code: def test_message_fingerprint_is_recalculated_after_setting_data():
      message = Message(data={TEXT: "This is a test sentence."})
      fp1 = message.fingerprint()
      message.set(INTENT, "test")
      fp2 = message.fingerprint()
      assert fp1 != fp2
  
file_path: rasa/tests/shared/nlu/training_data/test_message.py
imports: from typing import Optional, Text, List
  import pytest
  import numpy
  import scipy.sparse
  from rasa.shared.nlu.training_data.features import Features
  from rasa.shared.nlu.constants import TEXT, FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE, ACTION_TEXT, ACTION_NAME, INTENT, RESPONSE
  from rasa.shared.nlu.training_data.message import Message
  from rasa.nlu.tokenizers.whitespace_tokenizer import WhitespaceTokenizer
label_desc: Use image node_id 8 for calling a global function with example usage: test_message_fingerprint_is_recalculated_after_setting_data() without return types