[AUTO] JuliaFormatter.jl run

docs/api_reference.jl

@@ -130,7 +130,6 @@ function generate_api_reference(src_dir::String, ext_dir::String)
             title_in_menu="Solvers",
             filename="solvers",
         ),
-
     ]
 
     # ───────────────────────────────────────────────────────────────────

docs/make.jl

@@ -37,7 +37,7 @@ include("api_reference.jl")
 # Build documentation
 # ═══════════════════════════════════════════════════════════════════════════════
 with_api_reference(src_dir, ext_dir) do api_pages
-    makedocs(;
+    return makedocs(;
         draft=draft,
         remotes=nothing, # Disable remote links. Needed for DocumenterReference
         warnonly=true,

src/Modelers/abstract_modeler.jl

@@ -58,7 +58,7 @@ Build an NLP model from a discretized optimal control problem and initial guess.
 function (modeler::AbstractNLPModeler)(
     ::Optimization.AbstractOptimizationProblem, initial_guess
 )
-    throw(
+    return throw(
         Exceptions.NotImplemented(
             "Model building not implemented";
             required_method="(modeler::$(typeof(modeler)))(prob::Optimization.AbstractOptimizationProblem, initial_guess)",
@@ -87,7 +87,7 @@ Build a solution object from a discretized optimal control problem and NLP solut
 function (modeler::AbstractNLPModeler)(
     ::Optimization.AbstractOptimizationProblem, ::SolverCore.AbstractExecutionStats
 )
-    throw(
+    return throw(
         Exceptions.NotImplemented(
             "Solution building not implemented";
             required_method="(modeler::$(typeof(modeler)))(prob::Optimization.AbstractOptimizationProblem, nlp_solution::SolverCore.AbstractExecutionStats)",

src/Modelers/adnlp.jl

@@ -226,8 +226,8 @@ $(TYPEDSIGNATURES)
 Return the description for the ADNLP modeler.
 """
 function Strategies.description(::Type{<:Modelers.ADNLP})
-    "NLP modeler using ADNLPModels with automatic differentiation.\n" *
-    "See: https://jso.dev/ADNLPModels.jl"
+    return "NLP modeler using ADNLPModels with automatic differentiation.\n" *
+           "See: https://jso.dev/ADNLPModels.jl"
 end
 
 """

src/Modelers/exa.jl

@@ -61,7 +61,7 @@ and returns an appropriate CUDA backend.
 - Uses CUDA.CUDABackend() for GPU execution
 """
 function __get_cuda_backend(::Type{<:GPU})
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :CUDA;
             message="to use GPU backend with Exa modeler",
@@ -226,8 +226,8 @@ $(TYPEDSIGNATURES)
 Return the description for the Exa modeler.
 """
 function Strategies.description(::Type{<:Modelers.Exa})
-    "NLP modeler using ExaModels, supporting CPU and GPU execution.\n" *
-    "See: https://exanauts.github.io/ExaModels.jl"
+    return "NLP modeler using ExaModels, supporting CPU and GPU execution.\n" *
+           "See: https://exanauts.github.io/ExaModels.jl"
 end
 
 """

src/Modelers/validation.jl

@@ -27,7 +27,7 @@ See also: `validate_adnlp_backend(::Core.AbstractTag, ::Val{:default})`, `get_va
 """
 function validate_adnlp_backend(tag::Core.AbstractTag, backend::Val)
     # This is the generic fallback - should never be reached
-    throw(
+    return throw(
         Exceptions.IncorrectArgument(
             "Invalid ADNLPModels backend";
             got="backend=$(backend)",
@@ -85,7 +85,7 @@ Validate Enzyme backend using tag dispatch.
 See also: `validate_adnlp_backend(::Core.AbstractTag, ::Val{:zygote})`, `get_validate_adnlp_backend`
 """
 function validate_adnlp_backend(tag::Core.AbstractTag, ::Val{:enzyme})
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :Enzyme;
             message="to use Enzyme backend with ADNLP modeler",
@@ -115,7 +115,7 @@ Validate Zygote backend using tag dispatch.
 See also: `validate_adnlp_backend(::Core.AbstractTag, ::Val{:enzyme})`, `get_validate_adnlp_backend`
 """
 function validate_adnlp_backend(tag::Core.AbstractTag, ::Val{:zygote})
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :Zygote;
             message="to use Zygote backend with ADNLP modeler",
@@ -182,7 +182,7 @@ Fallback method for invalid base types in ExaModels validation.
 See also: `validate_exa_base_type(::Type{<:AbstractFloat})`
 """
 function validate_exa_base_type(T)
-    throw(
+    return throw(
         Exceptions.IncorrectArgument(
             "Invalid base type for Modelers.Exa";
             got="base_type=$T",
@@ -315,7 +315,7 @@ function validate_backend_override(backend)
     isa(backend, Type) && backend <: ADNLPModels.ADBackend && return backend
     # Accept an ADBackend instance (e.g., ForwardDiffADGradient())
     isa(backend, ADNLPModels.ADBackend) && return backend
-    throw(
+    return throw(
         Exceptions.IncorrectArgument(
             "Backend override must be nothing, a Type{<:ADBackend}, or an ADBackend instance";
             got=string(typeof(backend)),

src/Optimization/contract.jl

@@ -31,7 +31,7 @@ nlp = builder(initial_guess; show_time=false, backend=:optimized)
 See also: `get_exa_model_builder`, `build_model`
 """
 function get_adnlp_model_builder(prob::AbstractOptimizationProblem)
-    throw(
+    return throw(
         Exceptions.NotImplemented(
             "ADNLP model builder not implemented";
             required_method="get_adnlp_model_builder(prob::$(typeof(prob)))",
@@ -69,7 +69,7 @@ nlp = builder(Float64, initial_guess; backend=nothing, minimize=true)
 See also: `get_adnlp_model_builder`, `build_model`
 """
 function get_exa_model_builder(prob::AbstractOptimizationProblem)
-    throw(
+    return throw(
         Exceptions.NotImplemented(
             "ExaModel builder not implemented";
             required_method="get_exa_model_builder(prob::$(typeof(prob)))",
@@ -107,7 +107,7 @@ sol = builder(nlp_stats)
 See also: `get_exa_solution_builder`, `build_solution`
 """
 function get_adnlp_solution_builder(prob::AbstractOptimizationProblem)
-    throw(
+    return throw(
         Exceptions.NotImplemented(
             "ADNLP solution builder not implemented";
             required_method="get_adnlp_solution_builder(prob::$(typeof(prob)))",
@@ -145,7 +145,7 @@ sol = builder(nlp_stats)
 See also: `get_adnlp_solution_builder`, `build_solution`
 """
 function get_exa_solution_builder(prob::AbstractOptimizationProblem)
-    throw(
+    return throw(
         Exceptions.NotImplemented(
             "ExaSolution builder not implemented";
             required_method="get_exa_solution_builder(prob::$(typeof(prob)))",

src/Solvers/abstract_solver.jl

@@ -63,7 +63,7 @@ stats = solver(nlp, display=false)
 See also: `AbstractNLPSolver`, `CommonSolve.solve`
 """
 function (solver::AbstractNLPSolver)(nlp; display::Bool=true)
-    throw(
+    return throw(
         Exceptions.NotImplemented(
             "Solver callable not implemented";
             required_method="(solver::$(typeof(solver)))(nlp; display=Bool)",

src/Solvers/ipopt.jl

@@ -128,8 +128,8 @@ $(TYPEDSIGNATURES)
 Return the description for the Ipopt solver.
 """
 function Strategies.description(::Type{<:Solvers.Ipopt})
-    "Interior-point NLP solver (COIN-OR Ipopt).\n" *
-    "See: https://coin-or.github.io/Ipopt/OPTIONS.html"
+    return "Interior-point NLP solver (COIN-OR Ipopt).\n" *
+           "See: https://coin-or.github.io/Ipopt/OPTIONS.html"
 end
 
 """
@@ -229,7 +229,7 @@ See also: `Ipopt`, `Strategies.metadata`
 function build_ipopt_solver(
     ::Type{<:Core.AbstractTag}, parameter::Type{<:AbstractStrategyParameter}; kwargs...
 )
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :NLPModelsIpopt;
             message="to create Ipopt, access options, and solve problems",
@@ -254,7 +254,7 @@ See also: `Ipopt`, `Strategies.StrategyMetadata`
 """
 function Strategies.metadata(::Type{<:Solvers.Ipopt{P}}) where {P<:CPU}
     # Extension is missing
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :NLPModelsIpopt;
             message="to access Ipopt{$P} options metadata",

src/Solvers/knitro.jl

@@ -131,8 +131,8 @@ $(TYPEDSIGNATURES)
 Return the description for the Knitro solver.
 """
 function Strategies.description(::Type{<:Solvers.Knitro})
-    "Commercial NLP solver by Artelys (requires license).\n" *
-    "See: https://www.artelys.com/app/docs/knitro/3_referenceManual/userOptions.html"
+    return "Commercial NLP solver by Artelys (requires license).\n" *
+           "See: https://www.artelys.com/app/docs/knitro/3_referenceManual/userOptions.html"
 end
 
 """
@@ -232,7 +232,7 @@ See also: `Knitro`, `Strategies.metadata`
 function build_knitro_solver(
     ::Type{<:Core.AbstractTag}, parameter::Type{<:AbstractStrategyParameter}; kwargs...
 )
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :NLPModelsKnitro;
             message="to create Knitro, access options, and solve problems",
@@ -257,7 +257,7 @@ See also: `Knitro`, `Strategies.StrategyMetadata`
 """
 function Strategies.metadata(::Type{<:Solvers.Knitro{P}}) where {P<:CPU}
     # Extension is missing
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :NLPModelsKnitro;
             message="to access Knitro{$P} options metadata",

src/Solvers/madncl.jl

@@ -90,8 +90,8 @@ $(TYPEDSIGNATURES)
 Return the description for the MadNCL solver.
 """
 function Strategies.description(::Type{<:Solvers.MadNCL})
-    "Augmented Lagrangian NLP solver built on MadNLP.\n" *
-    "See: https://github.com/MadNLP/MadNCL.jl"
+    return "Augmented Lagrangian NLP solver built on MadNLP.\n" *
+           "See: https://github.com/MadNLP/MadNCL.jl"
 end
 
 """
@@ -189,7 +189,7 @@ See also: `MadNCL`, `Strategies.metadata`
 function build_madncl_solver(
     ::Type{<:Core.AbstractTag}, parameter::Type{<:AbstractStrategyParameter}; kwargs...
 )
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :MadNCL,
             :MadNLP;
@@ -216,7 +216,7 @@ See also: `MadNCL`, `Strategies.StrategyMetadata`
 function Strategies.metadata(
     ::Type{<:Solvers.MadNCL{P}}
 ) where {P<:AbstractStrategyParameter}
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :MadNCL,
             :MadNLP;

src/Solvers/madnlp.jl

@@ -96,8 +96,8 @@ $(TYPEDSIGNATURES)
 Return the description for the MadNLP solver.
 """
 function Strategies.description(::Type{<:Solvers.MadNLP})
-    "Interior-point NLP solver with sparse linear algebra and GPU support.\n" *
-    "See: https://madsuite.org/MadNLP.jl/stable/options/"
+    return "Interior-point NLP solver with sparse linear algebra and GPU support.\n" *
+           "See: https://madsuite.org/MadNLP.jl/stable/options/"
 end
 
 """
@@ -195,7 +195,7 @@ See also: `MadNLP`, `Strategies.metadata`
 function build_madnlp_solver(
     ::Type{<:Core.AbstractTag}, parameter::Type{<:AbstractStrategyParameter}; kwargs...
 )
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :MadNLP;
             message="to create MadNLP, access options, and solve problems",
@@ -221,7 +221,7 @@ See also: `MadNLP`, `Strategies.StrategyMetadata`
 function Strategies.metadata(
     ::Type{<:Solvers.MadNLP{P}}
 ) where {P<:AbstractStrategyParameter}
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :MadNLP;
             message="to access MadNLP{$P} options metadata",

src/Solvers/madnlpsuite.jl

@@ -25,7 +25,7 @@ Return the default linear solver for the given parameter type.
 - GPU implementation provided by CTSolversMadNLPGPU extension
 """
 function __madnlp_suite_default_linear_solver(::Type{<:GPU})
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :MadNLPGPU;
             message="to use GPU linear solver with MadNLP/MadNCL",

src/Solvers/uno.jl

@@ -157,8 +157,8 @@ $(TYPEDSIGNATURES)
 Return the description for the Uno solver.
 """
 function Strategies.description(::Type{<:Solvers.Uno})
-    "Unified modular NLP solver combining interior-point, SQP, trust-region and filter strategies.\n" *
-    "See: https://unosolver.readthedocs.io/en/latest/"
+    return "Unified modular NLP solver combining interior-point, SQP, trust-region and filter strategies.\n" *
+           "See: https://unosolver.readthedocs.io/en/latest/"
 end
 
 """
@@ -258,7 +258,7 @@ See also: `Uno`, `Strategies.metadata`
 function build_uno_solver(
     ::Type{<:Core.AbstractTag}, parameter::Type{<:AbstractStrategyParameter}; kwargs...
 )
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :UnoSolver;
             message="to create Uno, access options, and solve problems",
@@ -283,7 +283,7 @@ See also: `Uno`, `Strategies.StrategyMetadata`
 """
 function Strategies.metadata(::Type{<:Solvers.Uno{P}}) where {P<:CPU}
     # Extension is missing
-    throw(
+    return throw(
         Exceptions.ExtensionError(
             :UnoSolver;
             message="to access Uno{$P} options metadata",

test/problems/elec.jl

@@ -2,7 +2,7 @@
 using Random
 
 function elec_objective(x, y, z, i, j)
-    1.0 / sqrt((x[i] - x[j])^2 + (y[i] - y[j])^2 + (z[i] - z[j])^2)
+    return 1.0 / sqrt((x[i] - x[j])^2 + (y[i] - y[j])^2 + (z[i] - z[j])^2)
 end
 elec_constraint(x, y, z, i) = x[i]^2 + y[i]^2 + z[i]^2 - 1.0
 function elec_objective(x, y, z)

test/suite/extensions/test_madncl_extension.jl

@@ -69,12 +69,10 @@ function test_madncl_extension()
             Test.@test :jacobian_constant in keys(meta)
             Test.@test Options.default(meta[:bound_push]) isa Core.NotProvidedType
             Test.@test Options.default(meta[:bound_fac]) isa Core.NotProvidedType
-            Test.@test Options.default(meta[:constr_mult_init_max]) isa
-                Core.NotProvidedType
+            Test.@test Options.default(meta[:constr_mult_init_max]) isa Core.NotProvidedType
             Test.@test Options.default(meta[:fixed_variable_treatment]) isa
                 Core.NotProvidedType
-            Test.@test Options.default(meta[:equality_treatment]) isa
-                Core.NotProvidedType
+            Test.@test Options.default(meta[:equality_treatment]) isa Core.NotProvidedType
             Test.@test :kkt_system in keys(meta)
             Test.@test :hessian_approximation in keys(meta)
             Test.@test :mu_init in keys(meta)

test/suite/extensions/test_madnlp_extension.jl

@@ -137,12 +137,10 @@ function test_madnlp_extension()
             # Test initialization defaults
             Test.@test Options.default(meta[:bound_push]) isa Core.NotProvidedType
             Test.@test Options.default(meta[:bound_fac]) isa Core.NotProvidedType
-            Test.@test Options.default(meta[:constr_mult_init_max]) isa
-                Core.NotProvidedType
+            Test.@test Options.default(meta[:constr_mult_init_max]) isa Core.NotProvidedType
             Test.@test Options.default(meta[:fixed_variable_treatment]) isa
                 Core.NotProvidedType
-            Test.@test Options.default(meta[:equality_treatment]) isa
-                Core.NotProvidedType
+            Test.@test Options.default(meta[:equality_treatment]) isa Core.NotProvidedType
         end
 
         # ====================================================================
@@ -152,7 +150,7 @@ function test_madnlp_extension()
         Test.@testset "Contract validation" begin
             Test.@test Strategies.id(Solvers.MadNLP) isa Symbol
             Test.@test Strategies.metadata(Solvers.MadNLP) isa Strategies.StrategyMetadata
-            solver = Solvers.MadNLP(print_level = MadNLP.ERROR)
+            solver = Solvers.MadNLP(print_level=MadNLP.ERROR)
             Test.@test Strategies.options(solver) isa Strategies.StrategyOptions
         end
 

test/suite/integration/test_comprehensive_validation.jl

@@ -857,5 +857,5 @@ end # module
 
 # Redefine in outer scope for TestRunner
 function test_comprehensive_validation()
-    TestComprehensiveValidation.test_comprehensive_validation()
+    return TestComprehensiveValidation.test_comprehensive_validation()
 end

test/suite/integration/test_mode_propagation.jl

@@ -45,7 +45,7 @@ end
 function FakeStrategy(; mode::Symbol=:strict, kwargs...)
     # Redirect warnings to avoid polluting test output
     opts = redirect_stderr(devnull) do
-        Strategies.build_strategy_options(FakeStrategy; mode=mode, kwargs...)
+        return Strategies.build_strategy_options(FakeStrategy; mode=mode, kwargs...)
     end
     return FakeStrategy(opts)
 end