fix: propagate iip of parent problem to InitializationProblem

Author: AayushSabharwal

src/systems/problem_utils.jl

@@ -867,7 +867,7 @@ denotes whether the `SciMLProblem` being constructed is in implicit DAE form (`D
 All other keyword arguments are forwarded to `InitializationProblem`.
 """
 function maybe_build_initialization_problem(
-        sys::AbstractSystem, op::AbstractDict, u0map, pmap, t, defs,
+        sys::AbstractSystem, iip, op::AbstractDict, u0map, pmap, t, defs,
         guesses, missing_unknowns; implicit_dae = false, u0_constructor = identity,
         p_constructor = identity, floatT = Float64, initialization_eqs = [],
         use_scc = true, kwargs...)
@@ -877,7 +877,7 @@ function maybe_build_initialization_problem(
         t = zero(floatT)
     end
 
-    initializeprob = ModelingToolkit.InitializationProblem{true, SciMLBase.FullSpecialize}(
+    initializeprob = ModelingToolkit.InitializationProblem{iip}(
         sys, t, u0map, pmap; guesses, initialization_eqs,
         use_scc, u0_constructor, p_constructor, kwargs...)
     if state_values(initializeprob) !== nothing
@@ -1105,7 +1105,8 @@ function process_SciMLProblem(
 
     if build_initializeprob
         kws = maybe_build_initialization_problem(
-            sys, op, u0map, pmap, t, defs, guesses, missing_unknowns;
+            sys, constructor <: SciMLBase.AbstractSciMLFunction{true},
+            op, u0map, pmap, t, defs, guesses, missing_unknowns;
             implicit_dae, warn_initialize_determined, initialization_eqs,
             eval_expression, eval_module, fully_determined,
             warn_cyclic_dependency, check_units = check_initialization_units,

test/initializationsystem.jl

@@ -1611,3 +1611,16 @@ end
         [g => 1.0]; guesses = [y => 1.0, λ => 1.0])
     @test !ModelingToolkit.is_split(prob.f.initialization_data.initializeprob.f.sys)
 end
+
+@testset "`InitializationProblem` retains `iip` of parent" begin
+    @parameters g
+    @variables x(t) y(t) [state_priority = 10] λ(t)
+    eqs = [D(D(x)) ~ λ * x
+           D(D(y)) ~ λ * y - g
+           x^2 + y^2 ~ 1]
+    @mtkbuild pend = ODESystem(eqs, t)
+    prob = ODEProblem(pend, SA[x => 1.0, D(x) => 0.0], (0.0, 1.0),
+        SA[g => 1.0]; guesses = [y => 1.0, λ => 1.0])
+    @test !SciMLBase.isinplace(prob)
+    @test !SciMLBase.isinplace(prob.f.initialization_data.initializeprob)
+end