Prediction per timestamp about erpp-rmtpp HOT 2 OPEN

I also believe what you have stated is true (Reference lines 69 and 70 in model.py). For a sequence of length L, the model should train (and predict) the next timestamp and category for every subset sequence of length K (<L). I will raise a pull request for this soon.

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If you go through utils.py, you will notice that the dataloader consists of length seq_len. If there is a sequence of length L, the author utilizes all contiguous seq_len length sequences (possible only if seq_len <= L) in its training and testing, so each sequence in the data contributes (L-seq_len+1) sequences in the training and test data. What most other papers do is what I talked about above (predict next event for every subset sequence of length K (<L)).

from erpp-rmtpp.