Towards a cleaner and more maintainable internals of NonlinearSolve.jl #203
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Can we setup a PDE benchmark before merging this so we know that the change is not a performance regression? It shouldn't be, but it would be good to know that the new sparse diff stuff is on par in performance with the setup we had before. |
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You mean in SciMLBenchmarks? |
Codecov Report
@@ Coverage Diff @@
## master #203 +/- ##
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+ Coverage 94.42% 94.94% +0.52%
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Files 7 8 +1
Lines 699 732 +33
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+ Hits 660 695 +35
+ Misses 39 37 -2
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| autodiff = if iip && (ls.autodiff isa AutoZygote || ls.autodiff isa AutoSparseZygote) | ||
| @warn "Attempting to use Zygote.jl for linesearch on an in-place problem. Falling back to finite differencing." | ||
| AutoFiniteDiff() |
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why not fallback to ForwardDiff if it's being used elsewhere?
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I wanted to use VecJac, which doesn't have the forwarddiff yet (I think?). See https://github.com/JuliaDiff/SparseDiffTools.jl/blob/04810f5caea10633504ad44071f1a6b82cb9bb5a/src/differentiation/vecjac_products.jl#L51-L52
I can fix it upstream to just construct jacobian and then multiply, and then change the default here later
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Needs SciML/DiffEqBase.jl#926 |
Fixes #195 #158 #140 #63
ADTypes-- constructs the ADType from the old argument style!TODOs:
resid_prototypeto properly constructfu(Add resid_prototype to NonlinearFunction SciMLBase.jl#490)Holding Off Merge till we have some upstream benchmarks