code: def test_mul_sklearn_autoadapt():
      """Test auto-adapter for sklearn in mul."""
      RAND_SEED = 42
      X = _make_panel_X(
          n_instances=10, n_timepoints=12, random_state=RAND_SEED
      )
      X_test = X
  
      t1 = ExponentTransformer(power=2)
      t2 = StandardScaler()
      c = TimeSeriesDBSCAN(
          FlatDist.create_test_instance(), eps=4, min_samples=1
      )
  
      t12c_1 = t1 * (t2 * c)
      t12c_2 = (t1 * t2) * c
      t12c_3 = t1 * t2 * c
  
      assert isinstance(t12c_1, ClustererPipeline)
      assert isinstance(t12c_2, ClustererPipeline)
      assert isinstance(t12c_3, ClustererPipeline)
  
      y_pred = t12c_1.fit(X).predict(X_test)
  
      _assert_array_almost_equal(y_pred, t12c_2.fit(X).predict(X_test))
      _assert_array_almost_equal(y_pred, t12c_3.fit(X).predict(X_test))
  
file_path: sktime/sktime/clustering/compose/tests/test_pipeline.py
imports: from sklearn.preprocessing import StandardScaler
  from sktime.clustering.compose import ClustererPipeline
  from sktime.clustering.dbscan import TimeSeriesDBSCAN
  from sktime.dists_kernels import FlatDist
  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_panel_X
label_desc: Use image node_id 2 for calling a global function with example usage: test_mul_sklearn_autoadapt() without return types