def METHOD_NAME(model, train_dataiter, val_dataiter):
    # print logging by default
    logging.basicConfig(level=logging.DEBUG)
    console = logging.StreamHandler()
    console.setLevel(logging.DEBUG)
    logging.getLogger("").addHandler(console)
    model.fit(X=train_dataiter, eval_data=val_dataiter)
    logging.info("Finish fit...")
    prob = model.predict(val_dataiter)
    logging.info("Finish predict...")
    val_dataiter.reset()
    y = np.concatenate([batch.label[0].asnumpy() for batch in val_dataiter]).astype("int")
    py = np.argmax(prob, axis=1)
    acc1 = float(np.sum(py == y)) / len(y)
    logging.info("final accuracy = %f", acc1)
    assert acc1 > 0.94