Comments (1)
pkofod
commented on June 16, 2024
Well, it's not meant to be light weight. It provides AD as one if its features for Optim and NLsolve and LsqFit. However, if you look at NLSolvers.jl which is the new backend code for Optim, you will see that I specifically left out AD for this reason. Then, Optim will include AD and NLSolvers.jl will not. So if you really need something cheap, you can use NLSolvers.jl
from nlsolversbase.jl.
Related Issues (20)
- link to julianlsolvers fails HOT 1
- [doc] explicit definition of arguments HOT 8
- non-modifying fg HOT 13
- Complex-valued gradients broken HOT 7
- Joint Hessian and Jacobian evaluation using the TwiceDifferentiable type HOT 1
- Add option to specify ForwardDiff chunk size HOT 4
- Extending autodiff compatibilities HOT 4
- Himmelblau references in README.md HOT 2
- TagBot trigger issue HOT 7
- allow using other array types in TwiceOrderDifferentiable finite differences HOT 3
- Surprising runtime behaviour with objective types HOT 2
- Message from JET HOT 1
- Is there any documentation?
- sparse AD on OnceDifferentiableConstraints and TwiceDifferentiableConstraints
- Why are`f_calls`, `df_calls` and `h_calls` all `Vector{Int}`? HOT 1
- Precompiling NLSolversBase for Julia v 1.0.0 fails. HOT 4
- 1.0 development HOT 2
- Higher dimensionnal Hessian HOT 2
- Incorrect initialization of derivative storage HOT 3
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from nlsolversbase.jl.