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Don't use custom tags #411

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merged 1 commit into from
Apr 18, 2024
Merged

Don't use custom tags #411

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2 changes: 1 addition & 1 deletion ext/NonlinearSolveNLSolversExt.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@

if autodiff_concrete === :forwarddiff
fj_scalar = @closure (Jx, x) -> begin
T = typeof(NonlinearSolve.NonlinearSolveTag())
T = typeof(ForwardDiff.Tag(prob.f, eltype(x)))

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Added line #L37 was not covered by tests
x_dual = ForwardDiff.Dual{T}(x, one(x))
y = prob.f(x_dual, prob.p)
return ForwardDiff.value(y), ForwardDiff.extract_derivative(T, y)
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10 changes: 1 addition & 9 deletions src/internal/helpers.jl
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Expand Up @@ -30,13 +30,6 @@ function evaluate_f!!(f::NonlinearFunction{iip}, fu, u, p) where {iip}
end

# AutoDiff Selection Functions
struct NonlinearSolveTag end

function ForwardDiff.checktag(::Type{<:ForwardDiff.Tag{<:NonlinearSolveTag, <:T}},
f::F, x::AbstractArray{T}) where {T, F}
return true
end

function get_concrete_forward_ad(
autodiff::Union{ADTypes.AbstractForwardMode, ADTypes.AbstractFiniteDifferencesMode},
prob, sp::Val{test_sparse} = True, args...; kwargs...) where {test_sparse}
Expand All @@ -62,8 +55,7 @@ function get_concrete_forward_ad(
ad = if !ForwardDiff.can_dual(eltype(prob.u0)) # Use Finite Differencing
use_sparse_ad ? AutoSparseFiniteDiff() : AutoFiniteDiff()
else
tag = ForwardDiff.Tag(NonlinearSolveTag(), eltype(prob.u0))
(use_sparse_ad ? AutoSparseForwardDiff : AutoForwardDiff)(; tag)
(use_sparse_ad ? AutoSparseForwardDiff : AutoForwardDiff)()
end
return ad
end
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8 changes: 4 additions & 4 deletions src/internal/operators.jl
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Expand Up @@ -109,10 +109,10 @@ function JacobianOperator(prob::AbstractNonlinearProblem, fu, u; jvp_autodiff =
if jvp_autodiff isa AutoForwardDiff || jvp_autodiff isa AutoPolyesterForwardDiff
if iip
# FIXME: Technically we should propagate the tag but ignoring that for now
cache1 = Dual{typeof(ForwardDiff.Tag(NonlinearSolveTag(), eltype(u))),
eltype(u), 1}.(similar(u), ForwardDiff.Partials.(tuple.(u)))
cache2 = Dual{typeof(ForwardDiff.Tag(NonlinearSolveTag(), eltype(fu))),
eltype(fu), 1}.(similar(fu), ForwardDiff.Partials.(tuple.(fu)))
cache1 = Dual{typeof(ForwardDiff.Tag(uf, eltype(u))), eltype(u),
1}.(similar(u), ForwardDiff.Partials.(tuple.(u)))
cache2 = Dual{typeof(ForwardDiff.Tag(uf, eltype(fu))), eltype(fu),
1}.(similar(fu), ForwardDiff.Partials.(tuple.(fu)))
@closure (Jv, v, u, p) -> auto_jacvec!(Jv, uf, u, v, cache1, cache2)
else
@closure (v, u, p) -> auto_jacvec(uf, u, v)
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