#pragma once // @generated by torchgen/gen.py from Operator.h #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 _ops { struct TORCH_API to_dtype_layout { using schema = at::Tensor (const at::Tensor &, ::std::optional, ::std::optional, ::std::optional, ::std::optional, bool, bool, ::std::optional); using ptr_schema = schema*; // See Note [static constexpr char* members for windows NVCC] static constexpr const char* name = "aten::to"; static constexpr const char* overload_name = "dtype_layout"; static constexpr const char* schema_str = "to.dtype_layout(Tensor(a) self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, bool non_blocking=False, bool copy=False, MemoryFormat? memory_format=None) -> Tensor(a)"; static at::Tensor call(const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, bool non_blocking, bool copy, ::std::optional memory_format); static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional dtype, ::std::optional layout, ::std::optional device, ::std::optional pin_memory, bool non_blocking, bool copy, ::std::optional memory_format); }; struct TORCH_API to_device { using schema = at::Tensor (const at::Tensor &, at::Device, at::ScalarType, bool, bool, ::std::optional); using ptr_schema = schema*; // See Note [static constexpr char* members for windows NVCC] static constexpr const char* name = "aten::to"; static constexpr const char* overload_name = "device"; static constexpr const char* schema_str = "to.device(Tensor(a) self, Device device, ScalarType dtype, bool non_blocking=False, bool copy=False, MemoryFormat? memory_format=None) -> Tensor(a)"; static at::Tensor call(const at::Tensor & self, at::Device device, at::ScalarType dtype, bool non_blocking, bool copy, ::std::optional memory_format); static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Device device, at::ScalarType dtype, bool non_blocking, bool copy, ::std::optional memory_format); }; struct TORCH_API to_dtype { using schema = at::Tensor (const at::Tensor &, at::ScalarType, bool, bool, ::std::optional); using ptr_schema = schema*; // See Note [static constexpr char* members for windows NVCC] static constexpr const char* name = "aten::to"; static constexpr const char* overload_name = "dtype"; static constexpr const char* schema_str = "to.dtype(Tensor(a) self, ScalarType dtype, bool non_blocking=False, bool copy=False, MemoryFormat? memory_format=None) -> Tensor(a)"; static at::Tensor call(const at::Tensor & self, at::ScalarType dtype, bool non_blocking, bool copy, ::std::optional memory_format); static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ScalarType dtype, bool non_blocking, bool copy, ::std::optional memory_format); }; struct TORCH_API to_other { using schema = at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool, ::std::optional); using ptr_schema = schema*; // See Note [static constexpr char* members for windows NVCC] static constexpr const char* name = "aten::to"; static constexpr const char* overload_name = "other"; static constexpr const char* schema_str = "to.other(Tensor(a) self, Tensor other, bool non_blocking=False, bool copy=False, MemoryFormat? memory_format=None) -> Tensor(a)"; static at::Tensor call(const at::Tensor & self, const at::Tensor & other, bool non_blocking, bool copy, ::std::optional memory_format); static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, bool non_blocking, bool copy, ::std::optional memory_format); }; }} // namespace at::_ops