code: def test_mitie(
      text: Text,
      expected_tokens: List[Text],
      expected_indices: List[Tuple[int, int]],
      tokenizer: Callable[[Dict[Text, Any]], MitieTokenizer],
  ):
      tk = tokenizer({})
  
      tokens = tk.tokenize(Message.build(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_mitie_tokenizer.py
imports: from typing import Dict, Text, Any, Tuple, List, Callable
  import pytest
  from rasa.engine.graph import ExecutionContext
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  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
  from rasa.nlu.tokenizers.mitie_tokenizer import MitieTokenizer
label_desc: Use image node_id 2 for calling a global function with example usage: test_mitie(text, expected_tokens, expected_indices, tokenizer) without return types