def get_args_parser()

in main_linear.py [0:0]

• 45 lines of code
• 1 McCabe index (conditional complexity)

def get_args_parser():
    parser = argparse.ArgumentParser(description='Linear probe evaluation', add_help=False)
    parser.add_argument('--dataset', default='imagenet', help='dataset name')
    parser.add_argument('--output-dir', default='./', type=str)
    parser.add_argument('-a', '--arch', metavar='ARCH', default='vit_base_patch16_224',
                        help='model architecture: (default: ViT-B/16)')
    parser.add_argument('-j', '--workers', default=64, type=int, metavar='N',
                        help='number of data loading workers (default: 64)')
    parser.add_argument('--epochs', default=90, type=int, metavar='N',
                        help='number of total epochs to run')
    parser.add_argument('--start-epoch', default=0, type=int, metavar='N',
                        help='manual epoch number (useful on restarts)')
    parser.add_argument('-b', '--batch-size', default=128, type=int,
                        metavar='N',
                        help='number of samples per-device/per-gpu ')
    parser.add_argument('--lr', '--learning-rate', default=0.1, type=float,
                        metavar='LR', help='initial (base) learning rate', dest='lr')
    parser.add_argument('--momentum', default=0.9, type=float, metavar='M',
                        help='momentum')
    parser.add_argument('--wd', '--weight-decay', default=0., type=float,
                        metavar='W', help='weight decay (default: 0.)',
                        dest='weight_decay')
    parser.add_argument('-p', '--print-freq', default=10, type=int,
                        metavar='N', help='print frequency (default: 10)')
    parser.add_argument('--eval-freq', default=10, type=int)
    parser.add_argument('--resume', default='', type=str, metavar='PATH',
                        help='path to latest checkpoint (default: none)')
    parser.add_argument('-e', '--evaluate', dest='evaluate', action='store_true',
                        help='evaluate model on validation set')
    parser.add_argument('--world-size', default=1, type=int,
                        help='number of nodes for distributed training')
    parser.add_argument('--rank', default=0, type=int,
                        help='node rank for distributed training')
    parser.add_argument("--local_rank", type=int, default=0)
    parser.add_argument('--dist-url', default='env://', type=str,
                        help='url used to set up distributed training')
    parser.add_argument('--dist-backend', default='nccl', type=str,
                        help='distributed backend')
    parser.add_argument('--seed', default=None, type=int,
                        help='seed for initializing training. ')
    parser.add_argument('--gpu', default=None, type=int,
                        help='GPU id to use.')
    parser.add_argument('--pretrained', default='', type=str,
                        help='path to CLIP pretrained checkpoint')
    return parser