🤖 Format .jl files

Author: dpo

src/AL_alg.jl

@@ -156,12 +156,20 @@ function ALSolver(reg_nlp::AbstractRegularizedNLPModel{T, V}; kwargs...) where {
   y = V(undef, ncon)
   has_bnds = has_bounds(nlp)
   sub_model = AugLagModel(nlp, V(undef, ncon), T(0), x, T(0), V(undef, ncon))
-  sub_problem = RegularizedNLPModel(sub_model, reg_nlp.h,reg_nlp.selected)
+  sub_problem = RegularizedNLPModel(sub_model, reg_nlp.h, reg_nlp.selected)
   sub_solver = R2Solver(reg_nlp; kwargs...)
   sub_stats = RegularizedExecutionStats(sub_problem)
   M = typeof(nlp)
   ST = typeof(sub_solver)
-  return ALSolver{T, V, M, typeof(sub_problem), ST}(x, cx, y, has_bnds, sub_problem, sub_solver, sub_stats)
+  return ALSolver{T, V, M, typeof(sub_problem), ST}(
+    x,
+    cx,
+    y,
+    has_bnds,
+    sub_problem,
+    sub_solver,
+    sub_stats,
+  )
 end
 
 @doc (@doc ALSolver) function AL(::Val{:equ}, reg_nlp::AbstractRegularizedNLPModel; kwargs...)

test/runtests.jl

@@ -1,7 +1,14 @@
 using LinearAlgebra: length
 using LinearAlgebra, Random, Test
 using ProximalOperators
-using ADNLPModels, OptimizationProblems, OptimizationProblems.ADNLPProblems, NLPModels, NLPModelsModifiers, RegularizedProblems, RegularizedOptimization, SolverCore
+using ADNLPModels,
+  OptimizationProblems,
+  OptimizationProblems.ADNLPProblems,
+  NLPModels,
+  NLPModelsModifiers,
+  RegularizedProblems,
+  RegularizedOptimization,
+  SolverCore
 
 const global compound = 1
 const global nz = 10 * compound