d031df60072b9be0cc5032b480a69fbd8abea5ea,pointnet2/train/train_cls.py,,,#,69

Before Change

        start_epoch, best_loss = pt_utils.load_checkpoint(
            model, optimizer, filename=args.checkpoint.split(".")[0])

        lr_scheduler = lr_sched.LambdaLR(
            optimizer, lr_lambda=lr_lbmd, last_epoch=start_epoch)
        bnm_scheduler = pt_utils.BNMomentumScheduler(
            model, bn_lambda=bn_lbmd, last_epoch=start_epoch)
    else:
        lr_scheduler = lr_sched.LambdaLR(optimizer, lr_lambda=lr_lbmd)

After Change

    if args.checkpoint is not None:
        checkpoint_status = pt_utils.load_checkpoint(
            model, optimizer, filename=args.checkpoint.split(".")[0])
        if checkpoint_status is not None:
            it, start_epoch, best_loss = checkpoint_status
        
    lr_scheduler = lr_sched.LambdaLR(
        optimizer, lr_lambda=lr_lbmd, last_epoch=it)
    bnm_scheduler = pt_utils.BNMomentumScheduler(
        model, bn_lambda=bn_lbmd, last_epoch=it)

Instances