eval_linear.py [80:98]:
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parser.add_argument("--dist_url", default="env://", type=str,
                    help="url used to set up distributed training")
parser.add_argument("--world_size", default=-1, type=int, help="""
                    number of processes: it is set automatically and
                    should not be passed as argument""")
parser.add_argument("--rank", default=0, type=int, help="""rank of this process:
                    it is set automatically and should not be passed as argument""")
parser.add_argument("--local_rank", default=0, type=int,
                    help="this argument is not used and should be ignored")


def main():
    global args, best_acc
    args = parser.parse_args()
    init_distributed_mode(args)
    fix_random_seeds(args.seed)
    logger, training_stats = initialize_exp(
        args, "epoch", "loss", "prec1", "prec5", "loss_val", "prec1_val", "prec5_val"
    )
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eval_semisup.py [74:92]:
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parser.add_argument("--dist_url", default="env://", type=str,
                    help="url used to set up distributed training")
parser.add_argument("--world_size", default=-1, type=int, help="""
                    number of processes: it is set automatically and
                    should not be passed as argument""")
parser.add_argument("--rank", default=0, type=int, help="""rank of this process:
                    it is set automatically and should not be passed as argument""")
parser.add_argument("--local_rank", default=0, type=int,
                    help="this argument is not used and should be ignored")


def main():
    global args, best_acc
    args = parser.parse_args()
    init_distributed_mode(args)
    fix_random_seeds(args.seed)
    logger, training_stats = initialize_exp(
        args, "epoch", "loss", "prec1", "prec5", "loss_val", "prec1_val", "prec5_val"
    )
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