I run the deeplabv3+ on cityscapes dataset, in the training I run the following code:
for cur_step, (images, labels) in enumerate( train_loader ):
if scheduler is not None:
scheduler.step()
#images is ([8,3,512,512]) tensor, labels is  ([8,512,512]) tensor, 8 is the batch_size
images = images.to(device, dtype=torch.float32)
labels = labels.to(device, dtype=torch.long)
print( np.unique(labels.cpu().numpy()) )
# N, C, H, W
optim.zero_grad()
#outputs is ([8,20,512,512]) tensor, 20 is class num
outputs = model(images)
#criterion is Cross Entropy Loss
loss = criterion(outputs, labels)
loss.backward()
optim.step()
in the above code, I got the error
IMG_0118.JPG3264×2448 2.31 MB

I think the bug is in the " loss = criterion(outputs, labels)", but I dont know how to fix it