test: more test fixes

Author: avik-pal

Project.toml

@@ -81,7 +81,7 @@ LeastSquaresOptim = "0.8.5"
 LineSearches = "7.2"
 LinearAlgebra = "1.10"
 LinearSolve = "2.30"
-MINPACK = "=1.2"
+MINPACK = "1.2"
 MaybeInplace = "0.1.3"
 ModelingToolkit = "9.15.0"
 NLSolvers = "0.5"

lib/SciMLJacobianOperators/Project.toml

@@ -4,7 +4,6 @@ authors = ["Avik Pal <[email protected]> and contributors"]
 version = "0.1.0"
 
 [deps]
-ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
 ConcreteStructs = "2569d6c7-a4a2-43d3-a901-331e8e4be471"
 ConstructionBase = "187b0558-2788-49d3-abe0-74a17ed4e7c9"
 DifferentiationInterface = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
@@ -15,7 +14,6 @@ SciMLOperators = "c0aeaf25-5076-4817-a8d5-81caf7dfa961"
 Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 
 [compat]
-ADTypes = "1.8.1"
 ConcreteStructs = "0.2.3"
 ConstructionBase = "1.5"
 DifferentiationInterface = "0.5"

lib/SciMLJacobianOperators/src/SciMLJacobianOperators.jl

@@ -1,6 +1,5 @@
 module SciMLJacobianOperators
 
-using ADTypes: ADTypes
 using ConcreteStructs: @concrete
 using ConstructionBase: ConstructionBase
 using DifferentiationInterface: DifferentiationInterface
@@ -117,8 +116,8 @@ function JacobianOperator(prob::AbstractNonlinearProblem, fu, u; jvp_autodiff =
     vjp_op = prepare_vjp(skip_vjp, prob, f, u, fu; autodiff = vjp_autodiff)
     jvp_op = prepare_jvp(skip_jvp, prob, f, u, fu; autodiff = jvp_autodiff)
 
-    output_cache = similar(fu, T)
-    input_cache = similar(u, T)
+    output_cache = fu isa Number ? T(fu) : similar(fu, T)
+    input_cache = u isa Number ? T(u) : similar(u, T)
 
     return JacobianOperator{iip, T}(
         JVP(), jvp_op, vjp_op, (length(fu), length(u)), output_cache, input_cache)
@@ -290,12 +289,6 @@ function prepare_vjp(::Val{false}, prob::AbstractNonlinearProblem,
 
     @assert autodiff!==nothing "`vjp_autodiff` must be provided if `f` doesn't have \
                                 analytic `vjp` or `jac`."
-
-    if ADTypes.mode(autodiff) isa ADTypes.ForwardMode
-        @warn "AD Backend: $(autodiff) is a Forward Mode backend. Computing VJPs using \
-               this will be slow!"
-    end
-
     # TODO: Once DI supports const params we can use `p`
     fₚ = SciMLBase.JacobianWrapper{SciMLBase.isinplace(f)}(f, prob.p)
     if SciMLBase.isinplace(f)
@@ -337,12 +330,6 @@ function prepare_jvp(::Val{false}, prob::AbstractNonlinearProblem,
 
     @assert autodiff!==nothing "`jvp_autodiff` must be provided if `f` doesn't have \
                                 analytic `vjp` or `jac`."
-
-    if ADTypes.mode(autodiff) isa ADTypes.ReverseMode
-        @warn "AD Backend: $(autodiff) is a Reverse Mode backend. Computing JVPs using \
-               this will be slow!"
-    end
-
     # TODO: Once DI supports const params we can use `p`
     fₚ = SciMLBase.JacobianWrapper{SciMLBase.isinplace(f)}(f, prob.p)
     if SciMLBase.isinplace(f)

lib/SciMLJacobianOperators/test/runtests.jl

@@ -0,0 +1 @@
+

src/NonlinearSolve.jl

@@ -40,8 +40,8 @@ using Preferences: Preferences, @load_preference, @set_preferences!
 using RecursiveArrayTools: recursivecopy!, recursivefill!
 using SciMLBase: AbstractNonlinearAlgorithm, JacobianWrapper, AbstractNonlinearProblem,
                  AbstractSciMLOperator, _unwrap_val, has_jac, isinplace, NLStats
-using SciMLJacobianOperators: JacobianOperator, VecJacOperator, JacVecOperator,
-                              StatefulJacobianOperator
+using SciMLJacobianOperators: AbstractJacobianOperator, JacobianOperator, VecJacOperator,
+                              JacVecOperator, StatefulJacobianOperator
 using SparseArrays: AbstractSparseMatrix, SparseMatrixCSC
 using SparseDiffTools: SparseDiffTools, AbstractSparsityDetection,
                        ApproximateJacobianSparsity, JacPrototypeSparsityDetection,

src/utils.jl

@@ -48,6 +48,7 @@ end
     return deepcopy(x)
 end
 @inline __maybe_unaliased(x::AbstractNonlinearSolveOperator, alias::Bool) = x
+@inline __maybe_unaliased(x::AbstractJacobianOperator, alias::Bool) = x
 
 @inline __cond(J::AbstractMatrix) = cond(J)
 @inline __cond(J::SVector) = __cond(Diagonal(MVector(J)))

test/runtests.jl

@@ -10,8 +10,8 @@ const RETESTITEMS_NWORKER_THREADS = parse(Int,
     get(ENV, "RETESTITEMS_NWORKER_THREADS",
         string(max(Hwloc.num_virtual_cores() ÷ RETESTITEMS_NWORKERS, 1))))
 
-@info "Running tests for group: $LUXLIB_TEST_GROUP with $RETESTITEMS_NWORKERS workers"
+@info "Running tests for group: $(GROUP) with $(RETESTITEMS_NWORKERS) workers"
 
 ReTestItems.runtests(NonlinearSolve; tags = (GROUP == "all" ? nothing : [Symbol(GROUP)]),
-    nworkers = RETESTITEMS_NWORKERS,
-    nworker_threads = RETESTITEMS_NWORKER_THREADS, testitem_timeout = 3600, retries=4)
+    nworkers = RETESTITEMS_NWORKERS, nworker_threads = RETESTITEMS_NWORKER_THREADS,
+    testitem_timeout = 3600, retries = 4)