Check HEPAugFoldYielder and test-time augmentation

[GilesStrong]

One thing I've been surprised about is that increasing the amount of test-time data augmentation can sometimes decrease model performance. I would have thought that it would saturate, rather than decrease; all transformations result in valid events, unlike say in image augmentation where augmented data is only similar and things like Polyak averaging are useful.

I've been over the code in HEPAugFoldYielder multiple times and can't spot any errors, but a second set of eyes might help. There might also be errors in my assumptions about the input data...

If the code is correct, then it would be interesting to investigate further what causes the degradation in performance, and whether it is reproducible on other datasets.