7b53af23f51fdffe2692962db410cf9ce6dc0512,scripts/classification/imagenet/train_imagenet.py,,train,#Any#Any#,161

Before Change

            with ag.record():
                outputs = [net(X) for X in data]
                loss = [L(yhat, y) for yhat, y in zip(outputs, label_smooth)]
            for l in loss:
                l.backward()
            trainer.step(batch_size)
            acc_top1.update(label, outputs)
            acc_top5.update(label, outputs)
            train_loss += sum([l.sum().asscalar() for l in loss])

After Change

            with ag.record():
                outputs = [net(X) for X in data]
                loss = [L(yhat, y) for yhat, y in zip(outputs, label_smooth)]
            ag.backward(loss)
            trainer.step(batch_size)
            acc_top1.update(label, outputs)
            acc_top5.update(label, outputs)
            train_loss += sum([l.sum().asscalar() for l in loss])

Instances