#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION) #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 batch_norm_backward { using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional &, const ::std::optional &, const ::std::optional &, const ::std::optional &, bool, double, ::std::array, const at::Tensor &); using ptr_schema = schema*; // See Note [static constexpr char* members for windows NVCC] static constexpr const char* name = "aten::batch_norm_backward"; static constexpr const char* overload_name = ""; static constexpr const char* schema_str = "batch_norm_backward(Tensor grad_out, Tensor input, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, bool update, float eps, bool[3] output_mask, Tensor reserve) -> (Tensor, Tensor, Tensor)"; static ::std::tuple call(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, bool update, double eps, ::std::array output_mask, const at::Tensor & reserve); static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & weight, const ::std::optional & running_mean, const ::std::optional & running_var, const ::std::optional & save_mean, const ::std::optional & save_var, bool update, double eps, ::std::array output_mask, const at::Tensor & reserve); }; }} // namespace at::_ops #else #error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined." #endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION)