Optimise test time

Signed-off-by: Beat Buesser <[email protected]>

Author: beat-buesser

tests/defences/trainer/test_adversarial_trainer_oaat_pytorch.py

@@ -69,10 +69,10 @@ def _get_adv_trainer_oaat():
                 classifier,
                 norm=np.inf,
                 eps=0.2,
-                eps_step=0.02,
-                max_iter=20,
+                eps_step=0.01,
+                max_iter=5,
                 targeted=False,
-                num_random_init=1,
+                num_random_init=0,
                 batch_size=16,
                 verbose=False,
             )
@@ -120,7 +120,7 @@ def test_adversarial_trainer_oaat_pytorch_fit_and_predict(get_adv_trainer_oaat,
     else:
         accuracy = np.sum(predictions == y_test_mnist) / x_test_mnist.shape[0]
 
-    trainer.fit(x_train_mnist, y_train_mnist, nb_epochs=5, batch_size=16)
+    trainer.fit(x_train_mnist, y_train_mnist, nb_epochs=10, batch_size=16)
     predictions_new = np.argmax(trainer.predict(x_test_mnist), axis=1)
 
     if label_format == "one_hot":
@@ -170,7 +170,7 @@ def test_adversarial_trainer_oaat_pytorch_fit_generator_and_predict(
     else:
         accuracy = np.sum(predictions == y_test_mnist) / x_test_mnist.shape[0]
 
-    trainer.fit_generator(generator=generator, nb_epochs=10)
+    trainer.fit_generator(generator=generator, nb_epochs=5)
     predictions_new = np.argmax(trainer.predict(x_test_mnist), axis=1)
 
     if label_format == "one_hot":