{"REDUCEWINDOWPW", {"BiasAddGrad", "LRN", "LRNGrad"}},
          {"BN",
           {"FusedBatchNorm", "FusedBatchNormV2", "FusedBatchNormV3",
            "_FusedBatchNormEx", "FusedBatchNormGrad", "FusedBatchNormGradV2",
            "FusedBatchNormGradV3"}},
          {"Conv", {"_FusedConv2D"}},
          {"SORT", {"TopKV2"}},  // XLA version much faster then TF version.
          {"MISC",

  // CHECK-NEXT: %[[x_backprop:.*]] = mhlo.convert %[[mul3]] : tensor<8x8x8x8xf32>
  // CHECK-NEXT: return %[[x_backprop]] : tensor<8x8x8x8xf32>

    return success();
  }
};

using ConvertRFFTOp = ConvertFFTOp<TF::RFFTOp>;
using ConvertIRFFTOp = ConvertFFTOp<TF::IRFFTOp>;

// The base class to convert TensorFlow FusedBatchNormGrad*Op to HLO
// BatchNormGradOp for training and a sequence of binary ops for inference.
// TODO(b/145536565): move to legalize_tf_patterns.td if it applies.
template <typename FusedBatchNormGradOpT>

  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;

  let hasCanonicalizer = 1;

  let hasVerifier = 1;
}

def TF_FusedBatchNormGradOp : TF_Op<"FusedBatchNormGrad", [Pure]> {
  let summary = "Gradient for batch normalization.";

  let description = [{
Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW".