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There are many possible tensor modifications that break DP guarantees.
We make a weak attempt to verify the model does not break any conventions (e.g. check for BatchNorm layers), but it's in no way comprehensive.
Is there a way to generalise such modification? Only allow certain operations? Use tensor hooks somehow. No answer yet, but interesting topic to explore
The text was updated successfully, but these errors were encountered:
One idea on how to approach this: functional testing.
Static analysis might prove very challenging, but running a batch and then comparing the results with individually-run examples looks easy. We do the same when unit-testing grad samplers, now we just need to package it differently and provide interface for clients
There are many possible tensor modifications that break DP guarantees.
We make a weak attempt to verify the model does not break any conventions (e.g. check for BatchNorm layers), but it's in no way comprehensive.
Is there a way to generalise such modification? Only allow certain operations? Use tensor hooks somehow. No answer yet, but interesting topic to explore
The text was updated successfully, but these errors were encountered: