code: def pre_skip_aug(self, tokens, tuple_idx=None):
      results = []
      for token_idx, token in enumerate(tokens):
          if tuple_idx is not None:
              _token = token[tuple_idx]
          else:
              _token = token
          # skip punctuation
          if _token in string.punctuation:
              continue
          # skip stopwords by list
          if self.is_stop_words(_token):
              continue
          # skip stopwords by regex
          # https://github.com/makcedward/nlpaug/issues/81
          if self.stopwords_regex is not None and (
              self.stopwords_regex.match(_token)
              or self.stopwords_regex.match(" " + _token + " ")
              or self.stopwords_regex.match(" " + _token)
              or self.stopwords_regex.match(_token + " ")
          ):
              continue
  
          results.append(token_idx)
  
      return results
  
imports: import string
  import re
  from typing import Iterable
  from nlpaug.util import Method
  from nlpaug.util.text.tokenizer import Tokenizer
  from nlpaug import Augmenter
  from nlpaug.util import WarningException, WarningName, WarningCode, WarningMessage
label_desc: Use image node_id 5 for calling the WordAugmenter obj's underlying member method code with example usage: obj.pre_skip_aug(tokens, tuple_idx) and returns: results