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Bump to NLPModels 0.21 #327

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Bump to NLPModels 0.21 #327

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a9daf33
Bump to NLPModels 0.21
tmigot May 17, 2024
840a6bb
Fix objcons counters
tmigot May 24, 2024
13c8e04
Update Project.toml
tmigot May 24, 2024
bf6e5f3
revert changes
tmigot Jun 24, 2024
a67330a
Update counters
tmigot Aug 13, 2024
1364cd8
Update test_julia.jl
tmigot Aug 13, 2024
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ CUTEst_jll = "=2.0.6"
Combinatorics = "1.0"
DataStructures = "0.17, 0.18"
JSON = "0.8, 0.9, 0.10, 0.11, 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.20, 0.21"
NLPModels = "0.18, 0.19, 0.20"
NLPModels = "0.18, 0.19, 0.20, ^0.21.1"
julia = "^1.6.0"

[extras]
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6 changes: 2 additions & 4 deletions src/julia_interface.jl
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Expand Up @@ -31,7 +31,6 @@ function NLPModels.objcons!(
f,
c,
)
increment!(nlp, :neval_cons)
else
ccall(
dlsym(cutest_lib, :cutest_ufn_),
Expand All @@ -44,6 +43,7 @@ function NLPModels.objcons!(
)
end
increment!(nlp, :neval_obj)
increment!(nlp, :neval_cons)
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Well, isn't this the source of the error? You're incrementing nevals_cons even on unconstrained problems.

More generally, this pull request is about bumping the NLPModels version, but it does other things. I suggest removing the other changes so we can isolate the problem (if any).

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This is part of the update to NLPModels 0.21. This was necessary to pass unit tests from NLPModelsTest that come along the new release.

Essentially, the idea is that we need to be consistent when calling cons! (and objcons!) on unconstrained problems.
I opened a new PR that updates link to better isolate the issue with the CI on macOS #328

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But what sense is there to incrementing neval_cons on an unconstrained problem?

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I think the discussion goes back to this: https://github.com/JuliaSmoothOptimizers/NLPModels.jl/blob/bfd4ceafec9ad6f58cbf11a4a88f2e61767ce701/src/nlp/api.jl#L60
If a user is calling cons! on an unconstrained problem, should we increment or not? Currently, we do.

@cutest_error

return f[1], c
Expand Down Expand Up @@ -133,9 +133,7 @@ end
function NLPModels.obj(nlp::CUTEstModel, x::AbstractVector)
@lencheck nlp.meta.nvar x
f = objcons!(nlp, x, nlp.work)[1]
if nlp.meta.ncon > 0
decrement!(nlp, :neval_cons) # does not really count as a constraint eval
end
decrement!(nlp, :neval_cons) # does not really count as a constraint eval
return f
end

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2 changes: 1 addition & 1 deletion test/test_julia.jl
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Expand Up @@ -141,7 +141,7 @@ function test_nlpinterface(nlp::CUTEstModel, comp_nlp::AbstractNLPModel)
else
@assert nlp.counters.neval_obj == 3
@assert nlp.counters.neval_grad == 3
@assert nlp.counters.neval_cons == 0
@assert nlp.counters.neval_cons == 1
@assert nlp.counters.neval_jac == 0
@assert nlp.counters.neval_jprod == 0
@assert nlp.counters.neval_jtprod == 0
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