class_docstr: Perform fuzzy matching against a translation memory and
  augment source examples with target matches for Neural Fuzzy Repair.
  :cite:`bulte-tezcan-2019-neural`
class_docstr_tok: ["Perform","fuzzy","matching","against","a","translation","memory","and","augment","source","examples","with","target","matches","for","Neural","Fuzzy","Repair",".",":","cite",":","`","bulte-tezcan-2019-neural","`"]
docstr: Add the fuzzy match token to the src vocab.
docstr_tok: ["Add","the","fuzzy","match","token","to","the","src","vocab","."]
code: def get_specials(cls, opts):
      """Add the fuzzy match token to the src vocab."""
  
      return ([opts.fuzzy_token], list())
  
imports: from onmt.utils.logging import logger
  from onmt.transforms import register_transform
  from .transform import Transform
  from rapidfuzz import fuzz, process
  import numpy
  import time
label_desc: Use image node_id 4 for calling the FuzzyMatchTransform obj's underlying member method code with example usage: obj.get_specials(cls, opts) and returns: list,  list