class TrainingConfig(TrainingConfigBase):
abs_current_path = os.path.realpath('./')
root_path = os.path.join('/', *abs_current_path.split(os.path.sep)[:-3])
lib_dir = os.path.join(root_path, 'lib')
num_epochs = 105
eval_interval = 15
weight_decay = 5e-4
inner_iters = 3
K = 5
sigma = 2 / 255.0
eps = 8 / 255.0
create_optimizer = SGDOptimizerMaker(lr=1e-1 * 2 / K,
momentum=0.9,
weight_decay=5e-4)
create_lr_scheduler = PieceWiseConstantLrSchedulerMaker(
milestones=[55, 75, 95], gamma=0.1)
create_loss_function = torch.nn.CrossEntropyLoss
create_attack_method = None
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 = 0
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_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]))
class TrainingConfing(TrainingConfigBase):
lib_dir = lib_dir
num_epochs = 36
val_interval = 0
weight_decay = 5e-4
inner_iters = 3
K = 5
sigma = 2 / 255.0
eps = 8 / 255.0
create_optimizer = SGDOptimizerMaker(lr=1e-1 * 4 / K,
momentum=0.9,
weight_decay=5e-4)
create_lr_scheduler = PieceWiseConstantLrSchedulerMaker(
milestones=[30, 34, 36], 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_attack_method = None
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]))