code: def test_predict_hard_voting():
      X = np.array([[1, 2, 3], [4, 5, 6]])
      y = np.array([0, 1])
  
      model1 = LogisticRegression(solver="liblinear")
      model2 = LogisticRegression(solver="lbfgs")
      model1.fit(X, y)
      model2.fit(X, y)
  
      clf = postprocessing.SimpleVoter(
          [("model1", model1), ("model2", model2)],
          voting="hard",
          classes=model1.classes_,
      )
      pred = clf.predict(X)
      assert np.allclose(pred, y)
  
label_desc: Use image node_id 3 for calling a global function with example usage: test_predict_hard_voting() without return types