code: def moses_multi_bleu(hypotheses, references, lowercase=False):
      """Calculate the bleu score for hypotheses and references
      using the MOSES ulti-bleu.perl script.
  
      Args:
        hypotheses: A numpy array of strings where each string is a single example.
        references: A numpy array of strings where each string is a single example.
        lowercase: If true, pass the "-lc" flag to the multi-bleu script
  
      Returns:
        The BLEU score as a float32 value.
      """
  
      if np.size(hypotheses) == 0:
          return np.float32(0.0)
  
      # Get MOSES multi-bleu script
      try:
          multi_bleu_path, _ = urllib.request.urlretrieve(
              "https://raw.githubusercontent.com/moses-smt/mosesdecoder/"
              "master/scripts/generic/multi-bleu.perl"
          )
          os.chmod(multi_bleu_path, 0o755)
      except:  # pylint: disable=W0702
          tf.logging.info(
              "Unable to fetch multi-bleu.perl script, using local."
          )
          metrics_dir = os.path.dirname(os.path.realpath(__file__))
          bin_dir = os.path.abspath(
              os.path.join(metrics_dir, "..", "..", "bin")
          )
          multi_bleu_path = os.path.join(
              bin_dir, "tools/multi-bleu.perl"
          )
  
      # Dump hypotheses and references to tempfiles
      hypothesis_file = tempfile.NamedTemporaryFile()
      hypothesis_file.write("\n".join(hypotheses).encode("utf-8"))
      hypothesis_file.write(b"\n")
      hypothesis_file.flush()
      reference_file = tempfile.NamedTemporaryFile()
      reference_file.write("\n".join(references).encode("utf-8"))
      reference_file.write(b"\n")
      reference_file.flush()
  
      # Calculate BLEU using multi-bleu script
      with open(hypothesis_file.name, "r") as read_pred:
          bleu_cmd = [multi_bleu_path]
          if lowercase:
              bleu_cmd += ["-lc"]
          bleu_cmd += [reference_file.name]
          try:
              bleu_out = subprocess.check_output(
                  bleu_cmd, stdin=read_pred, stderr=subprocess.STDOUT
              )
              bleu_out = bleu_out.decode("utf-8")
              bleu_score = re.search(r"BLEU = (.+?),", bleu_out).group(
                  1
              )
              bleu_score = float(bleu_score)
          except subprocess.CalledProcessError as error:
              if error.output is not None:
                  tf.logging.warning(
                      "multi-bleu.perl script returned non-zero exit code"
                  )
                  tf.logging.warning(error.output)
              bleu_score = np.float32(0.0)
  
      # Close temp files
      hypothesis_file.close()
      reference_file.close()
  
      return np.float32(bleu_score)
  
file_path: seq2seq/seq2seq/metrics/bleu.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import os
  import re
  import subprocess
  import tempfile
  import numpy
  from six.moves import urllib
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: moses_multi_bleu(hypotheses, references, lowercase) and returns: np, np