code: def test_perfect_model():
      # Arrange
      model = PerfectModel()
      data = pd.DataFrame(
          data={
              "target": [1, 2, 1, 2, 3],
              "col1": ["a", "b", "a", "a", "c"],
          }
      )
      model.fit([], data["target"])
      # Act
      p = model.predict(data[["col1"]])
      proba = model.predict_proba(data[["col1"]])
      # Assert
      assert_that(p.tolist(), contains_exactly(1, 2, 1, 2, 3))
      expected_proba = np.array(
          [[1, 0, 0], [0, 1, 0], [1, 0, 0], [0, 1, 0], [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 2 for calling a global function with example usage: test_perfect_model() without return types