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@baggepinnen I think for Hessians, it would make sense to always default to sparse computations (when activated, I would keep the LBFGS approximation as the default)? Should it be pure ForwardDiff, or mixed mode?
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If your problems are reaasonably small, pure-ForwardDiff sparse Hessians are not a bad idea.
Otherwise you'd have to combine backends, and that's where it gets tricky:
ReverseDiff only remains alloc-free in the absence of constants
Zygote is of course not alloc-free, nor does it support mutation
Mooncake and Enzyme don't work as inner backends for ForwardDiff
Pure-Enzyme sparse Hessians would also be an option but at the moment they're not so optimized, and there are still bugs I don't understand with respect to DI.Cache in second-order Enzyme
@baggepinnen I think for Hessians, it would make sense to always default to sparse computations (when activated, I would keep the LBFGS approximation as the default)? Should it be pure ForwardDiff, or mixed mode?
The text was updated successfully, but these errors were encountered: