code: def wer(self):
      if self.words_ == 0:
          wer = np.nan
      else:
          wer = (
              100.0
              * (
                  self.insertions_
                  + self.deletions_
                  + self.substitutions_
              )
              / self.words_
          )
      return wer
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import re
  from collections import deque
  from enum import Enum
  import numpy
label_desc: Use image node_id 4 for calling the WERTransformer obj's underlying member method code with example usage: obj.wer() and returns: wer