return ArraysAreCastCompatible(inferred, actual);
    }
  }];
}

def TF_QuantizeAndDequantizeV2Op : TF_Op<"QuantizeAndDequantizeV2", [Pure]> {
  let summary = "Quantizes then dequantizes a tensor.";

  let description = [{
This op simulates the precision loss from the quantized forward pass by:

1. Quantizing the tensor to fixed point numbers, which should match the target

    *   `tf.einsum()`raises `ValueError` for unsupported equations like
        `"ii->"`.
    *   Add DCT-I and IDCT-I in `tf.signal.dct` and `tf.signal.idct`.
    *   Add LU decomposition op.
    *   Add quantile loss to gradient boosted trees in estimator.
    *   Add `round_mode` to `QuantizeAndDequantizeV2` op to select rounding
        algorithm.
    *   Add `unicode_encode`, `unicode_decode`, `unicode_decode_with_offsets`,