class_docstr: Generate potential replacements for a word using a masked language
  model.
code: def _get_transformations(self, current_text, indices_to_modify):
      words = current_text.words
      transformed_texts = []
  
      for i in indices_to_modify:
          word_to_replace = words[i]
          replacement_words = self.get_replacement_words(
              current_text, i
          )
          transformed_texts_idx = []
          for r in replacement_words:
              if r == word_to_replace:
                  continue
              transformed_texts_idx.append(
                  current_text.replace_word_at_index(i, r)
              )
          transformed_texts.extend(transformed_texts_idx)
  
      return transformed_texts
  
file_path: TextAttack/textattack/transformations/word_swaps/chn_transformations/chinese_word_swap_masked.py
imports: from transformers import pipeline
  from .None import WordSwap
label_desc: Use image node_id 3 for calling the ChineseWordSwapMaskedLM obj's underlying member method code with example usage: obj._get_transformations(current_text, indices_to_modify) and returns: transformed_texts