Comments (3)
Thanks, @dpo
Then MadNLP should always query nnz information from nlp.meta
. @dlcole3 feel free to create a PR for the fix and adding this to MadNLPTest
from madnlp.jl.
even madnlp(nls)
doesn't work, and it seems that the issue is caused by
get_nnzj(nls) != get_nnzj(nls.meta)
@dpo @abelsiqueira is this an expected behavior? If a solver wants to solve NLS problem as a generic NLP, does the solver need to query nnzj
and nnzh
from nls.meta
, not nls
?
from madnlp.jl.
@sshin23 get_nnzj(nls)
is the same as get_nnzj(nls.nls_meta)
, which should return the number of nonzeros in the Jacobian of the residual:
https://github.com/JuliaSmoothOptimizers/NLPModels.jl/blob/main/src/nls/tools.jl#L11
By contrast, get_nnzj(nls.meta)
would return the number of nonzeros in the Jacobian of the constraints (not counting bound constraints), if your NLSModel had any. In addition, nnzj was recently split into lin_nnzj and nln_nnzj (linear/nonlinear constraints).
from madnlp.jl.
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