How to use the torchfcn.models.FCN32s.download function in torchfcn

# https://github.com/shelhamer/fcn.berkeleyvision.org
    parser.add_argument(
        '--max-iteration', type=int, default=100000, help='max iteration'
    )
    parser.add_argument(
        '--lr', type=float, default=1.0e-12, help='learning rate',
    )
    parser.add_argument(
        '--weight-decay', type=float, default=0.0005, help='weight decay',
    )
    parser.add_argument(
        '--momentum', type=float, default=0.99, help='momentum',
    )
    parser.add_argument(
        '--pretrained-model',
        default=torchfcn.models.FCN32s.download(),
        help='pretrained model of FCN32s',
    )
    args = parser.parse_args()

    args.model = 'FCN16s'
    args.git_hash = git_hash()

    now = datetime.datetime.now()
    args.out = osp.join(here, 'logs', now.strftime('%Y%m%d_%H%M%S.%f'))

    os.makedirs(args.out)
    with open(osp.join(args.out, 'config.yaml'), 'w') as f:
        yaml.safe_dump(args.__dict__, f, default_flow_style=False)

    os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu)
    cuda = torch.cuda.is_available()