Merge branch 'master' into rw-progressbar

prbzrg · web-flow · commit 121c426eed68 · 2025-10-19T14:14:13.000+03:30
diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
@@ -26,6 +26,7 @@ jobs:
           - OptimizationGCMAES
           - OptimizationLBFGSB
           - OptimizationIpopt
+          - OptimizationMadNLP
           - OptimizationManopt
           - OptimizationMetaheuristics
           - OptimizationMOI
@@ -69,7 +70,7 @@ jobs:
           GROUP: ${{ matrix.group }}
       - uses: julia-actions/julia-processcoverage@v1
         with:
-          directories: src,lib/OptimizationBBO/src,lib/OptimizationCMAEvolutionStrategy/src,lib/OptimizationEvolutionary/src,lib/OptimizationGCMAES/src,lib/OptimizationIpopt/src,lib/OptimizationManopt/src,lib/OptimizationMOI/src,lib/OptimizationMetaheuristics/src,lib/OptimizationMultistartOptimization/src,lib/OptimizationNLopt/src,lib/OptimizationNOMAD/src,lib/OptimizationOptimJL/src,lib/OptimizationOptimisers/src,lib/OptimizationPolyalgorithms/src,lib/OptimizationQuadDIRECT/src,lib/OptimizationSpeedMapping/src
+          directories: src,lib/OptimizationBBO/src,lib/OptimizationCMAEvolutionStrategy/src,lib/OptimizationEvolutionary/src,lib/OptimizationGCMAES/src,lib/OptimizationIpopt/src,lib/OptimizationMadNLP/src,lib/OptimizationManopt/src,lib/OptimizationMOI/src,lib/OptimizationMetaheuristics/src,lib/OptimizationMultistartOptimization/src,lib/OptimizationNLopt/src,lib/OptimizationNOMAD/src,lib/OptimizationOptimJL/src,lib/OptimizationOptimisers/src,lib/OptimizationPolyalgorithms/src,lib/OptimizationQuadDIRECT/src,lib/OptimizationSpeedMapping/src
       - uses: codecov/codecov-action@v5
         with:
           file: lcov.info
diff --git a/docs/Project.toml b/docs/Project.toml
@@ -66,7 +66,7 @@ ModelingToolkit = "10.23"
 NLPModels = "0.21"
 NLPModelsTest = "0.10"
 NLopt = "0.6, 1"
-Optimization = "4"
+Optimization = "4, 5"
 OptimizationBBO = "0.4"
 OptimizationBase = "2, 3"
 OptimizationCMAEvolutionStrategy = "0.3"
@@ -76,7 +76,7 @@ OptimizationIpopt = "0.2"
 OptimizationMOI = "0.5"
 OptimizationManopt = "1"
 OptimizationMetaheuristics = "0.3"
-OptimizationNLPModels = "0.0.2"
+OptimizationNLPModels = "0.0.2, 1"
 OptimizationNLopt = "0.3"
 OptimizationNOMAD = "0.3"
 OptimizationOptimJL = "0.4"
diff --git a/docs/src/optimization_packages/multistartoptimization.md b/docs/src/optimization_packages/multistartoptimization.md
@@ -36,7 +36,7 @@ using Optimization, OptimizationMultistartOptimization, OptimizationNLopt
 rosenbrock(x, p) = (p[1] - x[1])^2 + p[2] * (x[2] - x[1]^2)^2
 x0 = zeros(2)
 p = [1.0, 100.0]
-f = OptimizationFunction(rosenbrock)
+f = OptimizationFunction(rosenbrock, Optimization.AutoForwardDiff())
 prob = Optimization.OptimizationProblem(f, x0, p, lb = [-1.0, -1.0], ub = [1.0, 1.0])
 sol = solve(prob, MultistartOptimization.TikTak(100), NLopt.LD_LBFGS())
 ```
diff --git a/lib/OptimizationBase/Project.toml b/lib/OptimizationBase/Project.toml
@@ -1,7 +1,7 @@
 name = "OptimizationBase"
 uuid = "bca83a33-5cc9-4baa-983d-23429ab6bcbb"
 authors = ["Vaibhav Dixit <vaibhavyashdixit@gmail.com> and contributors"]
-version = "3.2.0"
+version = "3.3.1"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
diff --git a/lib/OptimizationBase/ext/OptimizationZygoteExt.jl b/lib/OptimizationBase/ext/OptimizationZygoteExt.jl
@@ -208,7 +208,7 @@ function OptimizationBase.instantiate_function(
         lag_extras = prepare_hessian(
             lagrangian, soadtype, x, Constant(one(eltype(x))),
             Constant(ones(eltype(x), num_cons)), Constant(p), strict = Val(false))
-        lag_hess_prototype = zeros(Bool, num_cons, length(x))
+        lag_hess_prototype = zeros(Bool, length(x), length(x))
 
         function lag_h!(H::AbstractMatrix, θ, σ, λ)
             if σ == zero(eltype(θ))
@@ -288,6 +288,18 @@ function OptimizationBase.instantiate_function(
         f, x, adtype, p, num_cons; kwargs...)
 end
 
+function OptimizationBase.instantiate_function(
+        f::OptimizationFunction{true}, cache::OptimizationBase.ReInitCache,
+        adtype::DifferentiationInterface.SecondOrder{
+            <:ADTypes.AbstractADType, <:ADTypes.AutoZygote},
+        num_cons = 0; kwargs...)
+    x = cache.u0
+    p = cache.p
+
+    return OptimizationBase.instantiate_function(
+        f, x, adtype, p, num_cons; kwargs...)
+end
+
 function OptimizationBase.instantiate_function(
         f::OptimizationFunction{true}, x,
         adtype::ADTypes.AutoSparse{<:Union{ADTypes.AutoZygote,
@@ -575,4 +587,15 @@ function OptimizationBase.instantiate_function(
     return OptimizationBase.instantiate_function(f, x, adtype, p, num_cons; kwargs...)
 end
 
+function OptimizationBase.instantiate_function(
+        f::OptimizationFunction{true}, cache::OptimizationBase.ReInitCache,
+        adtype::ADTypes.AutoSparse{<:DifferentiationInterface.SecondOrder{
+            <:ADTypes.AbstractADType, <:ADTypes.AutoZygote}},
+        num_cons = 0; kwargs...)
+    x = cache.u0
+    p = cache.p
+
+    return OptimizationBase.instantiate_function(f, x, adtype, p, num_cons; kwargs...)
+end
+
 end
diff --git a/lib/OptimizationBase/src/OptimizationBase.jl b/lib/OptimizationBase/src/OptimizationBase.jl
@@ -15,10 +15,9 @@ import SciMLBase: solve, init, solve!, __init, __solve,
                   requireshessian, requiresconsjac,
                   requiresconshess
 
-@static if isdefined(SciMLBase, :supports_opt_cache_interface)
-    import SciMLBase: supports_opt_cache_interface
-else
-    supports_opt_cache_interface(alg) = false
+supports_opt_cache_interface(alg) = false
+@static if !hasmethod(SciMLBase.__solve, Tuple{OptimizationProblem, SciMLBase.AbstractOptimizationAlgorithm})
+    include("solve.jl")
 end
 
 export ObjSense, MaxSense, MinSense
@@ -40,7 +39,6 @@ Base.length(::NullData) = 0
 include("adtypes.jl")
 include("symify.jl")
 include("cache.jl")
-include("solve.jl")
 include("OptimizationDIExt.jl")
 include("OptimizationDISparseExt.jl")
 include("function.jl")
diff --git a/lib/OptimizationBase/src/OptimizationDIExt.jl b/lib/OptimizationBase/src/OptimizationDIExt.jl
@@ -198,7 +198,7 @@ function instantiate_function(
         lag_prep = prepare_hessian(
             lagrangian, soadtype, x, Constant(one(eltype(x))),
             Constant(ones(eltype(x), num_cons)), Constant(p))
-        lag_hess_prototype = zeros(Bool, num_cons, length(x))
+        lag_hess_prototype = zeros(Bool, length(x), length(x))
 
         function lag_h!(H::AbstractMatrix, θ, σ, λ)
             if σ == zero(eltype(θ))
@@ -457,7 +457,7 @@ function instantiate_function(
         lag_prep = prepare_hessian(
             lagrangian, soadtype, x, Constant(one(eltype(x))),
             Constant(ones(eltype(x), num_cons)), Constant(p))
-        lag_hess_prototype = zeros(Bool, num_cons, length(x))
+        lag_hess_prototype = zeros(Bool, length(x), length(x))
 
         function lag_h!(θ, σ, λ)
             if σ == zero(eltype(θ))
diff --git a/lib/OptimizationBase/src/cache.jl b/lib/OptimizationBase/src/cache.jl
@@ -62,7 +62,7 @@ function OptimizationCache(prob::SciMLBase.OptimizationProblem, opt;
         g = SciMLBase.requiresgradient(opt), h = SciMLBase.requireshessian(opt),
         hv = SciMLBase.requireshessian(opt), fg = SciMLBase.allowsfg(opt),
         fgh = SciMLBase.allowsfgh(opt), cons_j = SciMLBase.requiresconsjac(opt), cons_h = SciMLBase.requiresconshess(opt),
-        cons_vjp = SciMLBase.allowsconsjvp(opt), cons_jvp = SciMLBase.allowsconsjvp(opt), lag_h = SciMLBase.requireslagh(opt))
+        cons_vjp = SciMLBase.allowsconsvjp(opt), cons_jvp = SciMLBase.allowsconsjvp(opt), lag_h = SciMLBase.requireslagh(opt))
 
     if structural_analysis
         obj_res, cons_res = symify_cache(f, prob, num_cons, manifold)
diff --git a/lib/OptimizationBase/src/solve.jl b/lib/OptimizationBase/src/solve.jl
@@ -92,7 +92,7 @@ from NLopt for an example. The common local optimizer arguments are:
 """
 function solve(prob::SciMLBase.OptimizationProblem, alg, args...;
         kwargs...)::SciMLBase.AbstractOptimizationSolution
-    if supports_opt_cache_interface(alg)
+    if SciMLBase.supports_opt_cache_interface(alg)
         solve!(init(prob, alg, args...; kwargs...))
     else
         if prob.u0 !== nothing && !isconcretetype(eltype(prob.u0))
diff --git a/lib/OptimizationBase/test/adtests.jl b/lib/OptimizationBase/test/adtests.jl
@@ -144,6 +144,17 @@ optprob.cons_h(H3, x0)
     optprob.lag_h(H4, x0, σ, μ)
     @test H4≈σ * H2 + μ[1] * H3[1] rtol=1e-6
 
+    # Test that the AD-generated lag_hess_prototype has correct dimensions
+    @test !isnothing(optprob.lag_hess_prototype)
+    @test size(optprob.lag_hess_prototype) == (length(x0), length(x0))  # Should be n×n, not num_cons×n
+
+    # Test that we can actually use it as a buffer
+    if !isnothing(optprob.lag_hess_prototype)
+        H_proto = similar(optprob.lag_hess_prototype, Float64)
+        optprob.lag_h(H_proto, x0, σ, μ)
+        @test H_proto ≈ σ * H2 + μ[1] * H3[1] rtol=1e-6
+    end
+
     G2 = Array{Float64}(undef, 2)
     H2 = Array{Float64}(undef, 2, 2)
 
@@ -257,6 +268,17 @@ optprob.cons_h(H3, x0)
     optprob.lag_h(H4, x0, σ, μ)
     @test H4≈σ * H2 + μ[1] * H3[1] rtol=1e-6
 
+    # Test that the AD-generated lag_hess_prototype has correct dimensions
+    @test !isnothing(optprob.lag_hess_prototype)
+    @test size(optprob.lag_hess_prototype) == (length(x0), length(x0))  # Should be n×n, not num_cons×n
+
+    # Test that we can actually use it as a buffer (this would fail with the bug)
+    if !isnothing(optprob.lag_hess_prototype)
+        H_proto = similar(optprob.lag_hess_prototype, Float64)
+        optprob.lag_h(H_proto, x0, σ, μ)
+        @test H_proto ≈ σ * H2 + μ[1] * H3[1] rtol=1e-6
+    end
+
     G2 = Array{Float64}(undef, 2)
     H2 = Array{Float64}(undef, 2, 2)
 
@@ -490,6 +512,17 @@ end
     optprob.lag_h(H4, x0, σ, μ)
     @test H4≈σ * H1 + sum(μ .* H3) rtol=1e-6
 
+    # Test that the AD-generated lag_hess_prototype has correct dimensions
+    @test !isnothing(optprob.lag_hess_prototype)
+    @test size(optprob.lag_hess_prototype) == (length(x0), length(x0))  # Should be n×n, not num_cons×n
+
+    # Test that we can actually use it as a buffer (this would fail with the bug)
+    if !isnothing(optprob.lag_hess_prototype)
+        H_proto = similar(optprob.lag_hess_prototype, Float64)
+        optprob.lag_h(H_proto, x0, σ, μ)
+        @test H_proto ≈ σ * H1 + sum(μ .* H3) rtol=1e-6
+    end
+
     G2 = Array{Float64}(undef, 2)
     H2 = Array{Float64}(undef, 2, 2)
 
diff --git a/lib/OptimizationMadNLP/LICENSE b/lib/OptimizationMadNLP/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 Sebastian Micluța-Câmpeanu <sebastian.mc95@proton.me> and contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/lib/OptimizationMadNLP/Project.toml b/lib/OptimizationMadNLP/Project.toml
@@ -0,0 +1,41 @@
+name = "OptimizationMadNLP"
+uuid = "5d9c809f-c847-4062-9fba-1793bbfef577"
+version = "1.0.0"
+authors = ["Sebastian Micluța-Câmpeanu <sebastian.mc95@proton.me> and contributors"]
+
+[deps]
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+MadNLP = "2621e9c9-9eb4-46b1-8089-e8c72242dfb6"
+NLPModels = "a4795742-8479-5a88-8948-cc11e1c8c1a6"
+OptimizationBase = "bca83a33-5cc9-4baa-983d-23429ab6bcbb"
+SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
+SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
+SymbolicIndexingInterface = "2efcf032-c050-4f8e-a9bb-153293bab1f5"
+
+[compat]
+DifferentiationInterface = "0.7"
+ForwardDiff = "1.2.1"
+LinearAlgebra = "1.10.0"
+MadNLP = "0.8.12"
+ModelingToolkit = "10.23"
+NLPModels = "0.21.5"
+OptimizationBase = "3.3.1"
+SciMLBase = "2.90.0"
+SparseArrays = "1.10.0"
+SymbolicIndexingInterface = "0.3.40"
+Zygote = "0.7"
+julia = "1.10"
+
+[extras]
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
+DifferentiationInterface = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
+ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
+Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
+
+[targets]
+test = ["Aqua", "DifferentiationInterface", "ForwardDiff", "ModelingToolkit", "Random", "ReverseDiff", "Test", "Symbolics", "Zygote"]
diff --git a/lib/OptimizationMadNLP/src/OptimizationMadNLP.jl b/lib/OptimizationMadNLP/src/OptimizationMadNLP.jl
diff --git a/lib/OptimizationMadNLP/test/runtests.jl b/lib/OptimizationMadNLP/test/runtests.jl
diff --git a/lib/OptimizationNLopt/Project.toml b/lib/OptimizationNLopt/Project.toml
diff --git a/lib/OptimizationNLopt/src/OptimizationNLopt.jl b/lib/OptimizationNLopt/src/OptimizationNLopt.jl
diff --git a/lib/OptimizationNLopt/test/runtests.jl b/lib/OptimizationNLopt/test/runtests.jl
diff --git a/lib/OptimizationOptimisers/Project.toml b/lib/OptimizationOptimisers/Project.toml
