more fixes

Author: Vaibhavdixit02

lib/OptimizationManopt/src/OptimizationManopt.jl

@@ -328,7 +328,8 @@ end
 ## Optimization.jl stuff
 function SciMLBase.requiresgradient(opt::Union{
         GradientDescentOptimizer, ConjugateGradientDescentOptimizer,
-        QuasiNewtonOptimizer, ConvexBundleOptimizer, FrankWolfeOptimizer})
+        QuasiNewtonOptimizer, ConvexBundleOptimizer, FrankWolfeOptimizer,
+        AdaptiveRegularizationCubicOptimizer, TrustRegionsOptimizer})
     true
 end
 function SciMLBase.requireshessian(opt::Union{

lib/OptimizationNLPModels/Project.toml

@@ -19,10 +19,11 @@ julia = "1.9"
 [extras]
 NLPModelsTest = "7998695d-6960-4d3a-85c4-e1bceb8cd856"
 OptimizationOptimJL = "36348300-93cb-4f02-beb5-3c3902f8871e"
+ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
 OptimizationMOI = "fd9f6733-72f4-499f-8506-86b2bdd0dea1"
 
 [targets]
-test = ["Test", "NLPModelsTest", "OptimizationOptimJL", "Zygote", "Ipopt", "OptimizationMOI"]
+test = ["Test", "NLPModelsTest", "OptimizationOptimJL", "ReverseDiff", "Zygote", "Ipopt", "OptimizationMOI"]

lib/OptimizationNLPModels/test/runtests.jl

@@ -1,4 +1,5 @@
 using OptimizationNLPModels, Optimization, NLPModelsTest, Ipopt, OptimizationMOI, Zygote,
+      ReverseDiff,
       OptimizationOptimJL
 using Test
 

lib/OptimizationOptimJL/test/runtests.jl

@@ -1,6 +1,6 @@
 using OptimizationOptimJL,
-      OptimizationOptimJL.Optim, Optimization, ForwardDiff, Zygote, ReverseDiff.
-Random, ModelingToolkit, Optimization.OptimizationBase.DifferentiationInterface
+      OptimizationOptimJL.Optim, Optimization, ForwardDiff, Zygote, ReverseDiff,
+      Random, ModelingToolkit, Optimization.OptimizationBase.DifferentiationInterface
 using Test
 
 struct CallbackTester

lib/OptimizationPRIMA/test/runtests.jl

@@ -1,4 +1,4 @@
-using OptimizationPRIMA, Optimization, ForwardDiff, ModelingToolkit
+using OptimizationPRIMA, Optimization, ForwardDiff, ModelingToolkit, ReverseDiff
 using Test
 
 @testset "OptimizationPRIMA.jl" begin

test/minibatch.jl

@@ -58,9 +58,9 @@ optfun = OptimizationFunction(loss_adjoint,
     Optimization.AutoZygote())
 optprob = OptimizationProblem(optfun, pp, train_loader)
 
-sol = Optimization.solve(optprob,
+res1 = Optimization.solve(optprob,
     Optimization.Sophia(; η = 0.5,
-        λ = 0.0),
+        λ = 0.0), callback = callback,
     maxiters = 1000)
 @test 10res1.objective < l1