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尝试使用unet模型训练pytorch模型（初学者）Im，我将图像输入作为输入，并随同将标签输入作为输入图像蒙版并在其上转换数据集。我从其他地方获得了unet模型，我将交叉熵损失用作损失函数，但是我得到的尺寸超出了范围误差，

    `RuntimeError                              Traceback (most recent call last)
<ipython-input-358-fa0ef49a43ae> in <module>()
     16 for epoch in range(0, num_epochs):
     17     # train for one epoch
---> 18     curr_loss = train(train_loader, model, criterion, epoch, num_epochs)
     19 
     20     # store best loss and save a model checkpoint

<ipython-input-356-1bd6c6c281fb> in train(train_loader, model, criterion, epoch, num_epochs)
     16         # measure loss
     17         print (outputs.size(),labels.size())
---> 18         loss = criterion(outputs, labels)
     19         losses.update(loss.data[0], images.size(0))
     20 

/usr/local/lib/python3.5/dist-packages/torch/nn/modules/module.py in     _ _call__(self, *input, **kwargs)
    323         for hook in self._forward_pre_hooks.values():
    324             hook(self, input) …