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: Options for fuzzy matching.
docstr_tok: ["Options","for","fuzzy","matching","."]
code: def add_options(cls, parser):
      """Options for fuzzy matching."""
  
      group = parser.add_argument_group("Transform/FuzzyMatching")
      group.add(
          "--tm_path",
          "-tm_path",
          type=str,
          help="Path to a flat text TM.",
      )
      group.add(
          "--fuzzy_corpus_ratio",
          "-fuzzy_corpus_ratio",
          type=float,
          default=0.1,
          help="Ratio of corpus to augment with fuzzy matches.",
      )
      group.add(
          "--fuzzy_threshold",
          "-fuzzy_threshold",
          type=int,
          default=70,
          help="The fuzzy matching threshold.",
      )
      group.add(
          "--tm_delimiter",
          "-tm_delimiter",
          type=str,
          default="\t",
          help="The delimiter used in the flat text TM.",
      )
      group.add(
          "--fuzzy_token",
          "-fuzzy_token",
          type=str,
          default="｟fuzzy｠",
          help="The fuzzy token to be added with the matches.",
      )
      group.add(
          "--fuzzymatch_min_length",
          "-fuzzymatch_min_length",
          type=int,
          default=4,
          help="Min length for TM entries and examples to match.",
      )
      group.add(
          "--fuzzymatch_max_length",
          "-fuzzymatch_max_length",
          type=int,
          default=70,
          help="Max length for TM entries and examples to match.",
      )
  
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 2 for calling the FuzzyMatchTransform obj's underlying member method code with example usage: obj.add_options(cls, parser) without return types