class_docstr: Transformation that simulate typos error to transform sentence.
  
      https://arxiv.org/pdf/1711.02173.pdf
class_docstr_tok: ["Transformation","that","simulate","typos","error","to","transform","sentence",".","https",":","\/\/arxiv.org\/pdf\/1711.02173.pdf"]
docstr: Returns a list of words with typo errors.
  
  :param string word: the original word to be replaced
  :param int n: number of try times
  :return list: the list of candidate words to replace original words
docstr_tok: ["Returns","a","list","of","words","with","typo","errors",".",":","param","string","word",":","the","original","word","to","be","replaced",":","param","int","n",":","number","of","try","times",":","return","list",":","the","list","of","candidate","words","to","replace","original","words"]
code: def _get_replacement_words(self, word, n=1):
      r"""
      Returns a list of words with typo errors.
  
      :param string word: the original word to be replaced
      :param int n: number of try times
      :return list: the list of candidate words to replace original words
      """
  
      candidates = []
  
      for i in range(n):
          typo_method = self._get_typo_method()
          # default add one typo to each word
          typo_candidate = typo_method(
              word,
              num=1,
              skip_first=self.skip_first_char,
              skip_last=self.skip_last_char,
          )
          if typo_candidate == word:
              typo_method = random.choice([replace, insert, delete])
              typo_candidate = typo_method(
                  word,
                  num=1,
                  skip_first=self.skip_first_char,
                  skip_last=self.skip_last_char,
              )
          if typo_candidate:
              candidates.append(typo_candidate)
  
      return list(candidates)
  
file_path: textflint/textflint/generation/transformation/NER/ent_typos.py
imports: from ....common.utils.word_op import *
  from ..transformation import Transformation
  from ....common.utils.list_op import trade_off_sub_words
label_desc: Use image node_id 4 for calling the EntTypos obj's underlying member method code with example usage: obj._get_replacement_words(word, n) and returns: list