| 40 | |
| 41 | |
| 42 | def parse_args(): |
| 43 | parser = argparse.ArgumentParser('argument for training') |
| 44 | |
| 45 | parser.add_argument('--batch-size', type=int, default=512, |
| 46 | help='batch_size') |
| 47 | parser.add_argument('--num-workers', type=int, default=10, |
| 48 | help='num of workers to use') |
| 49 | |
| 50 | parser.add_argument('--epochs', type=int, default=10, |
| 51 | help='number of training epochs') |
| 52 | parser.add_argument('--gpu', type=int, default=0, |
| 53 | help='gpu index used for training') |
| 54 | |
| 55 | # model dataset |
| 56 | parser.add_argument('--model', type=str, default='resnet18') |
| 57 | parser.add_argument('--load-pretrained', type=str, default='no') |
| 58 | parser.add_argument('--task', type=str, default='aia', |
| 59 | help='specify the attack task, mia or ol') |
| 60 | parser.add_argument('--dataset', type=str, default='CelebA', |
| 61 | help='dataset') |
| 62 | parser.add_argument('--data-path', type=str, default='../data/', |
| 63 | help='data_path') |
| 64 | parser.add_argument('--input-shape', type=str, default="32,32,3", |
| 65 | help='comma delimited input shape input') |
| 66 | parser.add_argument('--defense', type=str, default='No', |
| 67 | help='No, AdvTrain, Olympus, and AttriGuard') |
| 68 | parser.add_argument('--alpha', type=float, default='1.0', |
| 69 | help='The coef to balance defense methods') |
| 70 | # parser.add_argument('--model_save_path', type=str, default='./save/', help='data_path') |
| 71 | |
| 72 | args = parser.parse_args() |
| 73 | |
| 74 | args.input_shape = [int(item) for item in args.input_shape.split(',')] |
| 75 | args.device = 'cuda:%d' % args.gpu if torch.cuda.is_available() else 'cpu' |
| 76 | |
| 77 | return args |
| 78 | |
| 79 | |
| 80 | # target/shadow model |