class_docstr: Transforms an input by replacing its tokens with words of mask language
  predicted.
  To accelerate transformation for long text, input single sentence to
  language model rather than whole text.
code: def skip_aug(self, words, words_indices, tokens, mask, **kwargs):
      if self.islist:
          return self.pre_skip_aug_list(
              words, words_indices, tokens, mask
          )
      else:
          return self.pre_skip_aug(words, words_indices, tokens, mask)
  
file_path: textflint/textflint/generation/transformation/UTCN/cn_nasal.py
imports: from ...transformation import CnWordSubstitute
  from pypinyin import lazy_pinyin
  from Pinyin2Hanzi import DefaultHmmParams
  from Pinyin2Hanzi import viterbi
label_desc: Use image node_id 4 for calling the CnNasal obj's underlying member method code with example usage: obj.skip_aug(words, words_indices, tokens, mask) and returns: self, self