Fix dependency structure of solvers to OptimizationBase

Project.toml

@@ -20,6 +20,10 @@ TerminalLoggers = "5d786b92-1e48-4d6f-9151-6b4477ca9bed"
 
 [sources]
 OptimizationBase = {path = "lib/OptimizationBase"}
+OptimizationLBFGSB = {path = "lib/OptimizationLBFGSB"}
+OptimizationMOI = {path = "lib/OptimizationMOI"}
+OptimizationOptimJL = {path = "lib/OptimizationOptimJL"}
+OptimizationOptimisers = {path = "lib/OptimizationOptimisers"}
 
 [compat]
 ADTypes = "1.2"
@@ -47,6 +51,7 @@ Mooncake = "0.4.138"
 Optim = ">= 1.4.1"
 Optimisers = ">= 0.2.5"
 OptimizationBase = "2"
+OptimizationLBFGSB = "1"
 OptimizationMOI = "0.5"
 OptimizationOptimJL = "0.4"
 OptimizationOptimisers = "0.3"
@@ -84,6 +89,7 @@ Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 Optim = "429524aa-4258-5aef-a3af-852621145aeb"
+OptimizationLBFGSB = "22f7324a-a79d-40f2-bebe-3af60c77bd15"
 Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
 OptimizationMOI = "fd9f6733-72f4-499f-8506-86b2bdd0dea1"
 OptimizationOptimJL = "36348300-93cb-4f02-beb5-3c3902f8871e"
@@ -103,6 +109,6 @@ Mooncake = "da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"
 
 [targets]
 test = ["Aqua", "BenchmarkTools", "Boltz", "ComponentArrays", "DiffEqFlux", "Enzyme", "FiniteDiff", "Flux", "ForwardDiff",
-    "Ipopt", "IterTools", "Lux", "MLUtils", "ModelingToolkit", "Optim", "OptimizationMOI", "OptimizationOptimJL", "OptimizationOptimisers", 
+    "Ipopt", "IterTools", "Lux", "MLUtils", "ModelingToolkit", "Optim", "OptimizationLBFGSB", "OptimizationMOI", "OptimizationOptimJL", "OptimizationOptimisers", 
     "OrdinaryDiffEqTsit5", "Pkg", "Random", "ReverseDiff", "SafeTestsets", "SciMLSensitivity", "SparseArrays",
     "Symbolics",  "Test", "Tracker", "Zygote", "Mooncake"]

lib/OptimizationAuglag/Project.toml

@@ -3,23 +3,26 @@ uuid = "2ea93f80-9333-43a1-a68d-1f53b957a421"
 authors = ["paramthakkar123 <[email protected]>"]
 version = "1.0.0"
 
+[sources]
+OptimizationBase = {path = "../OptimizationBase"}
+
 [deps]
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
-MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
-Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationBase = "bca83a33-5cc9-4baa-983d-23429ab6bcbb"
+MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
+SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
 ForwardDiff = "1.0.1"
+OptimizationBase = "2.13"
 MLUtils = "0.4.8"
-Optimization = "4.4.0"
-OptimizationBase = "2.10.0"
 OptimizationOptimisers = "0.3.8"
 Test = "1.10.0"
+SciMLBase = "2.58"
 julia = "1.10"
 
 [targets]

lib/OptimizationAuglag/src/OptimizationAuglag.jl

@@ -1,7 +1,6 @@
 module OptimizationAuglag
 
-using Optimization
-using OptimizationBase.SciMLBase: OptimizationProblem, OptimizationFunction, OptimizationStats
+using SciMLBase: OptimizationProblem, OptimizationFunction, OptimizationStats
 using OptimizationBase.LinearAlgebra: norm
 
 @kwdef struct AugLag
@@ -84,7 +83,7 @@ function SciMLBase.__solve(cache::OptimizationCache{
         P,
         C
 }
-    maxiters = Optimization._check_and_convert_maxiters(cache.solver_args.maxiters)
+    maxiters = OptimizationBase._check_and_convert_maxiters(cache.solver_args.maxiters)
 
     local x
 
@@ -116,7 +115,7 @@ function SciMLBase.__solve(cache::OptimizationCache{
             cache.f.cons(cons_tmp, θ)
             cons_tmp[eq_inds] .= cons_tmp[eq_inds] - cache.lcons[eq_inds]
             cons_tmp[ineq_inds] .= cons_tmp[ineq_inds] .- cache.ucons[ineq_inds]
-            opt_state = Optimization.OptimizationState(u = θ, objective = x[1])
+            opt_state = OptimizationBase.OptimizationState(u = θ, objective = x[1])
             if cache.callback(opt_state, x...)
                 error("Optimization halted by callback.")
             end

lib/OptimizationAuglag/test/runtests.jl

@@ -4,7 +4,7 @@ using OptimizationOptimisers
 using OptimizationAuglag
 using ForwardDiff
 using OptimizationBase: OptimizationCache
-using OptimizationBase.SciMLBase: OptimizationFunction
+using SciMLBase: OptimizationFunction
 using Test
 
 @testset "OptimizationAuglag.jl" begin

lib/OptimizationBBO/Project.toml

@@ -3,19 +3,24 @@ uuid = "3e6eede4-6085-4f62-9a71-46d9bc1eb92b"
 authors = ["Vaibhav Dixit <[email protected]> and contributors"]
 version = "0.4.2"
 
+[sources]
+OptimizationBase = {path = "../OptimizationBase"}
+
 [deps]
 BlackBoxOptim = "a134a8b2-14d6-55f6-9291-3336d3ab0209"
-Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
+OptimizationBase = "bca83a33-5cc9-4baa-983d-23429ab6bcbb"
+SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 
+[extras]
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
 [compat]
+julia = "1.10"
 BlackBoxOptim = "0.6"
-Optimization = "4.4"
+OptimizationBase = "2.13"
+SciMLBase = "2.58"
 Reexport = "1.2"
-julia = "1.10"
-
-[extras]
-Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
 test = ["Test"]

lib/OptimizationBBO/src/OptimizationBBO.jl

@@ -1,10 +1,10 @@
 module OptimizationBBO
 
 using Reexport
-import Optimization
-import Optimization: OptimizationBase
-import BlackBoxOptim, Optimization.SciMLBase
-import Optimization.SciMLBase: MultiObjectiveOptimizationFunction
+import OptimizationBase
+import OptimizationBase: SciMLBase
+import BlackBoxOptim
+import SciMLBase: MultiObjectiveOptimizationFunction
 
 abstract type BBO end
 
@@ -48,7 +48,7 @@ function decompose_trace(opt::BlackBoxOptim.OptRunController, progress)
     return BlackBoxOptim.best_candidate(opt)
 end
 
-function __map_optimizer_args(prob::Optimization.OptimizationCache, opt::BBO;
+function __map_optimizer_args(prob::OptimizationBase.OptimizationCache, opt::BBO;
         callback = nothing,
         maxiters::Union{Number, Nothing} = nothing,
         maxtime::Union{Number, Nothing} = nothing,
@@ -96,7 +96,7 @@ function map_objective(obj::BlackBoxOptim.IndexedTupleFitness)
     obj.orig
 end
 
-function SciMLBase.__solve(cache::Optimization.OptimizationCache{
+function SciMLBase.__solve(cache::OptimizationBase.OptimizationCache{
         F,
         RC,
         LB,
@@ -123,13 +123,13 @@ function SciMLBase.__solve(cache::Optimization.OptimizationCache{
         C
 }
     function _cb(trace)
-        if cache.callback === Optimization.DEFAULT_CALLBACK
+        if cache.callback === OptimizationBase.DEFAULT_CALLBACK
             cb_call = false
         else
             n_steps = BlackBoxOptim.num_steps(trace)
             curr_u = decompose_trace(trace, cache.progress)
             objective = map_objective(BlackBoxOptim.best_fitness(trace))
-            opt_state = Optimization.OptimizationState(;
+            opt_state = OptimizationBase.OptimizationState(;
                 iter = n_steps,
                 u = curr_u,
                 p = cache.p,
@@ -148,15 +148,15 @@ function SciMLBase.__solve(cache::Optimization.OptimizationCache{
         cb_call
     end
 
-    maxiters = Optimization._check_and_convert_maxiters(cache.solver_args.maxiters)
-    maxtime = Optimization._check_and_convert_maxtime(cache.solver_args.maxtime)
+    maxiters = OptimizationBase._check_and_convert_maxiters(cache.solver_args.maxiters)
+    maxtime = OptimizationBase._check_and_convert_maxtime(cache.solver_args.maxtime)
 
     _loss = function (θ)
         cache.f(θ, cache.p)
     end
 
     opt_args = __map_optimizer_args(cache, cache.opt;
-        callback = cache.callback === Optimization.DEFAULT_CALLBACK ?
+        callback = cache.callback === OptimizationBase.DEFAULT_CALLBACK ?
                    nothing : _cb,
         cache.solver_args...,
         maxiters = maxiters,
@@ -176,8 +176,8 @@ function SciMLBase.__solve(cache::Optimization.OptimizationCache{
     end
 
     # Use the improved convert function
-    opt_ret = Optimization.deduce_retcode(opt_res.stop_reason)
-    stats = Optimization.OptimizationStats(;
+    opt_ret = OptimizationBase.deduce_retcode(opt_res.stop_reason)
+    stats = OptimizationBase.OptimizationStats(;
         iterations = opt_res.iterations,
         time = opt_res.elapsed_time,
         fevals = opt_res.f_calls)

lib/OptimizationBBO/test/runtests.jl

@@ -1,5 +1,5 @@
 using OptimizationBBO, Optimization, BlackBoxOptim
-using Optimization.SciMLBase: MultiObjectiveOptimizationFunction
+using SciMLBase: MultiObjectiveOptimizationFunction
 using Test
 
 @testset "OptimizationBBO.jl" begin
@@ -9,14 +9,14 @@ using Test
     l1 = rosenbrock(x0, _p)
 
     optprob = OptimizationFunction(rosenbrock)
-    prob = Optimization.OptimizationProblem(optprob, x0, _p, lb = [-1.0, -1.0],
+    prob = OptimizationBase.OptimizationProblem(optprob, x0, _p, lb = [-1.0, -1.0],
         ub = [0.8, 0.8])
     sol = solve(prob, BBO_adaptive_de_rand_1_bin_radiuslimited())
     @test 10 * sol.objective < l1
 
     @test (@allocated solve(prob, BBO_adaptive_de_rand_1_bin_radiuslimited())) < 1e7
 
-    prob = Optimization.OptimizationProblem(optprob, nothing, _p, lb = [-1.0, -1.0],
+    prob = OptimizationBase.OptimizationProblem(optprob, nothing, _p, lb = [-1.0, -1.0],
         ub = [0.8, 0.8])
     sol = solve(prob, BBO_adaptive_de_rand_1_bin_radiuslimited())
     @test 10 * sol.objective < l1
@@ -74,7 +74,7 @@ using Test
             end
 
             mof_1 = MultiObjectiveOptimizationFunction(multi_obj_func_1)
-            prob_1 = Optimization.OptimizationProblem(mof_1, u0; lb = lb, ub = ub)
+            prob_1 = OptimizationBase.OptimizationProblem(mof_1, u0; lb = lb, ub = ub)
             sol_1 = solve(prob_1, opt, NumDimensions = 2,
                 FitnessScheme = ParetoFitnessScheme{2}(is_minimizing = true))
 
@@ -101,7 +101,7 @@ using Test
             end
 
             mof_1 = MultiObjectiveOptimizationFunction(multi_obj_func_1)
-            prob_1 = Optimization.OptimizationProblem(mof_1, u0; lb = lb, ub = ub)
+            prob_1 = OptimizationBase.OptimizationProblem(mof_1, u0; lb = lb, ub = ub)
             sol_1 = solve(prob_1, opt, NumDimensions = 2,
                 FitnessScheme = ParetoFitnessScheme{2}(is_minimizing = true),
                 callback = cb)
@@ -127,7 +127,7 @@ using Test
             end
 
             mof_2 = MultiObjectiveOptimizationFunction(multi_obj_func_2)
-            prob_2 = Optimization.OptimizationProblem(mof_2, u0; lb = lb, ub = ub)
+            prob_2 = OptimizationBase.OptimizationProblem(mof_2, u0; lb = lb, ub = ub)
             sol_2 = solve(prob_2, opt, NumDimensions = 2,
                 FitnessScheme = ParetoFitnessScheme{2}(is_minimizing = true))
 
@@ -147,7 +147,7 @@ using Test
             end
 
             mof_3 = MultiObjectiveOptimizationFunction(multi_obj_func_3)
-            prob_3 = Optimization.OptimizationProblem(mof_3, u0; lb = lb, ub = ub)
+            prob_3 = OptimizationBase.OptimizationProblem(mof_3, u0; lb = lb, ub = ub)
             sol_3 = solve(prob_3, opt, NumDimensions = 2,
                 FitnessScheme = ParetoFitnessScheme{2}(is_minimizing = true))
 

lib/OptimizationBase/Project.toml

@@ -1,7 +1,7 @@
 name = "OptimizationBase"
 uuid = "bca83a33-5cc9-4baa-983d-23429ab6bcbb"
 authors = ["Vaibhav Dixit <[email protected]> and contributors"]
-version = "2.12.0"
+version = "2.13.0"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"

lib/OptimizationBase/ext/OptimizationEnzymeExt.jl

@@ -1,8 +1,8 @@
 module OptimizationEnzymeExt
 
 import OptimizationBase, OptimizationBase.ArrayInterface
-import OptimizationBase.SciMLBase: OptimizationFunction
-import OptimizationBase.SciMLBase
+import SciMLBase: OptimizationFunction
+import SciMLBase
 import OptimizationBase.LinearAlgebra: I, dot
 import OptimizationBase.ADTypes: AutoEnzyme
 using Enzyme

lib/OptimizationBase/ext/OptimizationMTKExt.jl

@@ -1,8 +1,8 @@
 module OptimizationMTKExt
 
 import OptimizationBase, OptimizationBase.ArrayInterface
-import OptimizationBase.SciMLBase
-import OptimizationBase.SciMLBase: OptimizationFunction
+import SciMLBase
+import SciMLBase: OptimizationFunction
 import OptimizationBase.ADTypes: AutoModelingToolkit, AutoSymbolics, AutoSparse
 using ModelingToolkit
 

lib/OptimizationBase/ext/OptimizationZygoteExt.jl

@@ -3,7 +3,7 @@ module OptimizationZygoteExt
 using OptimizationBase, SparseArrays
 using OptimizationBase.FastClosures
 import OptimizationBase.ArrayInterface
-import OptimizationBase.SciMLBase: OptimizationFunction
+import SciMLBase: OptimizationFunction
 import OptimizationBase.LinearAlgebra: I, dot
 import DifferentiationInterface
 import DifferentiationInterface: prepare_gradient, prepare_hessian, prepare_hvp,

lib/OptimizationBase/src/OptimizationBase.jl

@@ -28,6 +28,8 @@ include("OptimizationDIExt.jl")
 include("OptimizationDISparseExt.jl")
 include("function.jl")
 include("solve.jl")
+include("utils.jl")
+include("state.jl")
 
 export solve, OptimizationCache, DEFAULT_CALLBACK, DEFAULT_DATA,
        IncompatibleOptimizerError, OptimizerMissingError, _check_opt_alg,

lib/OptimizationBase/src/OptimizationDIExt.jl

@@ -1,6 +1,6 @@
 using OptimizationBase
 import OptimizationBase.ArrayInterface
-import OptimizationBase.SciMLBase: OptimizationFunction
+import SciMLBase: OptimizationFunction
 import OptimizationBase.LinearAlgebra: I
 import DifferentiationInterface
 import DifferentiationInterface: prepare_gradient, prepare_hessian, prepare_hvp,

lib/OptimizationBase/src/OptimizationDISparseExt.jl

@@ -1,6 +1,6 @@
 using OptimizationBase
 import OptimizationBase.ArrayInterface
-import OptimizationBase.SciMLBase: OptimizationFunction
+import SciMLBase: OptimizationFunction
 import OptimizationBase.LinearAlgebra: I
 import DifferentiationInterface
 import DifferentiationInterface: prepare_gradient, prepare_hessian, prepare_hvp,

lib/OptimizationBase/src/augmented_lagrangian.jl

@@ -4,7 +4,7 @@ function generate_auglag(θ)
     cache.f.cons(cons_tmp, θ)
     cons_tmp[eq_inds] .= cons_tmp[eq_inds] - cache.lcons[eq_inds]
     cons_tmp[ineq_inds] .= cons_tmp[ineq_inds] .- cache.ucons[ineq_inds]
-    opt_state = Optimization.OptimizationState(u = θ, objective = x[1])
+    opt_state = OptimizationBase.OptimizationState(u = θ, objective = x[1])
     if cache.callback(opt_state, x...)
         error("Optimization halted by callback.")
     end

lib/OptimizationBase/src/function.jl

@@ -21,9 +21,9 @@ function rep_pars_vals!(e, p) end
 """
     instantiate_function(f, x, ::AbstractADType, p, num_cons = 0)::OptimizationFunction
 
-This function is used internally by Optimization.jl to construct
+This function is used internally by OptimizationBase.jl to construct
 the necessary extra functions (gradients, Hessians, etc.) before
-optimization. Each of the ADType dispatches use the supplied automatic
+OptimizationBase. Each of the ADType dispatches use the supplied automatic
 differentiation type in order to specify how the construction process
 occurs.
 

lib/OptimizationBase/src/solve.jl

@@ -12,11 +12,11 @@ end
 const OPTIMIZER_MISSING_ERROR_MESSAGE = """
                                         Optimization algorithm not found. Either the chosen algorithm is not a valid solver
                                         choice for the `OptimizationProblem`, or the Optimization solver library is not loaded.
-                                        Make sure that you have loaded an appropriate Optimization.jl solver library, for example,
+                                        Make sure that you have loaded an appropriate OptimizationBase.jl solver library, for example,
                                         `solve(prob,Optim.BFGS())` requires `using OptimizationOptimJL` and
                                         `solve(prob,Adam())` requires `using OptimizationOptimisers`.
 
-                                        For more information, see the Optimization.jl documentation: <https://docs.sciml.ai/Optimization/stable/>.
+                                        For more information, see the OptimizationBase.jl documentation: <https://docs.sciml.ai/Optimization/stable/>.
                                         """
 
 struct OptimizerMissingError <: Exception