class_docstr: This tokenizer is a wrapper for Jieba (https://github.com/fxsjy/jieba).
class_docstr_tok: ["This","tokenizer","is","a","wrapper","for","Jieba","(","https",":","\/\/github.com\/fxsjy\/jieba",")","."]
docstr: Initialize the tokenizer.
docstr_tok: ["Initialize","the","tokenizer","."]
code: def __init__(
      self,
      config: Dict[Text, Any],
      model_storage: ModelStorage,
      resource: Resource,
  ) -> None:
      """Initialize the tokenizer."""
      super().__init__(config)
      self._model_storage = model_storage
      self._resource = resource
  
imports: from __future__ import annotations
  import glob
  import logging
  import os
  import shutil
  from typing import Any, Dict, List, Optional, Text
  from rasa.engine.graph import ExecutionContext
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.tokenizers.tokenizer import Token, Tokenizer
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.training_data.training_data import TrainingData
label_desc: Use image node_id 3 to create a new JiebaTokenizer object from inherited base classes: Tokenizer with example: obj = JiebaTokenizer(config, model_storage, resource)