class_docstr: Augmenter that performs a given action at the word level.
  Valid actions are defined below as methods
class_docstr_tok: ["Augmenter","that","performs","a","given","action","at","the","word","level",".","Valid","actions","are","defined","below","as","methods"]
docstr: Augmenter that splits words in two
docstr_tok: ["Augmenter","that","splits","words","in","two"]
code: def split(self, data: str) -> str:
      """Augmenter that splits words in two"""
      results = []
      tokens = tokenize(data)
      aug_word_cnt = self._generate_aug_cnt(
          len(tokens), self.aug_min, self.aug_max, self.aug_p
      )
      filtered_word_idxes = self.pre_skip_aug(tokens)
      aug_word_idxes = set(
          get_aug_idxes(
              self,
              tokens,
              filtered_word_idxes,
              aug_word_cnt,
              Method.WORD,
              self.min_char,
          )
      )
  
      if not aug_word_idxes:
          return data
  
      for t_i, token in enumerate(tokens):
          if t_i not in aug_word_idxes:
              results.append(token)
              continue
  
          target_token = tokens[t_i]
          split_position = random.randint(1, len(target_token) - 1)
          first_token = target_token[:split_position]
          second_token = target_token[split_position:]
          results.extend([first_token, second_token])
  
      return detokenize(results)
  
file_path: AugLy/augly/text/augmenters/words_augmenter.py
imports: import random
  from typing import List, Optional
  from augly.text.augmenters.utils import detokenize, get_aug_idxes, tokenize
  from augly.utils.libsndfile import install_libsndfile
  from nlpaug.augmenter.word import WordAugmenter
  from nlpaug.util import Method
label_desc: Use image node_id 3 for calling the WordsAugmenter obj's underlying member method code with example usage: obj.split(data) and returns: detokenize, data