class_docstr: Runs end-to-end tokenization.
docstr: Converts a sequence of tokens (string) in a single string.
docstr_tok: ["Converts","a","sequence","of","tokens","(","string",")","in","a","single","string","."]
code: def convert_tokens_to_string(
      tokens, clean_up_tokenization_spaces=True
  ):
      """Converts a sequence of tokens (string) in a single string."""
  
      def clean_up_tokenization(out_string):
          """Clean up a list of simple English tokenization artifacts
          like spaces before punctuations and abbreviated 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
  
      text = " ".join(tokens).replace(" ##", "").strip()
      if clean_up_tokenization_spaces:
          clean_text = clean_up_tokenization(text)
          return clean_text
      else:
          return text
  
imports: from __future__ import absolute_import, division, print_function
  import collections
  import re
  import unicodedata
  import six
label_desc: Use image node_id 5 for calling the FullTokenizer obj's underlying member method code with example usage: obj.convert_tokens_to_string(tokens, clean_up_tokenization_spaces) and returns: out_string, clean_text, text