code: def compute_bleu_summaries(hook_args):
    
    decode_hparams = hook_args.decode_hparams
  
    if not (decode_hparams.decode_reference and decode_hparams.decode_to_file):
      return None
  
    values = []
    bleu = 100 * bleu_hook.bleu_wrapper(
        decode_hparams.decode_reference, decode_hparams.decode_to_file)
    values.append(tf.Summary.Value(tag="BLEU", simple_value=bleu))
    tf.logging.info("%s: BLEU = %6.2f" % (decode_hparams.decode_to_file, bleu))
    if hook_args.hparams.mlperf_mode:
      current_step = decode_hparams.mlperf_decode_step
      mlperf_log.transformer_print(
          key=mlperf_log.EVAL_TARGET, value=decode_hparams.mlperf_threshold)
      mlperf_log.transformer_print(
          key=mlperf_log.EVAL_ACCURACY,
          value={
              "epoch": max(current_step // decode_hparams.iterations_per_loop - 1,
                           0),
              "value": bleu
          })
      mlperf_log.transformer_print(key=mlperf_log.EVAL_STOP)
  
    if bleu >= decode_hparams.mlperf_threshold:
      decode_hparams.set_hparam("mlperf_success", True)
  
    return values
docs: Compute BLEU core summaries using the decoder output.
  
    Args:
      hook_args: DecodeHookArgs namedtuple
    Returns:
      A list of tf.Summary values if hook_args.hparams contains the
      reference file and the translated file.