content: # -*- coding: utf-8 -*-
  # Copyright 2017 Google Inc.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #      http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  """BLEU metric implementation.
  """
  
  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 as np
  
  from six.moves import urllib
  import tensorflow as tf
  
  
  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)
  