class_docstr: Generate potential insertion for a word using a masked language model.
  
  Based off of:
  CLARE: Contextualized Perturbation for Textual Adversarial Attack" (Li et al, 2020):
  https://arxiv.org/abs/2009.07502
  
  Args:
      masked_language_model (Union[str|transformers.AutoModelForMaskedLM]): Either the name of pretrained masked language model from `transformers` model hub
          or the actual model. Default is `bert-base-uncased`.
      tokenizer (obj): The tokenizer of the corresponding model. If you passed in name of a pretrained model for `masked_language_model`,
          you can skip this argument as the correct tokenizer can be infered from the name. However, if you're passing the actual model, you must
          provide a tokenizer.
      max_length (int): the max sequence length the masked language model is designed to work with. Default is 512.
      window_size (int): The number of surrounding words to include when making top word prediction.
          For each position to insert we take `window_size // 2` words to the left and `window_size // 2` words to the right and pass the text within the window
          to the masked language model. Default is `float("inf")`, which is equivalent to using the whole text.
      max_candidates (int): maximum number of candidates to consider inserting for each position. Replacements are
          ranked by model's confidence.
      min_confidence (float): minimum confidence threshold each new word must pass.
code: def extra_repr_keys(self):
      return [
          "masked_lm_name",
          "max_length",
          "max_candidates",
          "min_confidence",
      ]
  
file_path: TextAttack/textattack/transformations/word_insertions/word_insertion_masked_lm.py
imports: import re
  import torch
  from transformers import AutoModelForMaskedLM, AutoTokenizer
  from textattack.shared import utils
  from .word_insertion import WordInsertion
label_desc: Use image node_id 5 for calling the WordInsertionMaskedLM obj's underlying member method code with example usage: obj.extra_repr_keys() and returns: list