code: def test_FeatureUnion_pipeline():
      """Test pipeline with FeatureUnion."""
      # pipeline with segmentation plus multiple feature extraction
  
      steps = [
          ("segment", RandomIntervalSegmenter(n_intervals=1)),
          (
              "transform",
              FeatureUnion(
                  [("mean", mean_transformer), ("std", std_transformer)]
              ),
          ),
          ("clf", DecisionTreeClassifier()),
      ]
      clf = Pipeline(steps)
      clf.fit(X_train, y_train)
      y_pred = clf.predict(X_test)
  
      assert y_pred.shape[0] == y_test.shape[0]
  
file_path: sktime/sktime/transformations/tests/test_pipeline.py
imports: import numpy
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import FeatureUnion, Pipeline
  from sklearn.preprocessing import FunctionTransformer
  from sklearn.tree import DecisionTreeClassifier
  from sktime.datasets import load_gunpoint
  from sktime.transformations.panel.segment import RandomIntervalSegmenter
  from sktime.transformations.series.adapt import TabularToSeriesAdaptor
  from sktime.utils._testing.panel import make_classification_problem
label_desc: Use image node_id 1 for calling a global function with example usage: test_FeatureUnion_pipeline() without return types