#pragma once

// @generated by torchgen/gen.py from Operator.h

#include <tuple>
#include <vector>

// 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 <ATen/core/ATen_fwd.h>

namespace at {
namespace _ops {


struct TORCH_API _batch_norm_impl_index {
  using schema = ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,int64_t> (const at::Tensor &, const ::std::optional<at::Tensor> &, const ::std::optional<at::Tensor> &, const ::std::optional<at::Tensor> &, const ::std::optional<at::Tensor> &, bool, double, double, bool);
  using ptr_schema = schema*;
  // See Note [static constexpr char* members for windows NVCC]
  STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_batch_norm_impl_index")
  STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
  STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_batch_norm_impl_index(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> (Tensor, Tensor, Tensor, Tensor, int)")
  static ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,int64_t> call(const at::Tensor & input, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, const ::std::optional<at::Tensor> & running_mean, const ::std::optional<at::Tensor> & running_var, bool training, double momentum, double eps, bool cudnn_enabled);
  static ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,int64_t> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, const ::std::optional<at::Tensor> & running_mean, const ::std::optional<at::Tensor> & running_var, bool training, double momentum, double eps, bool cudnn_enabled);
};

}} // namespace at::_ops
