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Opt out from generic dual number handling for SparspakFactorization #838

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Opt out from generic dual number handling for SparspakFactorization #838

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5 changes: 5 additions & 0 deletions ext/LinearSolveForwardDiffExt.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -200,6 +200,11 @@ function SciMLBase.init(prob::DualAbstractLinearProblem, alg::GenericLUFactoriza
return __init(prob, alg, args...; kwargs...)
end

# Opt out for SparspakFactorization
function SciMLBase.init(prob::DualAbstractLinearProblem, alg::SparspakFactorization, args...; kwargs...)
return __init(prob, alg, args...; kwargs...)
end

function SciMLBase.init(prob::DualAbstractLinearProblem, alg::DefaultLinearSolver, args...; kwargs...)
if alg.alg === DefaultAlgorithmChoice.GenericLUFactorization
return __init(prob, alg, args...; kwargs...)
Expand Down
10 changes: 8 additions & 2 deletions test/forwarddiff_overloads.jl
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Expand Up @@ -3,6 +3,7 @@ using ForwardDiff
using Test
using SparseArrays
using ComponentArrays
using Sparspak

function h(p)
(A = [p[1] p[2]+1 p[2]^3;
Expand Down Expand Up @@ -188,7 +189,6 @@ backslash_x_p = A \ b

@test ≈(overload_x_p, backslash_x_p, rtol = 1e-9)


# Test that GenericLU doesn't create a DualLinearCache
A, b = h([ForwardDiff.Dual(5.0, 1.0, 0.0), ForwardDiff.Dual(5.0, 0.0, 1.0)])

Expand All @@ -197,6 +197,12 @@ prob = LinearProblem(A, b)

@test init(prob) isa LinearSolve.LinearCache

# Test that SparspakFactorization doesn't create a DualLinearCache
A, b = h([ForwardDiff.Dual(5.0, 1.0, 0.0), ForwardDiff.Dual(5.0, 0.0, 1.0)])

prob = LinearProblem(sparse(A), b)
@test init(prob, SparspakFactorization()) isa LinearSolve.LinearCache

# Test ComponentArray with ForwardDiff (Issue SciML/DifferentialEquations.jl#1110)
# This tests that ArrayInterface.restructure preserves ComponentArray structure

Expand Down Expand Up @@ -234,4 +240,4 @@ grad = ForwardDiff.gradient(component_linsolve, p_test)
@test grad isa Vector
@test length(grad) == 2
@test !any(isnan, grad)
@test !any(isinf, grad)
@test !any(isinf, grad)
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