def METHOD_NAME(model):
    model.eval()
    avg_acc = [[], []]
    for batch_id, data in enumerate(test_reader):
        img = paddle.to_tensor(data[0])
        img = paddle.reshape(img, [-1, 1, 28, 28])
        label = paddle.to_tensor(data[1])
        label = paddle.reshape(label, [-1, 1])
        out = model(img)
        acc_top1 = paddle.metric.accuracy(input=out, label=label, k=1)
        acc_top5 = paddle.metric.accuracy(input=out, label=label, k=5)
        avg_acc[0].append(acc_top1.numpy())
        avg_acc[1].append(acc_top5.numpy())
        if batch_id % 100 == 0:
            _logger.info(
                "Test | step {}: acc1 = {:}, acc5 = {:}".format(
                    batch_id, acc_top1.numpy(), acc_top5.numpy()))
    _logger.info("Test | Average: acc_top1 {}, acc_top5 {}".format(
        np.mean(avg_acc[0]), np.mean(avg_acc[1])))
    return np.mean(avg_acc[0]), np.mean(avg_acc[1])