class_docstr: Runs end-to-end tokenziation.
code: def tokenize(self, text):
      split_tokens = []
      for token in self.basic_tokenizer.tokenize(text):
          subtokens = self.cache.get(token, None)
          if subtokens is None:
              subtokens = self.wordpiece_tokenizer.tokenize(token)
              self.cache[token] = subtokens
          split_tokens.extend(subtokens)
  
          # for sub_token in self.wordpiece_tokenizer.tokenize(token):
          #     split_tokens.append(sub_token)
  
      return split_tokens
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import re
  import unicodedata
  import six
  import tensorflow
  import sys
label_desc: Use image node_id 2 for calling the FullTokenizer obj's underlying member method code with example usage: obj.tokenize(text) and returns: split_tokens