code: def test_cross_val_score(X, y, group_numbers):
      cv_args = {"test_size": 1, "train_size": 3}
      cv = GroupTimeSeriesSplit(**cv_args)
  
      expected_scores = np.array([0, 0.5, 0.25])
      clf = DummyClassifier(strategy="most_frequent")
      scoring = "accuracy"
      cv_scores = cross_val_score(
          clf, X, y, groups=group_numbers, scoring=scoring, cv=cv
      )
  
      assert np.array_equal(cv_scores, expected_scores)
  
imports: import numpy
  import pytest
  from sklearn.dummy import DummyClassifier
  from sklearn.model_selection import cross_val_score
  from mlxtend.evaluate import GroupTimeSeriesSplit
label_desc: Use image node_id 32 for calling a global function with example usage: test_cross_val_score(X, y, group_numbers) without return types