3b15c8b78b15ff0aafb15240c7d160570b532efb,tutorials/mnist_tutorial_cw.py,,mnist_tutorial_cw,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,25

Before Change

    idxs = [np.where(np.argmax(Y_test,axis=1)==i)[0][0] for i in range(10)]
    adv_inputs = np.array([[x]*10 for x in X_test[idxs]], dtype=np.float32).reshape((100,28,28,1))
    adv_ys = np.array([onehot(range(10),10) for x in range(10)], dtype=np.float32).reshape((100,10))

    adv = sess.run(cw.generate(tf.constant(adv_inputs), tf.constant(adv_ys), **cw_params))

After Change

    // Check if we are using a GPU, and generate higher quality attacks if we are
    try:
        with tf.device("/gpu:0"):
            sess.run(tf.constant(1))
        gpu = True
    except:

Instances