adversarial.rst

Advanced

The :class:`Adversarial` class provides an advanced way to specify the adversarial example that should be found by an attack and provides detailed information about the created adversarial. In addition, it provides a way to improve a previously found adversarial example by re-running an attack.

Implicit

model = TensorFlowModel(images, logits, bounds=(0, 255))
criterion = TargetClassProbability('ostrich', p=0.99)
attack = LBFGSAttack(model, criterion)

Running the attack by passing image and label will implicitly create an :class:`Adversarial` instance. By passing unpack=False we tell the attack to return the :class:`Adversarial` instance rather than the actual image.

adversarial = attack(image, label=label, unpack=False)

We can then get the actual image using the :attr:`image` attribute:

adversarial_image = adversarial.image

Explicit

model = TensorFlowModel(images, logits, bounds=(0, 255))
criterion = TargetClassProbability('ostrich', p=0.99)
attack = LBFGSAttack()

We can also create the :class:`Adversarial` instance ourselves and then pass it to the attack.

adversarial = Adversarial(model, criterion, image, label)
attack(adversarial)

Again, we can get the image using the :attr:`image` attribute:

adversarial_image = adversarial.image

This approach gives us more flexibility and allows us to specify a different distance measure:

distance = MeanAbsoluteDistance
adversarial = Adversarial(model, criterion, image, label, distance=distance)