class_docstr: Vocabulary class.
  
  :param pad_value: The string value for the padding position.
  :param oov_value: The string value for the out-of-vocabulary terms.
  
  Examples:
      >>> vocab = BertVocabulary(pad_value='[PAD]', oov_value='[UNK]')
      >>> indices = vocab.transform(list('ABCDDZZZ'))
class_docstr_tok: ["Vocabulary","class",".",":","param","pad_value",":","The","string","value","for","the","padding","position",".",":","param","oov_value",":","The","string","value","for","the","out-of-vocabulary","terms",".","Examples",":",">",">",">","vocab","=","BertVocabulary","(","pad_value=","'","[","PAD","]","'",",","oov_value=","'","[","UNK","]","'",")",">",">",">","indices","=","vocab.transform","(","list","(","'ABCDDZZZ","'",")",")"]
docstr: Transform a list of tokens to corresponding indices.
docstr_tok: ["Transform","a","list","of","tokens","to","corresponding","indices","."]
code: def transform(self, input_: list) -> list:
      """Transform a list of tokens to corresponding indices."""
      return [self._context["term_index"][token] for token in input_]
  
file_path: MatchZoo/matchzoo/preprocessors/units/vocabulary.py
imports: from .stateful_unit import StatefulUnit
label_desc: Use image node_id 3 for calling the BertVocabulary obj's underlying member method code with example usage: obj.transform(input_) and returns: unknown