code: def test_spacy_intent_featurizer(
      spacy_nlp_component: SpacyNLP, spacy_model: SpacyModel
  ):
      td = loading.load_data("data/examples/rasa/demo-rasa.json")
      spacy_nlp_component.process_training_data(td, spacy_model)
      spacy_featurizer = create_spacy_featurizer({})
      spacy_featurizer.process_training_data(td)
  
      intent_features_exist = np.array(
          [
              True
              if example.get("intent_features") is not None
              else False
              for example in td.intent_examples
          ]
      )
  
      # no intent features should have been set
      assert not any(intent_features_exist)
  
imports: from typing import Any, Dict, Text
  import numpy
  import pytest
  from rasa.nlu.utils.spacy_utils import SpacyModel, SpacyNLP
  from rasa.shared.nlu.training_data import loading
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
  from rasa.nlu.featurizers.dense_featurizer.spacy_featurizer import SpacyFeaturizer
  from rasa.nlu.constants import SPACY_DOCS
  from rasa.shared.nlu.constants import TEXT, INTENT, RESPONSE
label_desc: Use image node_id 5 for calling a global function with example usage: test_spacy_intent_featurizer(spacy_nlp_component, spacy_model) without return types