//===----------------------------------------------------------------------===//
// 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

  %0 = "tf.L2Loss"(%arg0) : (tensor<?x?xf32>) -> tensor<f32>

  // CHECK: return %[[LOSS]] : tensor<f32>
  func.return %0 : tensor<f32>
}

// CHECK-LABEL: func @l2_loss_unranked
func.func @l2_loss_unranked(%arg0: tensor<*xf32>) -> tensor<f32> {
  // CHECK: tf.L2Loss
  %0 = "tf.L2Loss"(%arg0) : (tensor<*xf32>) -> tensor<f32>
  func.return %0 : tensor<f32>
}

      "GatherV2",
      "HSVToRGB",
      "IFFT",
      "IFFT2D",
      "IFFT3D",
      "IRFFT",
      "IRFFT2D",
      "IRFFT3D",
      "If",
      "InTopKV2",
      "L2Loss",
      "LeakyRelu",
      "LinSpace",
      "ListDiff",
      "LogMatrixDeterminant",
      "LowerBound",
      "MatMul",
      "MatrixBandPart",
      "MatrixDiag",
      "MatrixDiagPart",

  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
}


def TF_L2LossOp : TF_Op<"L2Loss", [Pure]> {
  let summary = "L2 Loss.";

  let description = [{
Computes half the L2 norm of a tensor without the `sqrt`:

    output = sum(t ** 2) / 2
  }];

  let arguments = (ins