Sorry, in that case I don’t know what might be causing this issue, as this code snippet successfully returns the default arguments:
def get_args():
    parser = argparse.ArgumentParser("parameters")

    parser.add_argument('--p', type=int, default=10, help='P being a parameter accounting for the fact that we expect only a few number of relevant classes to occur in each image. (default: 10)')
    parser.add_argument('--k', type=int, default=1000, help=', there is an important trade-off on K that strongly depends on the ratio K/M. (default: 1000)')
    parser.add_argument('--batch-size', type=int, default=100, help='batch size, (default: 100)')
    parser.add_argument('--input-size', type=tuple, default=(32, 32), help='input data size, (default: (32, 32))')
    parser.add_argument('--load-pretrained', type=bool, default=True)

    args = parser.parse_args()

    return args

args = get_args()
print(args)
> Namespace(batch_size=100, input_size=(32, 32), k=1000, load_pretrained=True, p=10)
print(args.load_pretrained)
> True

It seems that your current environment isn’t able to parse the arguments and based on this I would recommend to post the issue (without the PyTorch code) on e.g. StackOverflow.