Nicholai Mitchko

@Kearm apologies, typing from my phone. I'll test later tonight.

zero_index = (unique_vals == 0).nonzero()
zero_count = temp_counts[zero_index]

@lmg-anon @Kearm , the code snippet should be fixed above. I was confusing what torch.unique returned.

The unique function will return the values and their counts. zero_index in the above snippets points to the counts tensor. In the counts tensor we can compare that against a previous iteration.

And thinking through this code, there's got to be a better way to check if two sets of activation tensors overlap, and pick the ones that overlap the least.

https://stackoverflow.com/a/62407582/1813580

@Kearm I was talking about @nmitchko 's code snippet

@Kearm and @lmg-anon want to try the update (i'm away from my cluster so can't test the code at the moment) I changed the original post.

Actually the code probably still doesn't work