class_docstr: An accumulator object capable of computing BLEU score using multiple references.
  The BLEU score is always smoothed a bit so that it's never undefined. For sentence-level
  measurements, proper smoothing should be used via the smoothing parameter (set to 1.0 for
  the same behavior as default Moses's MERT sentence BLEU).
docstr: Create the scoring object.
  @param max_ngram: the n-gram level to compute the score for (default: 4)
  @param case_sensitive: use case-sensitive matching (default: no)
  @param smoothing: constant to add for smoothing (defaults to 0.0, sentBLEU uses 1.0)
docstr_tok: ["Create","the","scoring","object",".","@","param","max_ngram",":","the","n-gram","level","to","compute","the","score","for","(","default",":","4",")","@","param","case_sensitive",":","use","case-sensitive","matching","(","default",":","no",")","@","param","smoothing",":","constant","to","add","for","smoothing","(","defaults","to","0.0",",","sentBLEU","uses","1.0",")"]
code: def __init__(self, max_ngram=4, case_sensitive=False, smoothing=0.0):
      """Create the scoring object.
      @param max_ngram: the n-gram level to compute the score for (default: 4)
      @param case_sensitive: use case-sensitive matching (default: no)
      @param smoothing: constant to add for smoothing (defaults to 0.0, sentBLEU uses 1.0)
      """
      super(BLEUScore, self).__init__(max_ngram, case_sensitive)
      self.smoothing = smoothing
      self.reset()
  
imports: from __future__ import unicode_literals
  from __future__ import division
  from builtins import zip
  from builtins import range
  from past.utils import old_div
  from builtins import object
  from collections import defaultdict
  import math
  import re
label_desc: Use image node_id 1 to create a new BLEUScore object from inherited base classes: NGramScore with example: obj = BLEUScore(max_ngram, case_sensitive, smoothing)