code: def tokenize(self, token):
      chars = list(token)
      if len(chars) > self.max_input_chars_per_word:
          return [self.unk_token]
  
      start = 0
      sub_tokens = []
      while start < len(chars):
          end = len(chars)
          cur_substr = None
          while start < end:
              substr = "".join(chars[start:end])
              if substr in self.vocab:
                  cur_substr = substr
                  break
              end -= 1
          if cur_substr is None:
              sub_tokens.append(self.unk_token)
              start += 1
          else:
              sub_tokens.append(cur_substr)
              start = end
  
      return sub_tokens
  
imports: import collections
  import os
  from typing import List, Optional, Tuple
  from transformers.utils import is_jieba_available, requires_backends
  from ...tokenization_utils import PreTrainedTokenizer
  from ...utils import logging
label_desc: Use image node_id 2 for calling the WordpieceTokenizer obj's underlying member method code with example usage: obj.tokenize(token) and returns: sub_tokens, list