32e4d362935db01ae4b3df9a6d8635b3da60cf64,train_vidreid_xent_htri.py,,train,#Any#Any#Any#Any#Any#Any#Any#Any#,144

Before Change

        
        outputs, features = model(imgs)
        if args.htri_only:
            if isinstance(features, (tuple, list)):
                loss = DeepSupervision(criterion_htri, features, pids)
            else:
                loss = criterion_htri(features, pids)

After Change

        batch_time.update(time.time() - end)

        xent_losses.update(xent_loss.item(), pids.size(0))
        htri_losses.update(htri_loss.item(), pids.size(0))
        accs.update(accuracy(outputs, pids)[0])

        if (batch_idx + 1) % args.print_freq == 0:

Instances