fix pep8 in mnist_tutorial_tf
@@ -124,9 +124,9 @@ def mnist_tutorial(train_start=0, train_end=60000, test_start=0,
# For the fgsm attack used in this tutorial, the attack has zero
# gradient so enabling this flag does not change the gradient.
# For some other attacks, enabling this flag increases the cost of
- # training, but gives the defender the ability to anticipate how the
- # atacker will change their strategy in response to updates to the
- # defender's parameters.
+ # training, but gives the defender the ability to anticipate how
+ # the atacker will change their strategy in response to updates to
+ # the defender's parameters.
adv_x = tf.stop_gradient(adv_x)
preds_adv = model.get_probs(adv_x)
