def METHOD_NAME():
    n_tasks = 5
    dataset, metric = get_dataset(mode="classification",
                                  featurizer="smiles2img",
                                  n_tasks=n_tasks)
    model = ChemCeption(n_tasks=n_tasks,
                        img_spec="engd",
                        model_dir=None,
                        mode="classification")
    model.fit(dataset, nb_epoch=300)
    scores = model.evaluate(dataset, [metric], [])
    assert scores['mean-roc_auc_score'] >= 0.9