#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 native_batch_norm { using schema = ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double); using ptr_schema = schema*; // See Note [static constexpr char* members for windows NVCC] STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::native_batch_norm") STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor)") static ::std::tuple call(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps); static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps); }; struct TORCH_API native_batch_norm_out { using schema = ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &); using ptr_schema = schema*; // See Note [static constexpr char* members for windows NVCC] STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::native_batch_norm") STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "native_batch_norm.out(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!))") static ::std::tuple call(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); }; }} // namespace at::_ops