code: def bleu_wrapper(ref_filename, hyp_filename, case_sensitive=False):
      """Compute BLEU for two files (reference and hypothesis translation)."""
      ref_lines = text_encoder.native_to_unicode(
          tf.gfile.Open(ref_filename, "r").read()
      ).split("\n")
      hyp_lines = text_encoder.native_to_unicode(
          tf.gfile.Open(hyp_filename, "r").read()
      ).split("\n")
      assert len(ref_lines) == len(hyp_lines), "{} != {}".format(
          len(ref_lines), len(hyp_lines)
      )
      if not case_sensitive:
          ref_lines = [x.lower() for x in ref_lines]
          hyp_lines = [x.lower() for x in hyp_lines]
      ref_tokens = [bleu_tokenize(x) for x in ref_lines]
      hyp_tokens = [bleu_tokenize(x) for x in hyp_lines]
      return compute_bleu(ref_tokens, hyp_tokens)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import math
  import os
  import re
  import sys
  import time
  import unicodedata
  import numpy
  import six
  from six.moves import range
  from six.moves import zip
  from tensor2tensor.data_generators import text_encoder
  import tensorflow.compat.v1
label_desc: Use image node_id 5 for calling a global function with example usage: bleu_wrapper(ref_filename, hyp_filename, case_sensitive) and returns: compute_bleu