code: def __init__(self, config, *args, **kwargs):
      try:
          from transformers3 import BertTokenizer
      except ImportError:
          from transformers import BertTokenizer
  
      if isinstance(config, str):
          config = {"from_pretrained": config}
  
      from_pretrained_name = config.get(
          "from_pretrained", "bert-base-uncased"
      )
      kwargs_dict = dict(
          kwargs, do_lower_case="uncased" in from_pretrained_name
      )
      self._tokenizer = BertTokenizer.from_pretrained(
          from_pretrained_name, **kwargs_dict
      )
      self._max_seq_length = config.get("max_seq_length", 25)
      self._probability = config.get("mask_probability", 0)
  
imports: import copy
  import random
  from typing import Any, Dict, List, Optional, Tuple, Union
  import torch
  from mmf.common.registry import registry
  from mmf.common.sample import Sample, SampleList
  from mmf.datasets.processors.processors import BaseProcessor
label_desc: Use image node_id 1 to create a new VILTTextTokenizer object from inherited base classes: MaskedTokenProcessor with example: obj = VILTTextTokenizer(config)