Consolidate Stats Handling

Project.toml

@@ -32,7 +32,6 @@ TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 
 [weakdeps]
 BandedMatrices = "aae01518-5342-5314-be14-df237901396f"
-Enlsip = "d5306a6b-d590-428d-a53a-eb3bb2d36f2d"
 FastLevenbergMarquardt = "7a0df574-e128-4d35-8cbd-3d84502bf7ce"
 FixedPointAcceleration = "817d07cb-a79a-5c30-9a31-890123675176"
 LeastSquaresOptim = "0fc2ff8b-aaa3-5acd-a817-1944a5e08891"
@@ -46,7 +45,6 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [extensions]
 NonlinearSolveBandedMatricesExt = "BandedMatrices"
-NonlinearSolveEnlsipExt = "Enlsip"
 NonlinearSolveFastLevenbergMarquardtExt = "FastLevenbergMarquardt"
 NonlinearSolveFixedPointAccelerationExt = "FixedPointAcceleration"
 NonlinearSolveLeastSquaresOptimExt = "LeastSquaresOptim"
@@ -67,7 +65,6 @@ BenchmarkTools = "1.4"
 CUDA = "5.2"
 ConcreteStructs = "0.2.3"
 DiffEqBase = "6.149.0"
-Enlsip = "0.9"
 Enzyme = "0.12"
 ExplicitImports = "1.4.4"
 FastBroadcast = "0.2.8"
@@ -119,7 +116,6 @@ Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 BandedMatrices = "aae01518-5342-5314-be14-df237901396f"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
-Enlsip = "d5306a6b-d590-428d-a53a-eb3bb2d36f2d"
 Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
 ExplicitImports = "7d51a73a-1435-4ff3-83d9-f097790105c7"
 FastLevenbergMarquardt = "7a0df574-e128-4d35-8cbd-3d84502bf7ce"
@@ -145,4 +141,4 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["Aqua", "BandedMatrices", "BenchmarkTools", "CUDA", "Enlsip", "Enzyme", "ExplicitImports", "FastLevenbergMarquardt", "FixedPointAcceleration", "LeastSquaresOptim", "MINPACK", "ModelingToolkit", "NLSolvers", "NLsolve", "NaNMath", "NonlinearProblemLibrary", "OrdinaryDiffEq", "Pkg", "Random", "ReTestItems", "SIAMFANLEquations", "SpeedMapping", "StableRNGs", "StaticArrays", "Sundials", "Symbolics", "Test", "Zygote"]
+test = ["Aqua", "BandedMatrices", "BenchmarkTools", "CUDA", "Enzyme", "ExplicitImports", "FastLevenbergMarquardt", "FixedPointAcceleration", "LeastSquaresOptim", "MINPACK", "ModelingToolkit", "NLSolvers", "NLsolve", "NaNMath", "NonlinearProblemLibrary", "OrdinaryDiffEq", "Pkg", "Random", "ReTestItems", "SIAMFANLEquations", "SpeedMapping", "StableRNGs", "StaticArrays", "Sundials", "Symbolics", "Test", "Zygote"]

docs/src/basics/nonlinear_solution.md

@@ -9,7 +9,6 @@ SciMLBase.NonlinearSolution
 
 ```@docs
 SciMLBase.NLStats
-NonlinearSolve.ImmutableNLStats
 ```
 
 ## Return Code

src/NonlinearSolve.jl

@@ -34,13 +34,14 @@ using PrecompileTools: @recompile_invalidations, @compile_workload, @setup_workl
                          istril, istriu, lu, mul!, norm, pinv, tril!, triu!
     using LineSearches: LineSearches
     using LinearSolve: LinearSolve, LUFactorization, QRFactorization, ComposePreconditioner,
-                       InvPreconditioner, needs_concrete_A
+                       InvPreconditioner, needs_concrete_A, AbstractFactorization,
+                       DefaultAlgorithmChoice, DefaultLinearSolver
     using MaybeInplace: @bb
     using Printf: @printf
     using Preferences: Preferences, @load_preference, @set_preferences!
     using RecursiveArrayTools: recursivecopy!, recursivefill!
     using SciMLBase: AbstractNonlinearAlgorithm, JacobianWrapper, AbstractNonlinearProblem,
-                     AbstractSciMLOperator, _unwrap_val, has_jac, isinplace
+                     AbstractSciMLOperator, _unwrap_val, has_jac, isinplace, NLStats
     using SparseArrays: AbstractSparseMatrix, SparseMatrixCSC
     using SparseDiffTools: SparseDiffTools, AbstractSparsityDetection,
                            ApproximateJacobianSparsity, JacPrototypeSparsityDetection,

src/abstract_types.jl

@@ -142,7 +142,6 @@ abstract type AbstractNonlinearSolveLineSearchCache end
 
 function reinit_cache!(
         cache::AbstractNonlinearSolveLineSearchCache, args...; p = cache.p, kwargs...)
-    cache.nf[] = 0
     cache.p = p
 end
 
@@ -235,7 +234,7 @@ function __show_cache(io::IO, cache::AbstractNonlinearSolveCache, indent = 0)
     println(io, (" "^(indent + 4)) * "u = ", get_u(cache), ",")
     println(io, (" "^(indent + 4)) * "residual = ", get_fu(cache), ",")
     println(io, (" "^(indent + 4)) * "inf-norm(residual) = ", norm(get_fu(cache), Inf), ",")
-    println(io, " "^(indent + 4) * "nsteps = ", get_nsteps(cache), ",")
+    println(io, " "^(indent + 4) * "nsteps = ", cache.stats.nsteps, ",")
     println(io, " "^(indent + 4) * "retcode = ", cache.retcode)
     print(io, " "^(indent) * ")")
 end

src/core/approximate_jacobian.jl

@@ -95,7 +95,7 @@ end
     inv_workspace
 
     # Counters
-    nf::Int
+    stats::NLStats
     nsteps::Int
     nresets::Int
     max_resets::Int
@@ -131,7 +131,7 @@ function __reinit_internal!(cache::ApproximateJacobianSolveCache{INV, GB, iip},
     end
     cache.p = p
 
-    cache.nf = 1
+    __reinit_internal!(cache.stats)
     cache.nsteps = 0
     cache.nresets = 0
     cache.steps_since_last_reset = 0
@@ -151,8 +151,9 @@ end
 
 function SciMLBase.__init(
         prob::AbstractNonlinearProblem{uType, iip}, alg::ApproximateJacobianSolveAlgorithm,
-        args...; alias_u0 = false, maxtime = nothing, maxiters = 1000, abstol = nothing,
-        reltol = nothing, linsolve_kwargs = (;), termination_condition = nothing,
+        args...; stats = empty_nlstats(), alias_u0 = false, maxtime = nothing,
+        maxiters = 1000, abstol = nothing, reltol = nothing,
+        linsolve_kwargs = (;), termination_condition = nothing,
         internalnorm::F = DEFAULT_NORM, kwargs...) where {uType, iip, F}
     timer = get_timer_output()
     @static_timeit timer "cache construction" begin
@@ -164,18 +165,17 @@ function SciMLBase.__init(
         INV = store_inverse_jacobian(alg.update_rule)
 
         linsolve = get_linear_solver(alg.descent)
-        initialization_cache = __internal_init(
-            prob, alg.initialization, alg, f, fu, u, p; linsolve, maxiters, internalnorm)
+        initialization_cache = __internal_init(prob, alg.initialization, alg, f, fu, u, p;
+            stats, linsolve, maxiters, internalnorm)
 
         abstol, reltol, termination_cache = init_termination_cache(
             prob, abstol, reltol, fu, u, termination_condition)
         linsolve_kwargs = merge((; abstol, reltol), linsolve_kwargs)
 
         J = initialization_cache(nothing)
         inv_workspace, J = INV ? __safe_inv_workspace(J) : (nothing, J)
-        descent_cache = __internal_init(
-            prob, alg.descent, J, fu, u; abstol, reltol, internalnorm,
-            linsolve_kwargs, pre_inverted = Val(INV), timer)
+        descent_cache = __internal_init(prob, alg.descent, J, fu, u; stats, abstol, reltol,
+            internalnorm, linsolve_kwargs, pre_inverted = Val(INV), timer)
         du = get_du(descent_cache)
 
         reinit_rule_cache = __internal_init(alg.reinit_rule, J, fu, u, du)
@@ -192,28 +192,28 @@ function SciMLBase.__init(
             supports_trust_region(alg.descent) || error("Trust Region not supported by \
                                                         $(alg.descent).")
             trustregion_cache = __internal_init(
-                prob, alg.trustregion, f, fu, u, p; internalnorm, kwargs...)
+                prob, alg.trustregion, f, fu, u, p; stats, internalnorm, kwargs...)
             GB = :TrustRegion
         end
 
         if alg.linesearch !== missing
             supports_line_search(alg.descent) || error("Line Search not supported by \
                                                         $(alg.descent).")
             linesearch_cache = __internal_init(
-                prob, alg.linesearch, f, fu, u, p; internalnorm, kwargs...)
+                prob, alg.linesearch, f, fu, u, p; stats, internalnorm, kwargs...)
             GB = :LineSearch
         end
 
         update_rule_cache = __internal_init(
-            prob, alg.update_rule, J, fu, u, du; internalnorm)
+            prob, alg.update_rule, J, fu, u, du; stats, internalnorm)
 
         trace = init_nonlinearsolve_trace(prob, alg, u, fu, ApplyArray(__zero, J), du;
             uses_jacobian_inverse = Val(INV), kwargs...)
 
         return ApproximateJacobianSolveCache{INV, GB, iip, maxtime !== nothing}(
             fu, u, u_cache, p, du, J, alg, prob, initialization_cache,
             descent_cache, linesearch_cache, trustregion_cache, update_rule_cache,
-            reinit_rule_cache, inv_workspace, 0, 0, 0, alg.max_resets,
+            reinit_rule_cache, inv_workspace, stats, 0, 0, alg.max_resets,
             maxiters, maxtime, alg.max_shrink_times, 0, timer, 0.0,
             termination_cache, trace, ReturnCode.Default, false, false, kwargs)
     end
@@ -223,7 +223,7 @@ function __step!(cache::ApproximateJacobianSolveCache{INV, GB, iip};
         recompute_jacobian::Union{Nothing, Bool} = nothing) where {INV, GB, iip}
     new_jacobian = true
     @static_timeit cache.timer "jacobian init/reinit" begin
-        if get_nsteps(cache) == 0  # First Step is special ignore kwargs
+        if cache.nsteps == 0  # First Step is special ignore kwargs
             J_init = __internal_solve!(
                 cache.initialization_cache, cache.fu, cache.u, Val(false))
             if INV

src/core/generalized_first_order.jl

@@ -97,7 +97,7 @@ concrete_jac(::GeneralizedFirstOrderAlgorithm{CJ}) where {CJ} = CJ
     trustregion_cache
 
     # Counters
-    nf::Int
+    stats::NLStats
     nsteps::Int
     maxiters::Int
     maxtime
@@ -135,7 +135,7 @@ function __reinit_internal!(
     end
     cache.p = p
 
-    cache.nf = 1
+    __reinit_internal!(cache.stats)
     cache.nsteps = 0
     cache.maxiters = maxiters
     cache.maxtime = maxtime
@@ -153,9 +153,10 @@ end
 
 function SciMLBase.__init(
         prob::AbstractNonlinearProblem{uType, iip}, alg::GeneralizedFirstOrderAlgorithm,
-        args...; alias_u0 = false, maxiters = 1000, abstol = nothing,
-        reltol = nothing, maxtime = nothing, termination_condition = nothing,
-        internalnorm = DEFAULT_NORM, linsolve_kwargs = (;), kwargs...) where {uType, iip}
+        args...; stats = empty_nlstats(), alias_u0 = false, maxiters = 1000,
+        abstol = nothing, reltol = nothing, maxtime = nothing,
+        termination_condition = nothing, internalnorm = DEFAULT_NORM,
+        linsolve_kwargs = (;), kwargs...) where {uType, iip}
     timer = get_timer_output()
     @static_timeit timer "cache construction" begin
         (; f, u0, p) = prob
@@ -170,11 +171,11 @@ function SciMLBase.__init(
         linsolve_kwargs = merge((; abstol, reltol), linsolve_kwargs)
 
         jac_cache = JacobianCache(
-            prob, alg, f, fu, u, p; autodiff = alg.jacobian_ad, linsolve,
+            prob, alg, f, fu, u, p; stats, autodiff = alg.jacobian_ad, linsolve,
             jvp_autodiff = alg.forward_ad, vjp_autodiff = alg.reverse_ad)
         J = jac_cache(nothing)
-        descent_cache = __internal_init(prob, alg.descent, J, fu, u; abstol, reltol,
-            internalnorm, linsolve_kwargs, timer)
+        descent_cache = __internal_init(prob, alg.descent, J, fu, u; stats, abstol,
+            reltol, internalnorm, linsolve_kwargs, timer)
         du = get_du(descent_cache)
 
         if alg.trustregion !== missing && alg.linesearch !== missing
@@ -189,15 +190,15 @@ function SciMLBase.__init(
             supports_trust_region(alg.descent) || error("Trust Region not supported by \
                                                         $(alg.descent).")
             trustregion_cache = __internal_init(
-                prob, alg.trustregion, f, fu, u, p; internalnorm, kwargs...)
+                prob, alg.trustregion, f, fu, u, p; stats, internalnorm, kwargs...)
             GB = :TrustRegion
         end
 
         if alg.linesearch !== missing
             supports_line_search(alg.descent) || error("Line Search not supported by \
                                                         $(alg.descent).")
             linesearch_cache = __internal_init(
-                prob, alg.linesearch, f, fu, u, p; internalnorm, kwargs...)
+                prob, alg.linesearch, f, fu, u, p; stats, internalnorm, kwargs...)
             GB = :LineSearch
         end
 
@@ -206,7 +207,7 @@ function SciMLBase.__init(
 
         return GeneralizedFirstOrderAlgorithmCache{iip, GB, maxtime !== nothing}(
             fu, u, u_cache, p, du, J, alg, prob, jac_cache, descent_cache, linesearch_cache,
-            trustregion_cache, 0, 0, maxiters, maxtime, alg.max_shrink_times, timer,
+            trustregion_cache, stats, 0, maxiters, maxtime, alg.max_shrink_times, timer,
             0.0, true, termination_cache, trace, ReturnCode.Default, false, kwargs)
     end
 end

src/core/generic.jl

@@ -1,11 +1,11 @@
 function SciMLBase.__solve(prob::Union{NonlinearProblem, NonlinearLeastSquaresProblem},
-        alg::AbstractNonlinearSolveAlgorithm, args...; kwargs...)
-    cache = init(prob, alg, args...; kwargs...)
+        alg::AbstractNonlinearSolveAlgorithm, args...; stats = empty_nlstats(), kwargs...)
+    cache = SciMLBase.__init(prob, alg, args...; stats, kwargs...)
     return solve!(cache)
 end
 
 function not_terminated(cache::AbstractNonlinearSolveCache)
-    return !cache.force_stop && get_nsteps(cache) < cache.maxiters
+    return !cache.force_stop && cache.nsteps < cache.maxiters
 end
 
 function SciMLBase.solve!(cache::AbstractNonlinearSolveCache)
@@ -16,21 +16,16 @@ function SciMLBase.solve!(cache::AbstractNonlinearSolveCache)
     # The solver might have set a different `retcode`
     if cache.retcode == ReturnCode.Default
         cache.retcode = ifelse(
-            get_nsteps(cache) ≥ cache.maxiters, ReturnCode.MaxIters, ReturnCode.Success)
+            cache.nsteps ≥ cache.maxiters, ReturnCode.MaxIters, ReturnCode.Success)
     end
 
     update_from_termination_cache!(cache.termination_cache, cache)
 
-    update_trace!(cache.trace, get_nsteps(cache), get_u(cache),
+    update_trace!(cache.trace, cache.nsteps, get_u(cache),
         get_fu(cache), nothing, nothing, nothing; last = True)
 
     return SciMLBase.build_solution(cache.prob, cache.alg, get_u(cache), get_fu(cache);
-        cache.retcode, stats = __compile_stats(cache), cache.trace)
-end
-
-function __compile_stats(cache::AbstractNonlinearSolveCache)
-    return ImmutableNLStats(get_nf(cache), get_njacs(cache), get_nfactors(cache),
-        get_nsolve(cache), get_nsteps(cache))
+        cache.retcode, cache.stats, cache.trace)
 end
 
 """
@@ -55,7 +50,8 @@ function SciMLBase.step!(cache::AbstractNonlinearSolveCache{iip, timeit},
         __step!(cache, args...; kwargs...)
     end
 
-    hasfield(typeof(cache), :nsteps) && (cache.nsteps += 1)
+    cache.stats.nsteps += 1
+    cache.nsteps += 1
 
     if timeit
         cache.total_time += time() - time_start

src/core/spectral_methods.jl

@@ -60,7 +60,7 @@ concrete_jac(::GeneralizedDFSane) = nothing
     linesearch_cache
 
     # Counters
-    nf::Int
+    stats::NLStats
     nsteps::Int
     maxiters::Int
     maxtime
@@ -106,7 +106,7 @@ function __reinit_internal!(
 
     reset!(cache.trace)
     reinit!(cache.termination_cache, get_fu(cache), get_u(cache); kwargs...)
-    cache.nf = 1
+    __reinit_internal!(cache.stats)
     cache.nsteps = 0
     cache.maxiters = maxiters
     cache.maxtime = maxtime
@@ -116,9 +116,9 @@ end
 
 @internal_caches GeneralizedDFSaneCache :linesearch_cache
 
-function SciMLBase.__init(prob::AbstractNonlinearProblem, alg::GeneralizedDFSane,
-        args...; alias_u0 = false, maxiters = 1000, abstol = nothing,
-        reltol = nothing, termination_condition = nothing,
+function SciMLBase.__init(prob::AbstractNonlinearProblem, alg::GeneralizedDFSane, args...;
+        stats = empty_nlstats(), alias_u0 = false, maxiters = 1000,
+        abstol = nothing, reltol = nothing, termination_condition = nothing,
         internalnorm::F = DEFAULT_NORM, maxtime = nothing, kwargs...) where {F}
     timer = get_timer_output()
     @static_timeit timer "cache construction" begin
@@ -130,8 +130,8 @@ function SciMLBase.__init(prob::AbstractNonlinearProblem, alg::GeneralizedDFSane
         fu = evaluate_f(prob, u)
         @bb fu_cache = copy(fu)
 
-        linesearch_cache = __internal_init(
-            prob, alg.linesearch, prob.f, fu, u, prob.p; maxiters, internalnorm, kwargs...)
+        linesearch_cache = __internal_init(prob, alg.linesearch, prob.f, fu, u, prob.p;
+            stats, maxiters, internalnorm, kwargs...)
 
         abstol, reltol, tc_cache = init_termination_cache(
             prob, abstol, reltol, fu, u_cache, termination_condition)
@@ -150,7 +150,7 @@ function SciMLBase.__init(prob::AbstractNonlinearProblem, alg::GeneralizedDFSane
 
         return GeneralizedDFSaneCache{isinplace(prob), maxtime !== nothing}(
             fu, fu_cache, u, u_cache, prob.p, du, alg, prob, σ_n, T(alg.σ_min),
-            T(alg.σ_max), linesearch_cache, 0, 0, maxiters, maxtime,
+            T(alg.σ_max), linesearch_cache, stats, 0, maxiters, maxtime,
             timer, 0.0, tc_cache, trace, ReturnCode.Default, false, kwargs)
     end
 end