b88d36cd9c8056e15607a40f5d10a9072ab84b22,train_vidreid_xent.py,,main,#,87

Before Change

    print("Initializing model: {}".format(args.arch))
    model = models.init_model(name=args.arch, num_classes=dataset.num_train_pids, loss={"xent"})
    print("Model size: {:.5f}M".format(sum(p.numel() for p in model.parameters())/1000000.0))

    criterion = CrossEntropyLabelSmooth(num_classes=dataset.num_train_pids, use_gpu=use_gpu)
    optimizer = init_optim(args.optim, model.parameters(), args.lr, args.weight_decay)

After Change

    scheduler = lr_scheduler.MultiStepLR(optimizer, milestones=args.stepsize, gamma=args.gamma)
    start_epoch = args.start_epoch

    if args.fixbase_epoch > 0:
        optimizer_tmp = init_optim(args.optim, model.classifier.parameters(), args.fixbase_lr, args.weight_decay)

    if args.resume:
        print("Loading checkpoint from "{}"".format(args.resume))
        checkpoint = torch.load(args.resume)
        model.load_state_dict(checkpoint["state_dict"])

Instances