Skip to content

Make length of Partials known at compile time in ForwardDiff overloads #727

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 3 commits into
base: main
Choose a base branch
from
Open

Make length of Partials known at compile time in ForwardDiff overloads #727

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
cf2edd8
make sure that Partials length is known
jClugstor Aug 14, 2025
dd049b0
add Dual problem JET tests
jClugstor Aug 15, 2025
010269e
Update test/nopre/jet.jl
ChrisRackauckas Aug 15, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions ext/LinearSolveForwardDiffExt.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ const DualBLinearProblem = LinearProblem{
const DualAbstractLinearProblem = Union{
DualLinearProblem, DualALinearProblem, DualBLinearProblem}

LinearSolve.@concrete mutable struct DualLinearCache{DT <: Dual}
LinearSolve.@concrete mutable struct DualLinearCache{DT}
linear_cache

partials_A
Expand Down Expand Up @@ -113,10 +113,10 @@ function linearsolve_dual_solution(
end

function linearsolve_dual_solution(u::AbstractArray, partials,
cache::DualLinearCache{DT}) where {DT}
cache::DualLinearCache{DT}) where {T, V, N, DT <: Dual{T,V,N}}
# Handle single-level duals for arrays
partials_list = RecursiveArrayTools.VectorOfArray(partials)
return map(((uᵢ, pᵢ),) -> DT(uᵢ, Partials(Tuple(pᵢ))),
return map(((uᵢ, pᵢ),) -> DT(uᵢ, Partials{N,V}(NTuple{N,V}(pᵢ))),
zip(u, partials_list[i, :] for i in 1:length(partials_list.u[1])))
end

Expand Down
22 changes: 21 additions & 1 deletion test/nopre/jet.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
using LinearSolve, RecursiveFactorization, LinearAlgebra, SparseArrays, Test
using LinearSolve, ForwardDiff, RecursiveFactorization, LinearAlgebra, SparseArrays, Test
using JET

# Dense problem setup
Expand All @@ -22,6 +22,18 @@ prob_sparse = LinearProblem(A_sparse, b)
A_sparse_spd = sparse(A_spd)
prob_sparse_spd = LinearProblem(A_sparse_spd, b)

# Dual problem set up
function h(p)
(A = [p[1] p[2]+1 p[2]^3;
3*p[1] p[1]+5 p[2] * p[1]-4;
p[2]^2 9*p[1] p[2]],
b = [p[1] + 1, p[2] * 2, p[1]^2])
end

A, b = h([ForwardDiff.Dual(5.0, 1.0, 0.0), ForwardDiff.Dual(5.0, 0.0, 1.0)])

dual_prob = LinearProblem(A, b)

@testset "JET Tests for Dense Factorizations" begin
# Working tests - these pass JET optimization checks
JET.@test_opt init(prob, nothing)
Expand Down Expand Up @@ -108,3 +120,11 @@ end
JET.@test_opt solve(prob) broken=true
JET.@test_opt solve(prob_sparse) broken=true
end

@testset "JET Tests for creating Dual solutions" begin
# Make sure there's no runtime dispatch when making solutions of Dual problems
dual_cache = init(prob)
ext = Base.get_extension(LinearSolve, :LinearSolveForwardDiffExt)
JET.@test_opt ext.linearsolve_dual_solution(
[1.0, 1.0, 1.0], [[1.0, 1.0, 1.0], [1.0, 1.0, 1.0]], dual_cache )
end
Loading