steps_per_epoch=7500 // batch_size,
validation_steps=2500 // batch_size,
callbacks=[tensorboard_callback])
for images, labels in ds_train.take(1): # only take first element of dataset
images_ex = ep.astensors(images)
labels_ex = ep.astensors(labels)
fmodel = fb.TensorFlowModel(baseline_model, bounds=(0, 1))
attacks = [
fa.FGSM(),
fa.LinfPGD(),
fa.LinfBasicIterativeAttack(),
fa.LinfAdditiveUniformNoiseAttack(),
fa.LinfDeepFoolAttack(),
]
attacks_names = [
"FGSM", "LinfPGD", "LinfBasicIterativeAttack",
"LinfAdditiveUniformNoiseAttack", "LinfDeepFoolAttack"
]
epsilons = [
0.0, 0.0005, 0.001, 0.0015, 0.002, 0.003, 0.005, 0.01, 0.02, 0.03, 0.1,
0.3, 0.5, 1.0
]
transfer_methods = [
#"Transfer With Last Layer",
#"Transfer With No Last Layer",
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(
fa.GaussianBlurAttack(steps=10, max_sigma=224.0),
uses_grad=True,
requires_real_model=True,
),
AttackTestTarget(fa.L2DeepFoolAttack(steps=50, loss="logits"),
uses_grad=True),
AttackTestTarget(fa.L2DeepFoolAttack(steps=50, loss="crossentropy"),
uses_grad=True),
AttackTestTarget(fa.LinfDeepFoolAttack(steps=50), uses_grad=True),
AttackTestTarget(fa.BoundaryAttack(steps=50)),
AttackTestTarget(
fa.BoundaryAttack(
steps=110,
init_attack=fa.LinearSearchBlendedUniformNoiseAttack(steps=50),
update_stats_every_k=1,
)),
AttackTestTarget(fa.SaltAndPepperNoiseAttack(steps=50),
None,
uses_grad=True),
AttackTestTarget(fa.SaltAndPepperNoiseAttack(steps=50, channel_axis=1),
None,
uses_grad=True),
AttackTestTarget(fa.LinearSearchBlendedUniformNoiseAttack(steps=50), None),
AttackTestTarget(fa.L2AdditiveGaussianNoiseAttack(), 2500.0),
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,
),
None,
False,
False,
),
(fa.SaltAndPepperNoiseAttack(steps=50), None, True, False),
(fa.SaltAndPepperNoiseAttack(steps=50, channel_axis=1), None, True, False),
(fa.LinearSearchBlendedUniformNoiseAttack(steps=50), None, False, False),
(fa.L2AdditiveGaussianNoiseAttack(), 2500.0, False, False),
