code: def test_FeatureUnion():
      """Test FeatureUnion fit_transform."""
      X, y = load_gunpoint(return_X_y=True)
      feature_union = FeatureUnion(
          [("mean", mean_transformer), ("std", std_transformer)]
      )
      Xt = feature_union.fit_transform(X, y)
      assert Xt.shape == (
          X.shape[0],
          X.shape[1] * len(feature_union.transformer_list),
      )
  
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 2 for calling a global function with example usage: test_FeatureUnion() without return types