1c8990edea80ea31b78618fb4e8ab01396edc95b,art/attacks/iterative_method.py,BasicIterativeMethod,generate,#BasicIterativeMethod#Any#,72

Before Change

                noise = projection(adv_x - x, self.eps, self.norm)
                adv_x = x + noise

        adv_preds = np.argmax(self.classifier.predict(adv_x), axis=1)
        if self.targeted:
            rate = np.sum(adv_preds == target_labels) / adv_x.shape[0]
        else:
            rate = np.sum(adv_preds != target_labels) / adv_x.shape[0]
        logger.info("Success rate of BIM attack: %.2f%%", rate)

        return adv_x

After Change

            if self._project:
                noise = projection(adv_x - x, self.eps, self.norm)
                adv_x = x + noise

        logger.info("Success rate of BIM attack: %.2f%%",
                    100 * compute_success(self.classifier, x, targets, adv_x, self.targeted))

        return adv_x

Instances