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[AUTO] JuliaFormatter.jl run #210

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Merged
merged 1 commit into from
Sep 10, 2025
Merged

[AUTO] JuliaFormatter.jl run #210

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7 changes: 6 additions & 1 deletion src/RegularizedOptimization.jl
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Expand Up @@ -8,7 +8,12 @@ using Arpack, ProximalOperators

# dependencies from us
using LinearOperators,
ManualNLPModels, NLPModels, NLPModelsModifiers, RegularizedProblems, ShiftedProximalOperators, SolverCore
ManualNLPModels,
NLPModels,
NLPModelsModifiers,
RegularizedProblems,
ShiftedProximalOperators,
SolverCore
using Percival: AugLagModel, update_y!, update_μ!

const callback_docstring = "
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2 changes: 1 addition & 1 deletion src/TRDH_alg.jl
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Expand Up @@ -190,7 +190,7 @@ function TRDH(
selected::AbstractVector{<:Integer} = 1:length(x0),
kwargs...,
) where {R <: Real, F, G, H, DQN <: AbstractDiagonalQuasiNewtonOperator, X}
nlp = NLPModel(x0, f, grad=∇f!)
nlp = NLPModel(x0, f, grad = ∇f!)
reg_nlp = RegularizedNLPModel(nlp, h, selected)
stats = TRDH(
reg_nlp;
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6 changes: 4 additions & 2 deletions src/TR_alg.jl
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Expand Up @@ -59,7 +59,9 @@ function TRSolver(
shifted(reg_nlp.h, xk, l_bound_m_x, u_bound_m_x, reg_nlp.selected) :
shifted(reg_nlp.h, xk, T(1), χ)

Bk = isa(reg_nlp.model, QuasiNewtonModel) ? hess_op(reg_nlp.model, xk) : hess_op!(reg_nlp.model, xk, similar(xk))
Bk =
isa(reg_nlp.model, QuasiNewtonModel) ? hess_op(reg_nlp.model, xk) :
hess_op!(reg_nlp.model, xk, similar(xk))
sub_nlp = R2NModel(Bk, ∇fk, zero(T), x0) #FIXME
subpb = RegularizedNLPModel(sub_nlp, ψ)
substats = RegularizedExecutionStats(subpb)
Expand Down Expand Up @@ -341,7 +343,7 @@ function SolverCore.solve!(
set_radius!(solver.subsolver.ψ, ∆_effective)
set_radius!(ψ, ∆_effective)
end
with_logger(subsolver_logger) do
with_logger(subsolver_logger) do
if isa(solver.subsolver, TRDHSolver) #FIXME
solver.subsolver.D.d[1] = 1/ν₁
solve!(
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19 changes: 12 additions & 7 deletions test/test_allocs.jl
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Expand Up @@ -42,21 +42,26 @@ end
# Test non allocating solve!
@testset "allocs" begin
for (h, h_name) ∈ ((NormL0(λ), "l0"),)
for (solver, solver_name) ∈ ((:R2Solver, "R2"), (:R2DHSolver, "R2DH"), (:R2NSolver, "R2N"), (:TRDHSolver, "TRDH"), (:TRSolver, "TR"))
for (solver, solver_name) ∈ (
(:R2Solver, "R2"),
(:R2DHSolver, "R2DH"),
(:R2NSolver, "R2N"),
(:TRDHSolver, "TRDH"),
(:TRSolver, "TR"),
)
@testset "$(solver_name)" begin
(solver_name == "R2N" || solver_name == "TR") && continue #FIXME
reg_nlp = RegularizedNLPModel(LBFGSModel(bpdn), h)
solver = eval(solver)(reg_nlp)
stats = RegularizedExecutionStats(reg_nlp)
solver_name == "R2" && @test @wrappedallocs(
solve!(solver, reg_nlp, stats, ν = 1.0, atol = 1e-6, rtol = 1e-6)
) == 0
solver_name == "R2" &&
@test @wrappedallocs(solve!(solver, reg_nlp, stats, ν = 1.0, atol = 1e-6, rtol = 1e-6)) ==
0
solver_name == "R2DH" && @test @wrappedallocs(
solve!(solver, reg_nlp, stats, σk = 1.0, atol = 1e-6, rtol = 1e-6)
) == 0
solver_name == "TRDH" && @test @wrappedallocs(
solve!(solver, reg_nlp, stats, atol = 1e-6, rtol = 1e-6)
) == 0
solver_name == "TRDH" &&
@test @wrappedallocs(solve!(solver, reg_nlp, stats, atol = 1e-6, rtol = 1e-6)) == 0
@test stats.status == :first_order
end
end
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