1 optimizer.zero_grad()
2 logit = model(feature)
3 loss = F.cross_entropy(logit, target)
4 loss.backward()
5 # clip gradients
6 utils.clip_grad_norm(model.parameters(), 1e-4)
7 optimizer.step()