class_docstr: Transforms all verb tenses in sentence.
  
  Offline Vocabulary is provided.
  Notice: transformed sentence will have syntax errors.
  
  TODO, align verb tense to avoid grammar error.
class_docstr_tok: ["Transforms","all","verb","tenses","in","sentence",".","Offline","Vocabulary","is","provided",".","Notice",":","transformed","sentence","will","have","syntax","errors",".","TODO",",","align","verb","tense","to","avoid","grammar","error","."]
docstr: Returns a list containing all possible words .
  
  :param str word: token word to transform.
  :param str pos: pos tag
  :param int n: max number of candidates
  :return list candidates: candidates list
docstr_tok: ["Returns","a","list","containing","all","possible","words",".",":","param","str","word",":","token","word","to","transform",".",":","param","str","pos",":","pos","tag",":","param","int","n",":","max","number","of","candidates",":","return","list","candidates",":","candidates","list"]
code: def _get_candidates(self, word, pos=None, n=1):
      r"""
      Returns a list containing all possible words .
  
      :param str word: token word to transform.
      :param str pos: pos tag
      :param int n: max number of candidates
      :return list candidates: candidates list
  
      """
      if pos not in VERB_TAG:
          return []
      else:
          candidates = self._get_tense_list(word)
          return self.sample_num(candidates, n)
  
file_path: textflint/textflint/generation/transformation/UT/tense.py
imports: from ...transformation import WordSubstitute
  from ....common.settings import VERB_PATH, VERB_TAG
  from ....common.utils.load import json_loader
  from ....common.utils.install import download_if_needed
label_desc: Use image node_id 4 for calling the Tense obj's underlying member method code with example usage: obj._get_candidates(word, pos, n) and returns: list, self