Pytorch:如何训练具有两个损失函数的网络？

import torch
import torch.nn as nn
import torch.optim as optim

class MyModel(nn.Module):
    def __init__(self):
        super(MyModel, self).__init__()
        # 定义网络结构

    def forward(self, x):
        # 定义前向传播过程
        return x

loss_function1 = nn.CrossEntropyLoss()
loss_function2 = nn.MSELoss()

optimizer = optim.SGD(model.parameters(), lr=0.001)

for epoch in range(num_epochs):
    for inputs, labels in dataloader:
        optimizer.zero_grad()
        outputs = model(inputs)
        loss1 = loss_function1(outputs, labels)
        loss2 = loss_function2(outputs, labels)
        total_loss = loss1 + loss2
        total_loss.backward()
        optimizer.step()