code: def test_DAG_transformer():
      """Tests the DAG transformer."""
      np.random.seed(123)
  
      # Load mini log-solubility dataset.
      current_dir = os.path.dirname(os.path.abspath(__file__))
      featurizer = dc.feat.ConvMolFeaturizer()
      tasks = ["outcome"]
      input_file = os.path.join(
          current_dir,
          "../../models/tests/assets/example_regression.csv",
      )
      loader = dc.data.CSVLoader(
          tasks=tasks, feature_field="smiles", featurizer=featurizer
      )
      dataset = loader.create_dataset(input_file)
      transformer = dc.trans.DAGTransformer(max_atoms=50)
      dataset = transformer.transform(dataset)
      # The transformer generates n DAGs for a molecule with n
      # atoms. These are denoted the "parents"
      for idm, mol in enumerate(dataset.X):
          assert dataset.X[idm].get_num_atoms() == len(
              dataset.X[idm].parents
          )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_DAG_transformer() without return types