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: Return the current BLEU score, according to the accumulated counts.
docstr_tok: ["Return","the","current","BLEU","score",",","according","to","the","accumulated","counts","."]
code: def bleu(self):
      """Return the current BLEU score, according to the accumulated counts."""
      # brevity penalty (smoothed a bit: if candidate length is 0, we change it to 1e-5
      # to avoid division by zero)
      bp = 1.0
      if self.cand_lens[0] <= self.ref_len:
          bp = math.exp(
              1.0
              - old_div(
                  self.ref_len,
                  (
                      float(self.cand_lens[0])
                      if self.cand_lens[0]
                      else 1e-5
                  ),
              )
          )
  
      return bp * self.ngram_precision()
  
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 6 for calling the BLEUScore obj's underlying member method code with example usage: obj.bleu() and returns: unknown