Enable gpu for bound-constrained problems (#208)

* Remove constrained type in ForwardDiffADHvprod * Allow more generic type in constructor
JuliaSmoothOptimizers · Dec 22, 2023 · f1c03b1 · f1c03b1
1 parent d4c48d2
commit f1c03b1
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Showing 3 changed files with 4 additions and 4 deletions.
diff --git a/src/forward.jl b/src/forward.jl
@@ -182,8 +182,8 @@ struct ForwardDiffADHvprod{Tag, GT, S, T, F, Tagf} <: ADBackend
   lz::Vector{ForwardDiff.Dual{Tag, T, 1}}
   glz::Vector{ForwardDiff.Dual{Tag, T, 1}}
   sol::S
-  longv::S
-  Hvp::S
+  longv
+  Hvp
   ∇φ!::GT
   z::Vector{ForwardDiff.Dual{Tagf, T, 1}}
   gz::Vector{ForwardDiff.Dual{Tagf, T, 1}}

diff --git a/src/nlp.jl b/src/nlp.jl
@@ -21,7 +21,7 @@ ADNLPModel(
   adbackend::ADModelBackend,
   f,
   c,
-) where {T, S} = ADNLPModel(meta, counters, adbackend, f, Int[], Int[], T[], c)
+) where {T, S} = ADNLPModel(meta, counters, adbackend, f, Int[], Int[], similar(meta.x0, 0), c)
 
 ADNLPModels.show_header(io::IO, nlp::ADNLPModel) =
   println(io, "ADNLPModel - Model with automatic differentiation backend $(nlp.adbackend)")

diff --git a/src/nls.jl b/src/nls.jl
@@ -23,7 +23,7 @@ ADNLSModel(
   adbackend::ADModelBackend,
   F,
   c,
-) where {T, S} = ADNLSModel(meta, nls_meta, counters, adbackend, F, Int[], Int[], T[], c)
+) where {T, S} = ADNLSModel(meta, nls_meta, counters, adbackend, F, Int[], Int[], similar(meta.x0, 0), c)
 
 ADNLPModels.show_header(io::IO, nls::ADNLSModel) = println(
   io,