code: def __init__(self, model_type, mode="neighbor", tokenizer=None):
      super().__init__(cache=True)
  
      self.model_type = model_type  # /sentence, word or character
      self.mode = mode
  
      if tokenizer:
          self.tokenizer = tokenizer
      else:
          if self.model_type == "sentence":
              try:
                  from nltk.tokenize import sent_tokenize
              except ModuleNotFoundError:
                  raise ModuleNotFoundError(
                      "Missed nltk library. Install transfomers by `pip install nltk`"
                  )
              self.tokenizer = sent_tokenize
  
imports: from nlpaug.model.word_rule.word_rule import WordRule
label_desc: Use image node_id 1 to create a new Shuffle object from inherited base classes: WordRule with example: obj = Shuffle(model_type, mode, tokenizer)