*   Add `UnifiedGRU` as the new GRU implementation for tf2.0. Change the default
    recurrent activation function for GRU from `hard_sigmoid` to `sigmoid`, and
    `reset_after` to True in 2.0. Historically recurrent activation is
    `hard_sigmoid` since it is fast than 'sigmoid'. With new unified backend
    between CPU and GPU mode, since the CuDNN kernel is using sigmoid, we change

    QuantizableResult,
    PredOpTrait<"input and output must have same element type",
      TFL_TCresVTEtIsSameAsOp<0, 0>>]> {
  let summary = "Hardswish activation function.";
  let description = [{
    Computes hard-swish activation function
      f(x) -> (x * relu6(x+3))/6
    element-wise.
  }];

  let arguments = (ins TFL_TensorOf<[F32, QUI8, QI8]>:$input);