code: def test_random_model():
      # Arrange
      model = RandomModel()
      y = pd.Series([1, 2, 1, 2, 3])
      x = np.ones(5)
      model.fit([], y)
      # Act
      np.random.seed(42)
      p = model.predict(x)
      np.random.seed(42)
      proba = model.predict_proba(x)
      # Assert
      assert_that(p.tolist(), contains_exactly(2, 3, 1, 3, 3))
      expected_proba = np.array(
          [[0, 1, 0], [0, 0, 1], [1, 0, 0], [0, 0, 1], [0, 0, 1]]
      )
      assert_that(np.equal(proba, expected_proba).sum(), is_(15))
  
imports: import numpy
  import pandas
  from hamcrest import assert_that, contains_exactly, is_
  from deepchecks.utils.simple_models import PerfectModel, RandomModel
label_desc: Use image node_id 1 for calling a global function with example usage: test_random_model() without return types