p, ::std::optional generator=::std::nullopt); + +} // namespace cpu +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/index_select.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/index_select.h new file mode 100644 index 0000000000000000000000000000000000000000..14b44e34d517916bb34155ff705d10a3662a412b --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/index_select.h @@ -0,0 +1,53 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::index_select.out(Tensor self, int dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & index_select_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index) { + return at::_ops::index_select_out::call(self, dim, index, out); +} +// aten::index_select.out(Tensor self, int dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & index_select_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, at::Tensor & out) { + return at::_ops::index_select_out::call(self, dim, index, out); +} + +// aten::index_select(Tensor self, int dim, Tensor index) -> Tensor +inline at::Tensor index_select(const at::Tensor & self, int64_t dim, const at::Tensor & index) { + return at::_ops::index_select::call(self, dim, index); +} + +// aten::index_select.dimname_out(Tensor self, Dimname dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & index_select_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, const at::Tensor & index) { + return at::_ops::index_select_dimname_out::call(self, dim, index, out); +} +// aten::index_select.dimname_out(Tensor self, Dimname dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & index_select_outf(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, at::Tensor & out) { + return at::_ops::index_select_dimname_out::call(self, dim, index, out); +} + +// aten::index_select.dimname(Tensor self, Dimname dim, Tensor index) -> Tensor +inline at::Tensor index_select(const at::Tensor & self, at::Dimname dim, const at::Tensor & index) { + return at::_ops::index_select_dimname::call(self, dim, index); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/is_signed.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/is_signed.h new file mode 100644 index 0000000000000000000000000000000000000000..decbb4e5a1622220c9517ac286d85f7426581d76 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/is_signed.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::is_signed(Tensor self) -> bool +inline bool __dispatch_is_signed(const at::Tensor & self) { + return at::_ops::is_signed::call(self); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_backward.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..551e1851e842e972401ac83b1e57bfc1fe0be40e --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_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::leaky_relu_backward.grad_input(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & leaky_relu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result) { + return at::_ops::leaky_relu_backward_grad_input::call(grad_output, self, negative_slope, self_is_result, grad_input); +} +// aten::leaky_relu_backward.grad_input(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & leaky_relu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result, at::Tensor & grad_input) { + return at::_ops::leaky_relu_backward_grad_input::call(grad_output, self, negative_slope, self_is_result, grad_input); +} + +// aten::leaky_relu_backward(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result) -> Tensor +inline at::Tensor leaky_relu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result) { + return at::_ops::leaky_relu_backward::call(grad_output, self, negative_slope, self_is_result); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4e4195c83ac435051d55bf92aa4880bbf801ff50 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_linalg_ldl_solve_out : public at::meta::structured_linalg_ldl_solve { +void impl(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_compositeexplicitautogradnonfunctional_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fb39fd7369f28c7dc6608c99d58114572245c83c --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_lu_factor_ex_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 ::std::tuple linalg_lu_factor_ex(const at::Tensor & A, bool pivot=true, bool check_errors=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/log1p_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/log1p_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..caa9a8c54f7256eaf657580873e6e7c3b6a058b7 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/log1p_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 log1p { + 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::log1p") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "log1p(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 log1p_ { + 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::log1p_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "log1p_(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 log1p_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::log1p") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "log1p.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/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_cuda_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..13a50f76303ba1b336f82ecb4e3071506ced7088 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/minimum_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 minimum(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & minimum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & minimum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu_cuda_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..50d671d4d035ff189a70a0a7bb3f5c0399055637 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_convolution_add_relu_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_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups); +TORCH_API at::Tensor miopen_convolution_add_relu_symint(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const ::std::optional & alpha, const ::std::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups); + +} // namespace cuda +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/select_scatter_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/select_scatter_native.h new file mode 100644 index 0000000000000000000000000000000000000000..6ba7d6a2207b60ee99d67f79ebc302c57f564907 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/select_scatter_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 & select_scatter_out_symint(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index, at::Tensor & out); +TORCH_API at::Tensor select_scatter_symint(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/softshrink_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/softshrink_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9e0e783ef6a4bd9e11fb519aafdf21c85ddbd110 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/softshrink_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_softshrink_out : public at::meta::structured_softshrink { +void impl(const at::Tensor & self, const at::Scalar & lambd, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_y1_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_y1_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a6b96e9ed6d967c3a516487b7be3f46dea3f309f --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_bessel_y1_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_bessel_y1(const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_bessel_y1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..921752fe249a75b96dae7e0b9cb20f8c87b65d74 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_t_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_chebyshev_polynomial_t { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_t(Tensor x, Tensor n) -> Tensor") + static at::Tensor call(const at::Tensor & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n); +}; + +struct TORCH_API special_chebyshev_polynomial_t_x_scalar { + using schema = at::Tensor (const at::Scalar &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "x_scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_t.x_scalar(Scalar x, Tensor n) -> Tensor") + static at::Tensor call(const at::Scalar & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n); +}; + +struct TORCH_API special_chebyshev_polynomial_t_n_scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "n_scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_t.n_scalar(Tensor x, Scalar n) -> Tensor") + static at::Tensor call(const at::Tensor & x, const at::Scalar & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n); +}; + +struct TORCH_API special_chebyshev_polynomial_t_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_t.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_chebyshev_polynomial_t_x_scalar_out { + using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "x_scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_t.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_chebyshev_polynomial_t_n_scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_t") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "n_scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_t.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..236562d05ecfabc6eb6696f9f0f642909fdae87d --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_u_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_chebyshev_polynomial_u { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_u") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor") + static at::Tensor call(const at::Tensor & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n); +}; + +struct TORCH_API special_chebyshev_polynomial_u_x_scalar { + using schema = at::Tensor (const at::Scalar &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_u") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "x_scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor") + static at::Tensor call(const at::Scalar & x, const at::Tensor & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n); +}; + +struct TORCH_API special_chebyshev_polynomial_u_n_scalar { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_u") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "n_scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor") + static at::Tensor call(const at::Tensor & x, const at::Scalar & n); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n); +}; + +struct TORCH_API special_chebyshev_polynomial_u_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_u") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_chebyshev_polynomial_u_x_scalar_out { + using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_u") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "x_scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +}; + +struct TORCH_API special_chebyshev_polynomial_u_n_scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_chebyshev_polynomial_u") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "n_scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_logsumexp_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_logsumexp_native.h new file mode 100644 index 0000000000000000000000000000000000000000..e710ca6c22d7c9dc6514a9b95b1d68fa5899b614 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_logsumexp_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_logsumexp(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false); +TORCH_API at::Tensor & special_logsumexp_out(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_ndtri_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_ndtri_native.h new file mode 100644 index 0000000000000000000000000000000000000000..fd944cda131b4fa2aed8215862d942fa36434a24 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/special_ndtri_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_special_ndtri_out : public at::meta::structured_special_ndtri { +void impl(const at::Tensor & self, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/squeeze_copy_native.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/squeeze_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..595780318afdbdc5026e7d38de88a1214b34d4b0 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/squeeze_copy_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & squeeze_copy_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor squeeze_copy(const at::Tensor & self); +TORCH_API at::Tensor & squeeze_copy_dim_out(const at::Tensor & self, int64_t dim, at::Tensor & out); +TORCH_API at::Tensor squeeze_copy_dim(const at::Tensor & self, int64_t dim); +TORCH_API at::Tensor & squeeze_copy_dims_out(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out); +TORCH_API at::Tensor squeeze_copy_dims(const at::Tensor & self, at::IntArrayRef dim); +} // namespace native +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/sym_storage_offset_compositeimplicitautograd_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/sym_storage_offset_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..56bb86216b37b67225000ae99e652919f75b38bf --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/sym_storage_offset_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 c10::SymInt sym_storage_offset(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_ops.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..8dbd174fcf8c1ff25f05dc26291129278b8892ef --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API trunc { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::trunc") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "trunc(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API trunc_ { + using schema = at::Tensor & (at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::trunc_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "trunc_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API trunc_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::trunc") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_cpu_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..e737debc10d916e66acc6a9e83aeb467bba118b2 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple unique_dim(const at::Tensor & self, int64_t dim, bool sorted=true, bool return_inverse=false, bool return_counts=false); + +} // namespace cpu +} // namespace at diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_real_copy.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_real_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..c7270d0b4dc4d40d4cd8296eedf696fc9abd4f2e --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/view_as_real_copy.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::view_as_real_copy(Tensor self) -> Tensor +inline at::Tensor view_as_real_copy(const at::Tensor & self) { + return at::_ops::view_as_real_copy::call(self); +} + +// aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_as_real_copy_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::view_as_real_copy_out::call(self, out); +} +// aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_as_real_copy_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::view_as_real_copy_out::call(self, out); +} + +} diff --git a/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/vsplit_compositeimplicitautograd_dispatch.h b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/vsplit_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..248adc9ead211c73a62affee2bf6b4721a9109e7 --- /dev/null +++ b/parrot/lib/python3.10/site-packages/torch/include/ATen/ops/vsplit_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 ::std::vector vsplit(const at::Tensor & self, int64_t sections); +TORCH_API ::std::vector vsplit(const at::Tensor & self, at::IntArrayRef indices); + +} // namespace compositeimplicitautograd +} // namespace at