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Same problem here. I am using a completely different dataset for audio processing. I extracted the S4ND and S4 layers into a different neural network architecture and I also got NaN after one epoch because the self.log_dt in SSKernelNPLR is nan. This must have happened during backpropagation because it is not updated otherwise (I believe)?
Sorry for not responding to this. I don't know why this is happening. I haven't revisited these experiments in a long time, but I'm quite confident that they were reproducible in the past. Perhaps something has changed in the libraries or perhaps there are some numerical issues on certain hardware
First of all, thank you for the comprehensive code base for all variants of S4 models.
However, as I try to run the Listops experiments with S4 (HYYT version), the losses for train, test and val all become nan after 1 epoch.
I ran the following script:
python -m train experiment=lra/s4-listops wandb=null
The final accuracy is also way below the reported accuracy (train=0.17).
Is there something that I have done wrong..?
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