How to handle unbalance data of multi-label classification?

It seems that ImageDataBunch cannot set the label weight since I am doing unbalanced multi-label classification problem. Is there any way to do it?

Additionally, I found binary_cross_entropy_with_logits is the default loss function for the multi-label problem, but I don’t know how to set the pos_weight parameter, it seems to be useful for label weight, I don’t know, I tried this:

learner = create_cnn(data=data, arch=arch, 

But I got an exception when I fit:

RuntimeError: TensorIterator expected type torch.DoubleTensor but got torch.cuda.FloatTensor

I changed to:

RuntimeError: TensorIterator expected type torch.FloatTensor but got torch.cuda.FloatTensor

So how to handle the unbalanced multi-label problem? Thanks much!


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