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sshin23 avatar sshin23 commented on June 16, 2024 1

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

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sshin23 avatar sshin23 commented on June 16, 2024

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?

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dpo avatar dpo commented on June 16, 2024

@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).

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