def __init__(self, pgd_alpha: float = 1.0, pgd_epsilon: float = 8.0, pgd_iteration: int = 8,
stop_conf: float = 0.9,
magnet: bool = False, randomized_smooth: bool = False, curvature: bool = False, **kwargs):
super().__init__(**kwargs)
self.param_list['pgd'] = ['pgd_alpha', 'pgd_epsilon', 'pgd_iteration']
self.pgd_alpha: float = pgd_alpha
self.pgd_epsilon: float = pgd_epsilon
self.pgd_iteration: int = pgd_iteration
self.pgd = PGD_Optimizer(alpha=self.pgd_alpha / 255, epsilon=self.pgd_epsilon / 255,
iteration=self.pgd_iteration)
self.stop_conf: float = stop_conf
if magnet:
self.magnet: MagNet = MagNet(dataset=self.dataset, pretrain=True)
self.randomized_smooth: bool = randomized_smooth
if curvature:
self.curvature: Curvature = Curvature(model=self.model)
def __init__(self, pgd_alpha: float = 1.0, pgd_eps: float = 8.0, pgd_iter: int = 8,
stop_conf: float = 0.9,
magnet: bool = False, randomized_smooth: bool = False, curvature: bool = False, **kwargs):
super().__init__(**kwargs)
self.param_list['pgd'] = ['pgd_alpha', 'pgd_eps', 'pgd_iter']
self.pgd_alpha: float = pgd_alpha
self.pgd_eps: float = pgd_eps
self.pgd_iter: int = pgd_iter
self.pgd = PGDoptimizer(pgd_alpha=self.pgd_alpha / 255, pgd_eps=self.pgd_eps / 255,
iteration=self.pgd_iter)
self.stop_conf: float = stop_conf
if magnet:
self.magnet: MagNet = MagNet(dataset=self.dataset, pretrained=True)
self.randomized_smooth: bool = randomized_smooth
if curvature:
from trojanvision.defenses.adv.curvature import Curvature
self.curvature = Curvature(model=self.model)
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.magnet = MagNet(dataset=self.dataset, pretrain=True)