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: Creates a new component (see parent class for full docstring).
docstr_tok: ["Creates","a","new","component","(","see","parent","class","for","full","docstring",")","."]
code: def create(
      cls,
      config: Dict[Text, Any],
      model_storage: ModelStorage,
      resource: Resource,
      execution_context: ExecutionContext,
  ) -> JiebaTokenizer:
      """Creates a new component (see parent class for full docstring)."""
      # Path to the dictionaries on the local filesystem.
      dictionary_path = config["dictionary_path"]
  
      if dictionary_path is not None:
          cls._load_custom_dictionary(dictionary_path)
      return cls(config, model_storage, 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 4 for calling the JiebaTokenizer obj's underlying member method code with example usage: obj.create(cls, config, model_storage, resource, execution_context) and returns: cls