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Inclusion of probability distributions (scope question)
Hi! Thanks for the awesome project -- a unified tensor interface is something that will help a lot of projects :)
I wanted to ask about the current/future scope of eagerpy
, specifically on the inclusion of probability distributions like in torch.distributions
, or tfp.distributions
? It seems like a more substantial project, and so may be more of a stand-alone effort, but I think this would be a great asset for people who want to keep fully agnostic to frameworks.
As an example, a project I work with (pyhf
) has it's own implementation of Tensor
that aims for essentially what eagerpy
does, but we also use it for probability distributions too within the module. This is done by wrapping around existing implementations and adding the extra math where needed -- my first impression with eagerpy
is that this may be better handled if there were stand-alone implementations of distributions using only eagerpy
tensors, but I'm not sure what the more practical option is.
Eager (hehe) to hear your thoughts!
I don't have any plans to add something like this, but I would certainly consider contributions in this direction.