def METHOD_NAME():
    class DummyNB301SurrogateModel:
        def predict(config, representation):
            return 96.0
    spec = (((0, 6), (1, 4), (0, 0), (1, 5), (1, 4), (3, 2), (0, 6), (3, 2)),
            ((0, 1), (1, 4), (0, 1), (1, 4), (2, 6), (3, 4), (1, 5), (2, 1)))
    data = {}
    data[spec] = {
        'runtime': [float(t * 100) for t in range(1, 99)],
        'train_losses': [float(l / 10) for l in range(98, 0, -1)],
        'val_accuracies': [float(i) for i in range(1, 99)]
    }
    api = {
        'nb301_arches': [spec],
        'nb301_model': DummyNB301SurrogateModel(),
        'nb301_data': data,
    }
    return api