Upload app.py

app.py

@@ -122,7 +122,7 @@ def iterative_least_likely_fgsm_cifar10(image, model, epsilon, alpha, niter, nb_
     return adv_x.numpy()
 
 def fn(dataset, attack):
-    epsilon=10/255
+    epsilon=5/255
     alpha=1
     niter = int(min(4 + epsilon*255, 1.25 * epsilon * 255))
     nb_classes = 10
@@ -148,7 +148,6 @@ def fn(dataset, attack):
         image1 = X_test_cifar10[idx]
         label1 = Y_test_cifar10[idx]
         pred1 = classes[np.argmax(label1)]
-        print(pred1)
         if attack == "FGSM":
             image2 = fgsm_cifar10(image1, label1, model_cifar10, epsilon)
         elif attack == "I_FGSM":
@@ -157,7 +156,6 @@ def fn(dataset, attack):
             image2 = iterative_least_likely_fgsm_cifar10(image1, model_cifar10, epsilon, alpha, niter, nb_classes)
         
         pred2 = classes[np.argmax(model_cifar10(image2.reshape((1,32,32,3))))]
-        print(pred2)
         image1 = image1.reshape((32,32,3))
         image2 = image2.reshape((32,32,3))