code: def test_clipping_y_transformer():
      """Test clipping transformer on y of singletask dataset."""
      n_samples = 10
      n_features = 3
      n_tasks = 1
      ids = np.arange(n_samples)
      X = np.zeros((n_samples, n_features))
      y = np.ones((n_samples, n_tasks))
      target = 5.0 * y
      y *= 6.0
      w = np.ones((n_samples, n_tasks))
      dataset = dc.data.NumpyDataset(X, y, w, ids)
      transformer = dc.trans.ClippingTransformer(
          transform_y=True, y_max=5.0
      )
      clipped_dataset = transformer.transform(dataset)
      X_t, y_t, w_t, ids_t = (
          clipped_dataset.X,
          clipped_dataset.y,
          clipped_dataset.w,
          clipped_dataset.ids,
      )
      # Check ids are unchanged.
      for id_elt, id_t_elt in zip(ids, ids_t):
          assert id_elt == id_t_elt
      # Check X is unchanged since this is a y transformer
      np.testing.assert_allclose(X, X_t)
      # Check w is unchanged since this is a y transformer
      np.testing.assert_allclose(w, w_t)
      # Check y is now holding the proper values when sorted.
      np.testing.assert_allclose(y_t, target)
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_clipping_y_transformer() without return types