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In #465, we implement RS2 sampling, which does not need any information from the forward pass. However, the actual training data in RS2 changes each epoch, which the selector currently does not support. We fitted the implementation to the downsampling case, but actually it might be better to extend the selector component to allow updating the TTS if no information from model forward pass is required, since the definition of downsampling more or less is using information from the forward pass.
The text was updated successfully, but these errors were encountered:
This implements the random selection from the [RS2
paper](https://openreview.net/pdf?id=JnRStoIuTe) minus the learning rate
scheduling adjustments.
Note that it is a bit suboptimal to use the downsampling infrastructure
here (#466). We might want to think about making the selector a bit more
dynamic, but for now, this will suffice to run experiments. #462 should
be merged before this is reviewed.
In #465, we implement RS2 sampling, which does not need any information from the forward pass. However, the actual training data in RS2 changes each epoch, which the selector currently does not support. We fitted the implementation to the downsampling case, but actually it might be better to extend the selector component to allow updating the TTS if no information from model forward pass is required, since the definition of downsampling more or less is using information from the forward pass.
The text was updated successfully, but these errors were encountered: