docstr: Available options for terminology matching.
docstr_tok: ["Available","options","for","terminology","matching","."]
code: def add_options(cls, parser):
      """Available options for terminology matching."""
  
      group = parser.add_argument_group("Transform/Terminology")
      group.add(
          "--termbase_path",
          "-termbase_path",
          type=str,
          help="Path to a dictionary file with terms.",
      )
      group.add(
          "--src_spacy_language_model",
          "-src_spacy_language_model",
          type=str,
          help="Name of the spacy language model for the source corpus.",
      )
      group.add(
          "--tgt_spacy_language_model",
          "-tgt_spacy_language_model",
          type=str,
          help="Name of the spacy language model for the target corpus.",
      )
      group.add(
          "--term_corpus_ratio",
          "-term_corpus_ratio",
          type=float,
          default=0.3,
          help="Ratio of corpus to augment with terms.",
      )
      group.add(
          "--term_example_ratio",
          "-term_example_ratio",
          type=float,
          default=0.2,
          help="Max terms allowed in an example.",
      )
      group.add(
          "--src_term_stoken",
          "-src_term_stoken",
          type=str,
          help="The source term start token.",
          default="｟src_term_start｠",
      )
      group.add(
          "--tgt_term_stoken",
          "-tgt_term_stoken",
          type=str,
          help="The target term start token.",
          default="｟tgt_term_start｠",
      )
      group.add(
          "--tgt_term_etoken",
          "-tgt_term_etoken",
          type=str,
          help="The target term end token.",
          default="｟tgt_term_end｠",
      )
      group.add(
          "--term_source_delimiter",
          "-term_source_delimiter",
          type=str,
          help="Any special token used for augmented source sentences. "
          "The default is the fuzzy token used in the "
          "FuzzyMatch transform.",
          default="｟fuzzy｠",
      )
  
imports: from onmt.utils.logging import logger
  from onmt.transforms import register_transform
  from .transform import Transform
  import spacy
  import ahocorasick
  import re
label_desc: Use image node_id 2 for calling the TerminologyTransform obj's underlying member method code with example usage: obj.add_options(cls, parser) without return types