//===----------------------------------------------------------------------===//
// L2Loss op patterns.
//===----------------------------------------------------------------------===//

def GetAllAxes : NativeCodeCall<
  "GetI64ElementsAttrForSeq("
  "0, $0.getType().cast<RankedTensorType>().getRank(), &$_builder)">;

// L2Loss is lowered using the formula,
// L2Loss(input) = Sum(input * input) / 2

using ops::Conv2D;
using ops::Conv2DBackpropInput;
using ops::DepthwiseConv2dNative;
using ops::Elu;
using ops::FractionalAvgPool;
using ops::FractionalMaxPool;
using ops::FusedBatchNormV3;
using ops::L2Loss;
using ops::LogSoftmax;
using ops::LRN;
using ops::MaxPool;
using ops::MaxPool3D;
using ops::MaxPoolV2;
using ops::Placeholder;
using ops::Relu;
using ops::Relu6;
using ops::Selu;
using ops::Softmax;

                  std::vector<Output>* grad_outputs) {
  grad_outputs->push_back(Mul(scope, op.input(0), grad_inputs[0]));
  return scope.status();
}
REGISTER_GRADIENT_OP("L2Loss", L2LossGrad);

Status BiasAddGradHelper(const Scope& scope, const Operation& op,
                         const std::vector<Output>& grad_inputs,
                         std::vector<Output>* grad_outputs) {