code: def test_dunder_mul():
      """Test the mul dunder method."""
      RAND_SEED = 42
      y = _make_classification_y(n_instances=10, random_state=RAND_SEED)
      X = _make_panel_X(
          n_instances=10, n_timepoints=20, random_state=RAND_SEED, y=y
      )
      X_test = _make_panel_X(
          n_instances=5, n_timepoints=20, random_state=RAND_SEED
      )
  
      t1 = ExponentTransformer(power=4)
      t2 = ExponentTransformer(power=0.25)
  
      c = KNeighborsTimeSeriesClassifier()
      t12c_1 = t1 * (t2 * c)
      t12c_2 = (t1 * t2) * c
      t12c_3 = t1 * t2 * c
  
      assert isinstance(t12c_1, ClassifierPipeline)
      assert isinstance(t12c_2, ClassifierPipeline)
      assert isinstance(t12c_3, ClassifierPipeline)
  
      y_pred = c.fit(X, y).predict(X_test)
  
      _assert_array_almost_equal(
          y_pred, t12c_1.fit(X, y).predict(X_test)
      )
      _assert_array_almost_equal(
          y_pred, t12c_2.fit(X, y).predict(X_test)
      )
      _assert_array_almost_equal(
          y_pred, t12c_3.fit(X, y).predict(X_test)
      )
  
file_path: sktime/sktime/classification/compose/tests/test_pipeline.py
imports: from sklearn.preprocessing import StandardScaler
  from sktime.classification.compose import ClassifierPipeline
  from sktime.classification.distance_based import KNeighborsTimeSeriesClassifier
  from sktime.transformations.panel.padder import PaddingTransformer
  from sktime.transformations.series.exponent import ExponentTransformer
  from sktime.transformations.series.impute import Imputer
  from sktime.utils._testing.estimator_checks import _assert_array_almost_equal
  from sktime.utils._testing.panel import _make_classification_y, _make_panel_X
label_desc: Use image node_id 1 for calling a global function with example usage: test_dunder_mul() without return types