}

// -----

// CHECK-LABEL: func @rfft_1D
func.func @rfft_1D(%arg0: tensor<8xf32>) -> tensor<5xcomplex<f32>> {
  %fftlength = "tf.Const"() {value = dense<[8]> : tensor<1xi32>} : () -> (tensor<1xi32>)
  // CHECK: "mhlo.fft"(%arg0) <{fft_length = dense<8> : tensor<1xi64>, fft_type = #mhlo<fft_type RFFT>}> : (tensor<8xf32>
  %0 = "tf.RFFT"(%arg0, %fftlength) : (tensor<8xf32>, tensor<1xi32>) -> tensor<5xcomplex<f32>>

                         symbolizeFftType(fft_string).value()),
        rewriter.getI64TensorAttr(fft_length));
    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.