jsma_mnist_10x10.py 文件源码

def make_jsma(sess, env, X_data, epochs=0.2, eps=1.0, batch_size=128):
    """
    Generate JSMA by running env.x_jsma.
    """
    print('\nMaking adversarials via JSMA')

    n_sample = X_data.shape[0]
    n_batch = int((n_sample + batch_size - 1) / batch_size)
    X_adv = np.empty_like(X_data)

    for batch in range(n_batch):
        print(' batch {0}/{1}'.format(batch + 1, n_batch), end='\r')
        start = batch * batch_size
        end = min(n_sample, start + batch_size)
        feed_dict = {
            env.x: X_data[start:end],
            env.target: np.random.choice(n_classes),
            env.adv_epochs: epochs,
            env.adv_eps: eps}
        adv = sess.run(env.x_jsma, feed_dict=feed_dict)
        X_adv[start:end] = adv
    print()

    return X_adv