kwargs = {'num_workers': 1, 'pin_memory': True} if args.cuda else {}
train_loader = torch.utils.data.DataLoader(datasets.MNIST(args.data_dir,
train=True,
download=True,
transform=transform),
batch_size=args.batch_size,
shuffle=False,
**kwargs)
"""
test_loader = torch.utils.data.DataLoader(
datasets.MNIST(args.data_dir, train=False, transform=transform),
batch_size=args.batch_size, shuffle=False, **kwargs)
"""
test_set_path = os.path.join(args.adv_ex_dir, 'Random_Test_%s_.p' % ('mnist'))
test_loader = torch.utils.data.DataLoader(custom_datasets.Adv(
filename=test_set_path, transp=True),
batch_size=args.batch_size,
shuffle=False,
**kwargs)
random_loader = torch.utils.data.DataLoader(
custom_datasets.RandomMNIST(transform=transform),
batch_size=args.batch_size,
shuffle=False,
**kwargs)
list_advs = ["fgsm", "bim-a", "bim-b", "jsma", "cw-l2"]
# List of attacks, copy from run_search
dataset = 'mnist'
list_adv_loader = []
transforms.Normalize((0.5, 0.5, 0.5),
(1.0,1.0,1.0))])
kwargs = {'num_workers': 1, 'pin_memory': True} if args.cuda else {}
train_loader = torch.utils.data.DataLoader(
datasets.CIFAR10(args.data_dir, train=True, download=True, transform=transform),
batch_size=args.batch_size, shuffle=True, **kwargs)
"""
test_loader = torch.utils.data.DataLoader(
datasets.CIFAR10(args.data_dir, train=False, transform=transform),
batch_size=args.batch_size, shuffle=False, **kwargs)
"""
test_set_path = os.path.join(args.adv_ex_dir,'Random_Test_%s_.p' % ('cifar'))
test_loader = torch.utils.data.DataLoader(
custom_datasets.Adv(filename=test_set_path, transp=True),
batch_size=args.batch_size, shuffle=False, **kwargs)
"""
random_loader = torch.utils.data.DataLoader(
custom_datasets.RandomCIFAR10(args.data_dir, transform=transform),
batch_size=args.batch_size, shuffle=False, **kwargs)
"""
list_advs = ["adapt-fgsm", "cw-fp"] # ['fgsm']
# List of attacks, copy from run_search
dataset = 'cifar'
list_adv_loader=[]
for advs in list_advs:
attack_file = os.path.join(args.adv_ex_dir, 'Adv_%s_%s.p' % (dataset, advs))
# FGSM attack is already shifted/normalized
adv_loader= torch.utils.data.DataLoader(
custom_datasets.Adv(filename=attack_file, transp=True),