# zero the parameter gradients
        optimizer.zero_grad()
        # forward + backward + optimize
        outputs = net(inputs)
        loss = criterion(outputs, labels)
        loss.backward()
        optimizer.step()

optimizer.zero_grad()意思是把梯度置零，也就是把loss关于weight的导数变成0.