54ff47e935ef0c79936bd7e3715674aca3b4f619,tutorials/mnist_tutorial_tf.py,,main,#Any#,24

Before Change

    model_2 = cnn_model()
    predictions_2 = model_2(x)
    fgsm2 = FastGradientMethod(model_2, sess=sess, params={"eps": 0.3})
    predictions_2_adv = model_2(fgsm2.generate(x))

    def evaluate_2():
        // Accuracy of adversarially trained model on legitimate test inputs
        eval_params = {"batch_size": FLAGS.batch_size}

After Change

    model_2 = cnn_model()
    predictions_2 = model_2(x)
    fgsm2 = FastGradientMethod(model_2, sess=sess)
    predictions_2_adv = model_2(fgsm2.generate(x, params={"eps": 0.3}))

    def evaluate_2():
        // Accuracy of adversarially trained model on legitimate test inputs
        eval_params = {"batch_size": FLAGS.batch_size}

Instances