confidence=2.0), uses_grad=True, ), AttackTestTarget( fa.EADAttack(binary_search_steps=3, steps=20, decision_rule="L1", regularization=0), uses_grad=True, ), AttackTestTarget(fa.NewtonFoolAttack(steps=20), uses_grad=True), AttackTestTarget(fa.VirtualAdversarialAttack(steps=50, xi=1), 10, uses_grad=True), AttackTestTarget(fa.PGD(), Linf(1.0), uses_grad=True), AttackTestTarget(fa.L2PGD(), L2(50.0), uses_grad=True), AttackTestTarget(fa.L1PGD(), 5000.0, uses_grad=True), AttackTestTarget(fa.LinfBasicIterativeAttack(abs_stepsize=0.2), Linf(1.0), uses_grad=True), AttackTestTarget(fa.L2BasicIterativeAttack(), L2(50.0), uses_grad=True), AttackTestTarget(fa.L1BasicIterativeAttack(), 5000.0, uses_grad=True), AttackTestTarget(fa.SparseL1DescentAttack(), 5000.0, uses_grad=True), AttackTestTarget(fa.FGSM(), Linf(100.0), uses_grad=True), AttackTestTarget(FGSM_GE(), Linf(100.0)), AttackTestTarget(fa.FGM(), L2(100.0), uses_grad=True), AttackTestTarget(fa.L1FastGradientAttack(), 5000.0, uses_grad=True), AttackTestTarget(fa.GaussianBlurAttack(steps=10), uses_grad=True, requires_real_model=True), AttackTestTarget(
True, False, ), ( fa.EADAttack(binary_search_steps=3, steps=20, decision_rule="L1", regularization=0), None, True, False, ), (fa.NewtonFoolAttack(steps=20), None, True, False), (fa.VirtualAdversarialAttack(steps=50, xi=1), 10, True, False), (fa.PGD(), Linf(1.0), True, False), (fa.L2PGD(), L2(50.0), True, False), (fa.LinfBasicIterativeAttack(abs_stepsize=0.2), Linf(1.0), True, False), (fa.L2BasicIterativeAttack(), L2(50.0), True, False), (fa.FGSM(), Linf(100.0), True, False), (fa.FGM(), L2(100.0), True, False), (fa.GaussianBlurAttack(steps=10), None, True, True), (fa.GaussianBlurAttack(steps=10, max_sigma=224.0), None, True, True), (fa.L2DeepFoolAttack(steps=50, loss="logits"), None, True, False), (fa.L2DeepFoolAttack(steps=50, loss="crossentropy"), None, True, False), (fa.LinfDeepFoolAttack(steps=50), None, True, False), (fa.BoundaryAttack(steps=50), None, False, False), ( fa.BoundaryAttack( steps=110, init_attack=fa.LinearSearchBlendedUniformNoiseAttack(steps=50), update_stats_every_k=1,