Add SciML integration tests #2593
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Your PR requires formatting changes to meet the project's style guidelines. Click here to view the suggested changes.diff --git a/test/integration/SciML/runtests.jl b/test/integration/SciML/runtests.jl
index 7c655e40..631ab6a9 100644
--- a/test/integration/SciML/runtests.jl
+++ b/test/integration/SciML/runtests.jl
@@ -9,47 +9,49 @@ using LinearSolve, LinearAlgebra
du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
- _saveat = SA[0.0,0.25,0.5,0.75,1.0,1.25,1.5,1.75,2.0,2.25,2.5,2.75,3.0]
+ _saveat = SA[0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0]
function f_dt(y::Array{Float64}, u0::Array{Float64})
tspan = (0.0, 3.0)
prob = ODEProblem{true, SciMLBase.FullSpecialize}(lorenz!, u0, tspan)
- sol = DiffEqBase.solve(prob, Tsit5(), saveat = _saveat, sensealg = DiffEqBase.SensitivityADPassThrough(), abstol=1e-12, reltol=1e-12)
- y .= sol[1,:]
+ sol = DiffEqBase.solve(prob, Tsit5(), saveat = _saveat, sensealg = DiffEqBase.SensitivityADPassThrough(), abstol = 1.0e-12, reltol = 1.0e-12)
+ y .= sol[1, :]
return nothing
- end;
+ end
function f_dt(u0)
tspan = (0.0, 3.0)
prob = ODEProblem{true, SciMLBase.FullSpecialize}(lorenz!, u0, tspan)
- sol = DiffEqBase.solve(prob, Tsit5(), saveat = _saveat, sensealg = DiffEqBase.SensitivityADPassThrough(), abstol=1e-12, reltol=1e-12)
- sol[1,:]
- end;
+ sol = DiffEqBase.solve(prob, Tsit5(), saveat = _saveat, sensealg = DiffEqBase.SensitivityADPassThrough(), abstol = 1.0e-12, reltol = 1.0e-12)
+ sol[1, :]
+ end
u0 = [1.0; 0.0; 0.0]
fdj = ForwardDiff.jacobian(f_dt, u0)
- ezj = stack(map(1:3) do i
- d_u0 = zeros(3)
- dy = zeros(13)
- y = zeros(13)
- d_u0[i] = 1.0
- Enzyme.autodiff(Forward, f_dt, Duplicated(y, dy), Duplicated(u0, d_u0));
- dy
- end)
+ ezj = stack(
+ map(1:3) do i
+ d_u0 = zeros(3)
+ dy = zeros(13)
+ y = zeros(13)
+ d_u0[i] = 1.0
+ Enzyme.autodiff(Forward, f_dt, Duplicated(y, dy), Duplicated(u0, d_u0))
+ dy
+ end
+ )
@test ezj ≈ fdj
function f_dt2(u0)
tspan = (0.0, 3.0)
prob = ODEProblem{true, SciMLBase.FullSpecialize}(lorenz!, u0, tspan)
- sol = DiffEqBase.solve(prob, Tsit5(), dt=0.1, saveat = _saveat, sensealg = DiffEqBase.SensitivityADPassThrough(), abstol=1e-12, reltol=1e-12)
- sum(sol[1,:])
+ sol = DiffEqBase.solve(prob, Tsit5(), dt = 0.1, saveat = _saveat, sensealg = DiffEqBase.SensitivityADPassThrough(), abstol = 1.0e-12, reltol = 1.0e-12)
+ sum(sol[1, :])
end
fdg = ForwardDiff.gradient(f_dt2, u0)
d_u0 = zeros(3)
- Enzyme.autodiff(Reverse, f_dt2, Active, Duplicated(u0, d_u0));
+ Enzyme.autodiff(Reverse, f_dt2, Active, Duplicated(u0, d_u0))
@test d_u0 ≈ fdg
end
@@ -61,7 +63,7 @@ struct senseloss0{T}
end
function (f::senseloss0)(u0p)
prob = ODEProblem{true}(odef, u0p[1:1], (0.0, 1.0), u0p[2:2])
- sum(solve(prob, Tsit5(), abstol = 1e-12, reltol = 1e-12, saveat = 0.1))
+ return sum(solve(prob, Tsit5(), abstol = 1.0e-12, reltol = 1.0e-12, saveat = 0.1))
end
@testset "SciMLSensitivity Adjoint Interface" begin
@@ -73,12 +75,12 @@ end
@test du0p ≈ dup
end
- @testset "LinearSolve Adjoints" begin
+@testset "LinearSolve Adjoints" begin
n = 4
- A = rand(n, n);
- dA = zeros(n, n);
- b1 = rand(n);
- db1 = zeros(n);
+ A = rand(n, n)
+ dA = zeros(n, n)
+ b1 = rand(n)
+ db1 = zeros(n)
function f(A, b1; alg = LUFactorization())
prob = LinearProblem(A, b1) |
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #2593 +/- ##
=======================================
Coverage 75.10% 75.10%
=======================================
Files 56 56
Lines 17724 17724
=======================================
Hits 13312 13312
Misses 4412 4412 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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ChrisRackauckas
commented
Sep 19, 2025
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Contributor
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BTW, it looks like this test just regressed in the latest release 😅 |
Member
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https://github.com/EnzymeAD/Enzyme.jl/actions/runs/17889611301/job/50873551207?pr=2593#step:9:11 (only in v1.11)
That's why we need these tests! |
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Yes that's the expected failure from the latest release |
wsmoses
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the above error is now fixed, however now it hits: which I really need an MWE for to figure out/fix |
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approve to see? locally it's just the testset. |
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Author
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yeah I don't know why that case doesn't work with Enzyme inside of a testset, but that is the case 🤷 |
wsmoses
reviewed
Sep 26, 2025
test/integration/SciML/runtests.jl
Outdated
| #@testset "SciMLSensitivity Adjoint Interface" begin | ||
| Enzyme.API.typeWarning!(false) | ||
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||
| odef(du, u, p, t) = du .= u .* p |
Member
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what if instead you put the function defns outside of the testset (but kept the testset)
Contributor
Author
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Seems to work like this locally. Not sure why Enzyme is sensitive here while Zygote isn't but I think it's ignorable. |
Member
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probably closure causing sadness |
Contributor
Author
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done |
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