def make_deepfool(sess, env, X_data, epochs=1, eps=0.01, batch_size=128):
"""
Generate FGSM by running env.xadv.
"""
print('\nMaking adversarials via FGSM')
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)
adv = sess.run(env.xadv, feed_dict={env.x: X_data[start:end],
env.adv_epochs: epochs})
X_adv[start:end] = adv
print()
return X_adv
deepfool_mnist.py 文件源码
python
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