Hi, when I try to change the dataset Cityscapes to a binary segmentation, the cross_entropy loss seems not work well with the binary mask,

Blockquote
File “source_only.py”, line 126, in main
lr_scheduler, epoch, visualize if args.debug else None, args)
File “source_only.py”, line 188, in train
loss_cls_s = criterion(pred_s, label_s)
File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 889, in _call_impl
result = self.forward(*input, **kwargs)
File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/loss.py”, line 1048, in forward
ignore_index=self.ignore_index, reduction=self.reduction)
File “/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py”, line 2693, in cross_entropy
return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction)
File “/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py”, line 2390, in nll_loss
ret = torch._C._nn.nll_loss2d(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
RuntimeError: only batches of spatial targets supported (3D tensors) but got targets of dimension: 4

and if I change it to BCEloss,

Blockquote
File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/loss.py”, line 613, in forward
return F.binary_cross_entropy(input, target, weight=self.weight, reduction=self.reduction)
File “/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py”, line 2755, in binary_cross_entropy
“Please ensure they have the same size.”.format(target.size(), input.size())
ValueError: Using a target size (torch.Size([2, 256, 512, 3])) that is different to the input size (torch.Size([2, 19, 256, 512])) is deprecated. Please ensure they have the same size.

it goes wrong with the channels, even I  set the num_class from 19 to 2.
I have no idea, any guidance will be so helpful!