class TrainingConfing(TrainingConfigBase):
lib_dir = lib_dir
num_epochs = 105
val_interval = 5
create_optimizer = SGDOptimizerMaker(lr=5e-2,
momentum=0.9,
weight_decay=5e-4)
create_lr_scheduler = PieceWiseConstantLrSchedulerMaker(
milestones=[75, 90, 100], gamma=0.1)
create_loss_function = torch.nn.CrossEntropyLoss
create_attack_method = \
IPGDAttackMethodMaker(eps = 8/255.0, sigma = 2/255.0, nb_iters = 10, norm = np.inf,
mean = torch.tensor(np.array([0]).astype(np.float32)[np.newaxis, :, np.newaxis, np.newaxis]),
std = torch.tensor(np.array([1]).astype(np.float32)[np.newaxis, :, np.newaxis, np.newaxis]))
create_evaluation_attack_method = \
IPGDAttackMethodMaker(eps = 8/255.0, sigma = 2/255.0, nb_iters = 20, norm = np.inf,
mean=torch.tensor(
np.array([0]).astype(np.float32)[np.newaxis, :, np.newaxis, np.newaxis]),
std=torch.tensor(np.array([1]).astype(np.float32)[np.newaxis, :, np.newaxis, np.newaxis]))
class TrainingConfing(TrainingConfigBase):
lib_dir = lib_dir
num_epochs = 40
val_interval = 1
weight_decay = 5e-4
inner_iters = 10
K = 5
sigma = 0.01
eps = 0.3
create_optimizer = SGDOptimizerMaker(lr=1e-2 / K,
momentum=0.9,
weight_decay=weight_decay)
create_lr_scheduler = PieceWiseConstantLrSchedulerMaker(
milestones=[30, 35, 39], gamma=0.1)
create_loss_function = None
# create_attack_method = None
create_attack_method = \
IPGDAttackMethodMaker(eps = 0.3, sigma = 0.01, nb_iters = 40, norm = np.inf,
mean = torch.tensor(np.array([0]).astype(np.float32)[np.newaxis, :, np.newaxis, np.newaxis]),
std = torch.tensor(np.array([1]).astype(np.float32)[np.newaxis, :, np.newaxis, np.newaxis]))
create_evaluation_attack_method = \
IPGDAttackMethodMaker(eps = 0.3, sigma = 0.01, nb_iters = 40, norm = np.inf,
mean=torch.tensor(
np.array([0]).astype(np.float32)[np.newaxis, :, np.newaxis, np.newaxis]),
std=torch.tensor(np.array([1]).astype(np.float32)[np.newaxis, :, np.newaxis, np.newaxis]))