Jacobian-Free Krylov Versions for TR/LM/GN #282
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Codecov ReportAttention:
Additional details and impacted files@@ Coverage Diff @@
## master #282 +/- ##
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+ Coverage 49.06% 94.04% +44.97%
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Files 19 20 +1
Lines 1824 1896 +72
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+ Hits 895 1783 +888
+ Misses 929 113 -816 ☔ View full report in Codecov by Sentry. |
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@ChrisRackauckas this is good to go on my end |
| __init_JᵀJ(J::StaticArray) = MArray{Tuple{size(J, 2), size(J, 2)}, eltype(J)}(undef) | ||
| __init_JᵀJ(J::Number, args...; kwargs...) = zero(J), zero(J) | ||
| function __init_JᵀJ(J::AbstractArray, fu, args...; kwargs...) | ||
| JᵀJ = J' * J |
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what is actually using this?
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None of the algorithms by default. But if LM/GN/TR is forced to use a Linear Solve which only works with square matrices then this needs to be triggered.
| end | ||
| autodiff = __concrete_vjp_autodiff(vjp_autodiff, jvp_autodiff, uf) | ||
| Jᵀ = VecJac(uf, u; fu, autodiff) | ||
| JᵀJ_op = SciMLOperators.cache_operator(Jᵀ * J, u) |
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This operator shouldn't need to be constructed.
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without doing the cache thing, it complained that for in place operations we need to run set the cache (something along those lines)
u. Should we allocate 2 caches? Inefficient for factorizations where we want to reuse factorization. How do we prevent the aliasingFixes #167