If you would like to use the weight as a class weight, I assume you have a binary target, i.e. it contains only zeros and ones.
In that case I would create a weight tensor and just multiply it with your unreduces loss. Here is a small example:
weight = torch.tensor([0.1, 0.9])
weight_ = weight[y.data.view(-1).long()].view_as(y)
criterion = nn.BCELoss(reduce=False)
loss = criterion(output, y)
loss_class_weighted = loss * weight_
loss_class_weighted = loss_class_weighted.mean()

Let me know, if that works for you.