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
              and not self.include_special_char
          ):
              continue
          """
                  TODO: cannot skip word that were split by tokenizer
              """
          # skip stopwords by list
          if self.stopwords is not None and _token in self.stopwords:
              continue
  
          # skip stopwords by regex
          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
  
          # skip if char is too less
          if len(token) < self.min_char:
              continue
  
          results.append(token_idx)
  
      return results
  
file_path: nlpaug/nlpaug/augmenter/char/char_augmenter.py
imports: import string
  import re
  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 6 for calling the CharAugmenter obj's underlying member method code with example usage: obj.pre_skip_aug(tokens, tuple_idx) and returns: results