code: def test_jieba(text, expected_tokens, expected_indices):
      tk = create_jieba()
  
      tokens = tk.tokenize(Message(data={TEXT: text}), attribute=TEXT)
  
      assert [t.text for t in tokens] == expected_tokens
      assert [t.start for t in tokens] == [
          i[0] for i in expected_indices
      ]
      assert [t.end for t in tokens] == [i[1] for i in expected_indices]
  
file_path: rasa/tests/nlu/tokenizers/test_jieba_tokenizer.py
imports: import logging
  from typing import Dict, Optional
  from _pytest.logging import LogCaptureFixture
  from _pytest.tmpdir import TempPathFactory
  from rasa.engine.graph import ExecutionContext
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.tokenizers.jieba_tokenizer import JiebaTokenizer
  import pytest
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
  from rasa.nlu.constants import TOKENS_NAMES
  from rasa.shared.nlu.constants import TEXT, INTENT
label_desc: Use image node_id 2 for calling a global function with example usage: test_jieba(text, expected_tokens, expected_indices) without return types