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add is_subsolver field for TRDH #304

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add is_subsolver field for TRDH #304

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98beb5f
add is_subsolver field for TRDH
MaxenceGollier Mar 2, 2026
66a6913
add is_subsolver field for trdh constructor
MaxenceGollier Mar 2, 2026
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2 changes: 1 addition & 1 deletion src/LMTR_alg.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -70,7 +70,7 @@ function LMTRSolver(
sub_nlp = LMModel(Jk, Fk, T(0), xk)
subpb = RegularizedNLPModel(sub_nlp, ψ)
substats = RegularizedExecutionStats(subpb)
subsolver = subsolver(subpb)
subsolver = subsolver == TRDHSolver ? subsolver(subpb, is_subsolver = true) : subsolver(subpb)
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@dpo dpo Mar 11, 2026

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Let's call the result sub_solver. It's a bit confusing to overwrite the type with an instance...


return LMTRSolver{T, typeof(ψ), V, typeof(χ), typeof(subsolver), typeof(subpb)}(
xk,
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6 changes: 4 additions & 2 deletions src/TRDH_alg.jl
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Expand Up @@ -24,12 +24,14 @@ mutable struct TRDHSolver{
u_bound::V
l_bound_m_x::V
u_bound_m_x::V
is_subsolver::Bool
end

function TRDHSolver(
reg_nlp::AbstractRegularizedNLPModel{T, V};
D::Union{Nothing, AbstractDiagonalQuasiNewtonOperator} = nothing,
χ = NormLinf(one(T)),
is_subsolver = false,
) where {T, V}
x0 = reg_nlp.model.meta.x0
l_bound = reg_nlp.model.meta.lvar
Expand All @@ -46,7 +48,6 @@ function TRDHSolver(
dk = similar(x0)
has_bnds = any(l_bound .!= T(-Inf)) || any(u_bound .!= T(Inf))

is_subsolver = reg_nlp.h isa ShiftedProximableFunction # case TRDH is used as a subsolver
if is_subsolver
ψ = shifted(reg_nlp.h, xk)
@assert !has_bnds
Expand Down Expand Up @@ -87,6 +88,7 @@ function TRDHSolver(
u_bound,
l_bound_k,
u_bound_k,
is_subsolver,
)
end

Expand Down Expand Up @@ -275,7 +277,7 @@ function SolverCore.solve!(
χ = solver.χ
has_bnds = solver.has_bnds

is_subsolver = h isa ShiftedProximableFunction # case TRDH is used as a subsolver
is_subsolver = solver.is_subsolver

if has_bnds
l_bound_m_x, u_bound_m_x = solver.l_bound_m_x, solver.u_bound_m_x
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2 changes: 1 addition & 1 deletion src/TR_alg.jl
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Expand Up @@ -71,7 +71,7 @@ function TRSolver(
sub_nlp = R2NModel(Bk, ∇fk, zero(T), x0) #FIXME
subpb = RegularizedNLPModel(sub_nlp, ψ)
substats = RegularizedExecutionStats(subpb)
subsolver = subsolver(subpb)
subsolver = subsolver == TRDHSolver ? subsolver(subpb, is_subsolver = true) : subsolver(subpb)

return TRSolver(
xk,
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