Closed amontoison closed 6 days ago
@amontoison I keep this in my list. Could you rebase the branch?
@amontoison I keep this in my list. Could you rebase the branch?
@tmigot Done
@amontoison I took care of the ADNLPModel-stuff, just rest to fix hess_structure_residual!
and hess_coord_residual!
for sparse backend.
@amontoison I took care of the ADNLPModel-stuff, just rest to fix
hess_structure_residual!
andhess_coord_residual!
for sparse backend.
@tmigot I think we need to create the backend for residual_hessian
with different arguments (f(x) = 0
and c(x) = F(x)
).
You probably know how to fix that.
@tmigot Tu sais à quoi ça sert ces lignes? d37a9a1#diff-a1616586d29af268a473ea5c9c5ea6d09aa5f0de50e914a9d0bedc8d4f7bb59eR92-R99
C'est pour couvrir le cas où le "backend" fourni par l'utilisateur est un NLPModel. Mais définir cette fonction
function get_residual_nnzj(nlp::AbstractNLPModel, nvar, nequ)
nlp.nls_meta.nnzj
end
devrait être suffisant je pense.
@tmigot All tests passed for Hessian but we probably need to update the API for jth_hess_residual
.
Thanks for fixing it. I think the implementation in AD&NLPModels of jth_residual_hess is not clear so I removed the additional implementation (https://github.com/JuliaSmoothOptimizers/NLPModels.jl/issues/466). It should work now
@tmigot Can you help me with it?