From 2f5bd103dd82968cc042e10bc914d8b1bacc5a0a Mon Sep 17 00:00:00 2001 From: Svetlana Karslioglu Date: Thu, 13 Oct 2022 15:54:32 -0700 Subject: [PATCH] Update fgsm_tutorial.py Added a comma --- beginner_source/fgsm_tutorial.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/beginner_source/fgsm_tutorial.py b/beginner_source/fgsm_tutorial.py index c2b05600e1e..69b7f2e9964 100644 --- a/beginner_source/fgsm_tutorial.py +++ b/beginner_source/fgsm_tutorial.py @@ -17,7 +17,7 @@ machine learning. You may be surprised to find that adding imperceptible perturbations to an image *can* cause drastically different model performance. Given that this is a tutorial, we will explore the topic -via example on an image classifier. Specifically we will use one of the +via example on an image classifier. Specifically, we will use one of the first and most popular attack methods, the Fast Gradient Sign Attack (FGSM), to fool an MNIST classifier.