test: enable runtime activity for now

test/enzyme.jl

@@ -177,47 +177,39 @@ Enzyme.autodiff(Reverse, f3, Duplicated(copy(A), dA), Duplicated(copy(b1), db1),
 A = rand(n, n);
 dA = zeros(n, n);
 b1 = rand(n);
-for alg in (
+
+function fnice(A, b, alg)
+    prob = LinearProblem(A, b)
+    sol1 = solve(prob, alg)
+    return sum(sol1.u)
+end
+
+@testset for alg in (
     LUFactorization(),
     RFLUFactorization()    # KrylovJL_GMRES(), fails
 )
-    @show alg
-    function fb(b)
-        prob = LinearProblem(A, b)
-
-        sol1 = solve(prob, alg)
+    fb_closure = b -> fnice(A, b, alg)
 
-        sum(sol1.u)
-    end
-    fb(b1)
-
-    fd_jac = FiniteDiff.finite_difference_jacobian(fb, b1) |> vec
+    fd_jac = FiniteDiff.finite_difference_jacobian(fb_closure, b1) |> vec
     @show fd_jac
 
     en_jac = map(onehot(b1)) do db1
-        eres = Enzyme.autodiff(Forward, fb, Duplicated(copy(b1), db1))
-        eres[1]
+        return only(Enzyme.autodiff(set_runtime_activity(Forward), fnice,
+            Const(A), Duplicated(b1, db1), Const(alg)))
     end |> collect
     @show en_jac
 
     @test en_jac≈fd_jac rtol=1e-4
 
-    function fA(A)
-        prob = LinearProblem(A, b1)
-
-        sol1 = solve(prob, alg)
+    fA_closure = A -> fnice(A, b1, alg)
 
-        sum(sol1.u)
-    end
-    fA(A)
-
-    fd_jac = FiniteDiff.finite_difference_jacobian(fA, A) |> vec
+    fd_jac = FiniteDiff.finite_difference_jacobian(fA_closure, A) |> vec
     @show fd_jac
 
     en_jac = map(onehot(A)) do dA
-        eres = Enzyme.autodiff(Forward, fA, Duplicated(copy(A), dA))
-        eres[1]
-    end |> collect
+                 return only(Enzyme.autodiff(set_runtime_activity(Forward), fnice,
+                     Duplicated(A, dA), Const(b1), Const(alg)))
+             end |> collect |> (x -> reshape(x, n, n))
     @show en_jac
 
     @test en_jac≈fd_jac rtol=1e-4