refactor: remove AutoModelingToolkit

Author: AayushSabharwal

lib/OptimizationBase/Project.toml

@@ -23,8 +23,6 @@ FiniteDiff = "6a86dc24-6348-571c-b903-95158fe2bd41"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 MLDataDevices = "7e8f7934-dd98-4c1a-8fe8-92b47a384d40"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
-ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
-ModelingToolkitBase = "7771a370-6774-4173-bd38-47e70ca0b839"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 SymbolicAnalysis = "4297ee4d-0239-47d8-ba5d-195ecdf594fe"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
@@ -35,8 +33,6 @@ OptimizationFiniteDiffExt = "FiniteDiff"
 OptimizationForwardDiffExt = "ForwardDiff"
 OptimizationMLDataDevicesExt = "MLDataDevices"
 OptimizationMLUtilsExt = "MLUtils"
-OptimizationMTKExt = "ModelingToolkit"
-OptimizationMTKBaseExt = "ModelingToolkitBase"
 OptimizationReverseDiffExt = "ReverseDiff"
 OptimizationSymbolicAnalysisExt = "SymbolicAnalysis"
 OptimizationZygoteExt = "Zygote"
@@ -53,8 +49,6 @@ ForwardDiff = "0.10.26, 1"
 LinearAlgebra = "1.9, 1.10"
 MLDataDevices = "1"
 MLUtils = "0.4"
-ModelingToolkit = "10.23, 11"
-ModelingToolkitBase = "1"
 PDMats = "0.11"
 Reexport = "1.2"
 ReverseDiff = "1.14"

lib/OptimizationBase/src/adtypes.jl

@@ -88,44 +88,6 @@ Hessian is not defined via ForwardDiff.
 """
 AutoForwardDiff
 
-"""
-    AutoModelingToolkit <: AbstractADType
-
-An AbstractADType choice for use in OptimizationFunction for automatically
-generating the unspecified derivative functions. Usage:
-
-```julia
-OptimizationFunction(f, AutoModelingToolkit(); kwargs...)
-```
-
-This uses the [ModelingToolkit.jl](https://github.com/SciML/ModelingToolkit.jl)
-package's `modelingtookitize` functionality to generate the derivatives and other fields of an `OptimizationFunction`.
-This backend creates the symbolic expressions for the objective and its derivatives as well as
-the constraints and their derivatives. Through `structural_simplify`, it enforces simplifications
-that can reduce the number of operations needed to compute the derivatives of the constraints. This automatically
-generates the expression graphs that some solver interfaces through OptimizationMOI like
-[AmplNLWriter.jl](https://github.com/jump-dev/AmplNLWriter.jl) require.
-
-  - Compatible with GPUs
-  - Compatible with Hessian-based optimization
-  - Compatible with Hv-based optimization
-  - Compatible with constraints
-
-Note that only the unspecified derivative functions are defined. For example,
-if a `hess` function is supplied to the `OptimizationFunction`, then the
-Hessian is not generated via ModelingToolkit.
-
-## Constructor
-
-```julia
-AutoModelingToolkit(false, false)
-```
-
-  - `obj_sparse`: to indicate whether the objective hessian is sparse.
-  - `cons_sparse`: to indicate whether the constraints' jacobian and hessian are sparse.
-
-"""
-AutoModelingToolkit
 
 """
     AutoReverseDiff <: AbstractADType

lib/OptimizationOptimJL/test/runtests.jl

@@ -163,7 +163,7 @@ end
     @test 10 * sol.objective < l1
 
     optprob = OptimizationFunction(rosenbrock,
-        OptimizationBase.AutoModelingToolkit(true, false))
+        OptimizationBase.AutoSparse(OptimizationBase.AutoSymbolics()))
     prob = OptimizationProblem(optprob, x0, _p)
     sol = solve(prob, Optim.Newton())
     @test 10 * sol.objective < l1