class_docstr: Customtokenizer which will tokenize the input text as words or phases and convert the words (str) to an index (int) using the vocab.
  If you would like tokens, please use `hub.BertTokenizer`.
docstr: Clean up a list of simple English tokenization artifacts like spaces before punctuations and abreviated forms.
docstr_tok: ["Clean","up","a","list","of","simple","English","tokenization","artifacts","like","spaces","before","punctuations","and","abreviated","forms","."]
code: def clean_up_tokenization(self, out_string: str) -> str:
      """
      Clean up a list of simple English tokenization artifacts like spaces before punctuations and abreviated forms.
      """
      out_string = (
          out_string.replace(" .", ".")
          .replace(" ?", "?")
          .replace(" !", "!")
          .replace(" ,", ",")
          .replace(" ' ", "'")
          .replace(" n't", "n't")
          .replace(" 'm", "'m")
          .replace(" 's", "'s")
          .replace(" 've", "'ve")
          .replace(" 're", "'re")
      )
      return out_string
  
imports: import collections
  import inspect
  import os
  from typing import Callable, List, Union
  import paddlehub
  from paddlehub.utils.log import logger
  from paddlehub.text.bert_tokenizer import BasicTokenizer
  from paddlehub.text.utils import load_vocab, whitespace_tokenize
label_desc: Use image node_id 13 for calling the CustomTokenizer obj's underlying member method code with example usage: obj.clean_up_tokenization(out_string) and returns: out_string