chore: remove more deprecations

Author: avik-pal

Project.toml

@@ -26,7 +26,6 @@ Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 SciMLJacobianOperators = "19f34311-ddf3-4b8b-af20-060888a46c0e"
 SciMLOperators = "c0aeaf25-5076-4817-a8d5-81caf7dfa961"
-Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 SimpleNonlinearSolve = "727e6d20-b764-4bd8-a329-72de5adea6c7"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 SparseConnectivityTracer = "9f842d2f-2579-4b1d-911e-f412cf18a3f5"
@@ -104,8 +103,7 @@ SIAMFANLEquations = "1.0.1"
 SciMLBase = "2.54.0"
 SciMLJacobianOperators = "0.1"
 SciMLOperators = "0.3.10"
-Setfield = "1.1.1"
-SimpleNonlinearSolve = "1.12.3"
+SimpleNonlinearSolve = "2"
 SparseArrays = "1.10"
 SparseConnectivityTracer = "0.6.5"
 SparseMatrixColorings = "0.4.2"

src/NonlinearSolve.jl

@@ -1,9 +1,5 @@
 module NonlinearSolve
 
-if isdefined(Base, :Experimental) && isdefined(Base.Experimental, Symbol("@max_methods"))
-    @eval Base.Experimental.@max_methods 1
-end
-
 using Reexport: @reexport
 using PrecompileTools: @compile_workload, @setup_workload
 
@@ -23,7 +19,7 @@ using LinearAlgebra: LinearAlgebra, ColumnNorm, Diagonal, I, LowerTriangular, Sy
                      UpperTriangular, axpy!, cond, diag, diagind, dot, issuccess, istril,
                      istriu, lu, mul!, norm, pinv, tril!, triu!
 using LineSearch: LineSearch, AbstractLineSearchAlgorithm, AbstractLineSearchCache,
-                  NoLineSearch, RobustNonMonotoneLineSearch, BackTracking
+                  NoLineSearch, RobustNonMonotoneLineSearch, BackTracking, LineSearchesJL
 using LinearSolve: LinearSolve, LUFactorization, QRFactorization,
                    needs_concrete_A, AbstractFactorization,
                    DefaultAlgorithmChoice, DefaultLinearSolver
@@ -34,7 +30,6 @@ using RecursiveArrayTools: recursivecopy!
 using SciMLBase: AbstractNonlinearAlgorithm, AbstractNonlinearProblem, _unwrap_val,
                  isinplace, NLStats
 using SciMLOperators: AbstractSciMLOperator
-using Setfield: @set!
 using StaticArraysCore: StaticArray, SVector, SArray, MArray, Size, SMatrix
 using SymbolicIndexingInterface: SymbolicIndexingInterface, ParameterIndexingProxy,
                                  symbolic_container, parameter_values, state_values, getu,
@@ -44,8 +39,6 @@ using SymbolicIndexingInterface: SymbolicIndexingInterface, ParameterIndexingPro
 using ADTypes: ADTypes, AbstractADType, AutoFiniteDiff, AutoForwardDiff,
                AutoPolyesterForwardDiff, AutoZygote, AutoEnzyme, AutoSparse,
                NoSparsityDetector, KnownJacobianSparsityDetector
-using ADTypes: AutoSparseFiniteDiff, AutoSparseForwardDiff, AutoSparsePolyesterForwardDiff,
-               AutoSparseZygote # FIXME: deprecated, remove in future
 using DifferentiationInterface: DifferentiationInterface, Constant
 using FiniteDiff: FiniteDiff
 using ForwardDiff: ForwardDiff, Dual
@@ -114,11 +107,20 @@ include("default.jl")
         push!(probs_nls, NonlinearProblem(fn, u0, 2.0))
     end
 
-    nls_algs = (NewtonRaphson(), TrustRegion(), LevenbergMarquardt(),
-        PseudoTransient(), Broyden(), Klement(), DFSane(), nothing)
+    nls_algs = (
+        NewtonRaphson(),
+        TrustRegion(),
+        LevenbergMarquardt(),
+        # PseudoTransient(),
+        Broyden(),
+        Klement(),
+        # DFSane(),
+        nothing
+    )
 
     probs_nlls = NonlinearLeastSquaresProblem[]
-    nlfuncs = ((NonlinearFunction{false}((u, p) -> (u .^ 2 .- p)[1:1]), [0.1, 0.0]),
+    nlfuncs = (
+        (NonlinearFunction{false}((u, p) -> (u .^ 2 .- p)[1:1]), [0.1, 0.0]),
         (NonlinearFunction{false}((u, p) -> vcat(u .* u .- p, u .* u .- p)), [0.1, 0.1]),
         (
             NonlinearFunction{true}(
@@ -127,15 +129,22 @@ include("default.jl")
         (
             NonlinearFunction{true}((du, u, p) -> du .= vcat(u .* u .- p, u .* u .- p),
                 resid_prototype = zeros(4)),
-            [0.1, 0.1]))
+            [0.1, 0.1]
+        )
+    )
     for (fn, u0) in nlfuncs
         push!(probs_nlls, NonlinearLeastSquaresProblem(fn, u0, 2.0))
     end
 
-    nlls_algs = (LevenbergMarquardt(), GaussNewton(), TrustRegion(),
-        LevenbergMarquardt(; linsolve = LUFactorization()),
-        GaussNewton(; linsolve = LUFactorization()),
-        TrustRegion(; linsolve = LUFactorization()), nothing)
+    nlls_algs = (
+        LevenbergMarquardt(),
+        GaussNewton(),
+        TrustRegion(),
+        # LevenbergMarquardt(; linsolve = LUFactorization()),
+        # GaussNewton(; linsolve = LUFactorization()),
+        # TrustRegion(; linsolve = LUFactorization()),
+        nothing
+    )
 
     @compile_workload begin
         @sync begin
@@ -177,7 +186,7 @@ export LineSearch, BackTracking, NoLineSearch, RobustNonMonotoneLineSearch, Line
 ## Trust Region Algorithms
 export RadiusUpdateSchemes
 
-# Export the termination conditions from DiffEqBase
+# Export the termination conditions from NonlinearSolveBase
 export SteadyStateDiffEqTerminationMode, SimpleNonlinearSolveTerminationMode,
        NormTerminationMode, RelTerminationMode, RelNormTerminationMode, AbsTerminationMode,
        AbsNormTerminationMode, RelSafeTerminationMode, AbsSafeTerminationMode,
@@ -189,8 +198,5 @@ export TraceAll, TraceMinimal, TraceWithJacobianConditionNumber
 # Reexport ADTypes
 export AutoFiniteDiff, AutoForwardDiff, AutoPolyesterForwardDiff, AutoZygote, AutoEnzyme,
        AutoSparse
-# FIXME: deprecated, remove in future
-export AutoSparseFiniteDiff, AutoSparseForwardDiff, AutoSparsePolyesterForwardDiff,
-       AutoSparseZygote
 
-end # module
+end

test/core/nlls_tests.jl

@@ -2,6 +2,13 @@
 using Reexport
 @reexport using NonlinearSolve, LinearSolve, LinearAlgebra, StableRNGs, Random, ForwardDiff,
                 Zygote
+using LineSearches: LineSearches, Static, HagerZhang, MoreThuente, StrongWolfe
+
+linesearches = []
+for ls in (Static(), HagerZhang(), MoreThuente(), StrongWolfe(), LineSearches.BackTracking())
+    push!(linesearches, LineSearchesJL(; method = ls))
+end
+push!(linesearches, BackTracking())
 
 true_function(x, θ) = @. θ[1] * exp(θ[2] * x) * cos(θ[3] * x + θ[4])
 true_function(y, x, θ) = (@. y = θ[1] * exp(θ[2] * x) * cos(θ[3] * x + θ[4]))
@@ -29,8 +36,7 @@ solvers = []
 for linsolve in [nothing, LUFactorization(), KrylovJL_GMRES(), KrylovJL_LSMR()]
     vjp_autodiffs = linsolve isa KrylovJL ? [nothing, AutoZygote(), AutoFiniteDiff()] :
                     [nothing]
-    for linesearch in [Static(), BackTracking(), HagerZhang(), StrongWolfe(), MoreThuente()],
-        vjp_autodiff in vjp_autodiffs
+    for linesearch in linesearches, vjp_autodiff in vjp_autodiffs
 
         push!(solvers, GaussNewton(; linsolve, linesearch, vjp_autodiff))
     end

test/core/rootfind_tests.jl

@@ -2,6 +2,7 @@
 using Reexport
 @reexport using BenchmarkTools, LinearSolve, NonlinearSolve, StaticArrays, Random,
                 LinearAlgebra, ForwardDiff, Zygote, Enzyme, DiffEqBase
+using LineSearches: LineSearches
 
 _nameof(x) = applicable(nameof, x) ? nameof(x) : _nameof(typeof(x))
 
@@ -46,8 +47,19 @@ function nlprob_iterator_interface(f, p_range, ::Val{iip}, solver) where {iip}
     return sols
 end
 
+for alg in (:Static, :StrongWolfe, :BackTracking, :MoreThuente, :HagerZhang)
+    algname = Symbol(:LineSearches, alg)
+    @eval function $(algname)(args...; autodiff = nothing, initial_alpha = true, kwargs...)
+        return LineSearch.LineSearchesJL(;
+            method = LineSearches.$(alg)(args...; kwargs...), autodiff, initial_alpha)
+    end
+end
+
 export nlprob_iterator_interface, benchmark_nlsolve_oop, benchmark_nlsolve_iip,
        TERMINATION_CONDITIONS, _nameof, newton_fails, quadratic_f, quadratic_f!
+export LineSearchesStatic, LineSearchesStrongWolfe, LineSearchesBackTracking,
+       LineSearchesMoreThuente, LineSearchesHagerZhang
+
 end
 
 # --- NewtonRaphson tests ---
@@ -57,9 +69,10 @@ end
             AutoForwardDiff(), AutoZygote(), AutoFiniteDiff()
         ),
         linesearch in (
-            Static(; autodiff = ad), StrongWolfe(; autodiff = ad),
-            BackTracking(; autodiff = ad), LineSearch.BackTracking(; autodiff = ad),
-            HagerZhang(; autodiff = ad), MoreThuente(; autodiff = ad)
+            LineSearchesStatic(; autodiff = ad), LineSearchesStrongWolfe(; autodiff = ad),
+            LineSearchesBackTracking(; autodiff = ad), BackTracking(; autodiff = ad),
+            LineSearchesHagerZhang(; autodiff = ad),
+            LineSearchesMoreThuente(; autodiff = ad)
         )
 
         u0s = ([1.0, 1.0], @SVector[1.0, 1.0], 1.0)
@@ -471,9 +484,10 @@ end
             AutoForwardDiff(), AutoZygote(), AutoFiniteDiff()
         ),
         linesearch in (
-            Static(; autodiff = ad), StrongWolfe(; autodiff = ad),
-            BackTracking(; autodiff = ad), LineSearch.BackTracking(; autodiff = ad),
-            HagerZhang(; autodiff = ad), MoreThuente(; autodiff = ad)
+            LineSearchesStatic(; autodiff = ad), LineSearchesStrongWolfe(; autodiff = ad),
+            LineSearchesBackTracking(; autodiff = ad), BackTracking(; autodiff = ad),
+            LineSearchesHagerZhang(; autodiff = ad),
+            LineSearchesMoreThuente(; autodiff = ad)
         ),
         init_jacobian in (Val(:identity), Val(:true_jacobian)),
         update_rule in (Val(:good_broyden), Val(:bad_broyden), Val(:diagonal))
@@ -524,9 +538,10 @@ end
             AutoForwardDiff(), AutoZygote(), AutoFiniteDiff()
         ),
         linesearch in (
-            Static(; autodiff = ad), StrongWolfe(; autodiff = ad),
-            BackTracking(; autodiff = ad), LineSearch.BackTracking(; autodiff = ad),
-            HagerZhang(; autodiff = ad), MoreThuente(; autodiff = ad)
+            LineSearchesStatic(; autodiff = ad), LineSearchesStrongWolfe(; autodiff = ad),
+            LineSearchesBackTracking(; autodiff = ad), BackTracking(; autodiff = ad),
+            LineSearchesHagerZhang(; autodiff = ad),
+            LineSearchesMoreThuente(; autodiff = ad)
         ),
         init_jacobian in (Val(:identity), Val(:true_jacobian), Val(:true_jacobian_diagonal))
 
@@ -577,10 +592,10 @@ end
             AutoForwardDiff(), AutoZygote(), AutoFiniteDiff()
         ),
         linesearch in (
-            Static(; autodiff = ad), StrongWolfe(; autodiff = ad),
-            BackTracking(; autodiff = ad), LineSearch.BackTracking(; autodiff = ad),
-            HagerZhang(; autodiff = ad), MoreThuente(; autodiff = ad),
-            LiFukushimaLineSearch()
+            LineSearchesStatic(; autodiff = ad), LineSearchesStrongWolfe(; autodiff = ad),
+            LineSearchesBackTracking(; autodiff = ad), BackTracking(; autodiff = ad),
+            LineSearchesHagerZhang(; autodiff = ad),
+            LineSearchesMoreThuente(; autodiff = ad), LiFukushimaLineSearch()
         )
 
         u0s = ([1.0, 1.0], @SVector[1.0, 1.0], 1.0)