code: def __init__(
      self,
      vocab_file,
      do_lower_case=False,
      do_basic_tokenize=True,
      never_split=None,
      unk_token="<unk>",
      sep_token=None,
      pad_token="<pad>",
      cls_token=None,
      mask_token=None,
      space_token="<space>",
      tokenize_chinese_chars=True,
      strip_accents=None,
      **kwargs,
  ):
      super().__init__(
          vocab_file=vocab_file,
          do_lower_case=do_lower_case,
          do_basic_tokenize=do_basic_tokenize,
          never_split=never_split,
          unk_token=unk_token,
          sep_token=sep_token,
          pad_token=pad_token,
          cls_token=cls_token,
          mask_token=mask_token,
          tokenize_chinese_chars=tokenize_chinese_chars,
          strip_accents=strip_accents,
          **kwargs,
      )
  
      self._space_token = space_token
  
file_path: DeepKE/src/deepke/name_entity_re/cross/seq2seq/t5_bert_tokenizer.py
imports: import logging
  from typing import Optional, List
  from transformers import BertTokenizer
label_desc: Use image node_id 1 to create a new T5BertTokenizer object from inherited base classes: BertTokenizer with example: obj = T5BertTokenizer(vocab_file, do_lower_case, do_basic_tokenize, never_split, unk_token, sep_token, pad_token, cls_token, mask_token, space_token, tokenize_chinese_chars, strip_accents)