4441480fde64e42a9c4af205bf2ab8003511172e,cifar.py,,train,#Any#,122

Before Change

            inputs, targets, indexes = inputs.cuda(), targets.cuda(), indexes.cuda()
        optimizer.zero_grad()

        inputs, targets, indexes = Variable(inputs), Variable(targets), Variable(indexes)
        features = net(inputs)
        outputs = lemniscate(features, indexes)
        loss = criterion(outputs, indexes)

After Change

        loss.backward()
        optimizer.step()

        train_loss.update(loss.item(), inputs.size(0))

        // measure elapsed time
        batch_time.update(time.time() - end)

Instances