Open neumannjan opened 1 year ago
Or does torch.Module
preserve this automatically? If yes, then this most definitely has to be part of the Module itself, not the dataset.
This is a reference to the same code, but in the latest commit as of right now:
I'm not sure how to move this to torch.Module, but it should be somehow serialized there with the rest of the model.
If we do an evaluation right after training (in the same run), then we are fine for now.
https://github.com/LukasZahradnik/deep-db-learning/blob/43e21b53b334c7fc3b4e0e699192d0a3ed3affac/db_transformer/ndata/convertor/cat_convertor.py#L24-L26
The above most definitely cannot survive across executions, e.g. from training to evaluation. The embedding vectors would get assigned to the actual values in an arbitrary order, given by the order in which the values are requested. However, we need this order to be ensured to be the exact the same for the same model every time, which this definitely doesn't do.