Function add_common_args

TinyViT/utils.py:15–54

(parser)

def add_common_args(parser):
    parser.add_argument('--cfg', type=str, required=True,
                        metavar="FILE", help='path to config file', )
    parser.add_argument(
        "--opts",
        help="Modify config options by adding 'KEY VALUE' pairs. ",
        default=None,
        nargs='+',
    )

    # easy config modification
    parser.add_argument('--batch-size', type=int,
                        help="batch size for single GPU")
    parser.add_argument('--data-path', type=str, help='path to dataset')
    parser.add_argument('--pretrained',
                        help='pretrained weight from checkpoint, could be imagenet22k pretrained weight')
    parser.add_argument('--resume', help='resume from checkpoint')
    parser.add_argument('--accumulation-steps', type=int,
                        help="gradient accumulation steps")
    parser.add_argument('--use-checkpoint', action='store_true',
                        help="whether to use gradient checkpointing to save memory")
    parser.add_argument('--disable_amp', action='store_true',
                        help='Disable pytorch amp')
    parser.add_argument('--output', default='output', type=str, metavar='PATH',
                        help='root of output folder, the full path is <output>/<model_name>/<tag> (default: output)')
    parser.add_argument('--tag', help='tag of experiment')
    parser.add_argument('--eval', action='store_true',
                        help='Perform evaluation only')
    parser.add_argument('--only-cpu', action='store_true',
                        help='Perform evaluation on CPU')
    parser.add_argument('--throughput', action='store_true',
                        help='Test throughput only')
    parser.add_argument('--use-sync-bn', action='store_true',
                        default=False, help='sync bn')
    parser.add_argument('--use-wandb', action='store_true',
                        default=False, help='use wandb to record log')

    # distributed training
    parser.add_argument("--local_rank", type=int,
                        help='local rank for DistributedDataParallel')


def load_checkpoint(config, model, optimizer, lr_scheduler, loss_scaler, logger):