code: def test_calculate_cls_vector(
      pooling, features, only_non_zero_vectors, expected
  ):
      actual = DenseFeaturizer.aggregate_sequence_features(
          features,
          pooling_operation=pooling,
          only_non_zero_vectors=only_non_zero_vectors,
      )
      assert np.all(actual == expected)
  
file_path: rasa/tests/nlu/featurizers/test_featurizer.py
imports: from rasa.shared.exceptions import InvalidConfigException
  from rasa.nlu.featurizers.featurizer import Featurizer
  from rasa.nlu.constants import FEATURIZER_CLASS_ALIAS
  from typing import List, Dict, Any, Text
  import numpy
  import pytest
  from rasa.nlu.featurizers.dense_featurizer.dense_featurizer import DenseFeaturizer
label_desc: Use image node_id 1 for calling a global function with example usage: test_calculate_cls_vector(pooling, features, only_non_zero_vectors, expected) without return types