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Ordinal regression models in PyTorch

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**RuntimeError: The size of tensor a (5) must match the size of tensor b (6) at non-singleton dimension 1** I'm working on a six classification task[0, 1, 2, 3, 4,...

Dear Torch friends Perhaps I am missing something, but I think the docs of "reduction_" function is not correct. Shall it be? ``` def _reduction(loss: torch.Tensor, reduction: str) -> torch.Tensor:...

Hi could u help understand the below peace of code. Why do we subtract the elements in linkmat ,then concatinating them . Isnt just cutpoints-X is sufficient ? ``` sigmoids=cutpoints-X...

```py class OrdinalLogisticModel(nn.Module): """ Parameters ---------- predictor : nn.Module When called, must return a torch.FloatTensor with shape [batch_size, 1] """ ``` hello , thank u for sharing! I have a...

Currently per-class weights are simply multiplied with the raw NLL loss, which skews the effective learning rate. They should be normalized by sum by default to avoid this: https://discuss.pytorch.org/t/the-value-of-weights-for-weighted-cross-entropy-should-be-normalized/190727