Mark tests broken on v1.6 as broken on v1.6

SciML · Oct 5, 2023 · a7ef698 · a7ef698
1 parent eddf8c4
commit a7ef698
Showing 1 changed file with 34 additions and 32 deletions.
diff --git a/test/ADtests.jl b/test/ADtests.jl
@@ -67,42 +67,44 @@ optprob.cons_h(H3, x0)
 G2 = Array{Float64}(undef, 2)
 H2 = Array{Float64}(undef, 2, 2)
 
-optf = OptimizationFunction(rosenbrock, Optimization.AutoEnzyme(), cons = cons)
-optprob = Optimization.instantiate_function(optf, x0, Optimization.AutoEnzyme(),
-    nothing, 1)
-optprob.grad(G2, x0)
-@test G1 == G2
-optprob.hess(H2, x0)
-@test H1 == H2
-res = Array{Float64}(undef, 1)
-optprob.cons(res, x0)
-@test res == [0.0]
-J = Array{Float64}(undef, 2)
-optprob.cons_j(J, [5.0, 3.0])
-@test J == [10.0, 6.0]
-H3 = [Array{Float64}(undef, 2, 2)]
-optprob.cons_h(H3, x0)
-@test H3 == [[2.0 0.0; 0.0 2.0]]
+if VERSION >= v"1.9"
+    optf = OptimizationFunction(rosenbrock, Optimization.AutoEnzyme(), cons = cons)
+    optprob = Optimization.instantiate_function(optf, x0, Optimization.AutoEnzyme(),
+        nothing, 1)
+    optprob.grad(G2, x0)
+    @test G1 == G2
+    optprob.hess(H2, x0)
+    @test H1 == H2
+    res = Array{Float64}(undef, 1)
+    optprob.cons(res, x0)
+    @test res == [0.0]
+    J = Array{Float64}(undef, 2)
+    optprob.cons_j(J, [5.0, 3.0])
+    @test J == [10.0, 6.0]
+    H3 = [Array{Float64}(undef, 2, 2)]
+    optprob.cons_h(H3, x0)
+    @test H3 == [[2.0 0.0; 0.0 2.0]]
 
 G2 = Array{Float64}(undef, 2)
 H2 = Array{Float64}(undef, 2, 2)
 
-optf = OptimizationFunction(rosenbrock, Optimization.AutoEnzyme(), cons = con2_c)
-optprob = Optimization.instantiate_function(optf, x0, Optimization.AutoEnzyme(),
-    nothing, 2)
-optprob.grad(G2, x0)
-@test G1 == G2
-optprob.hess(H2, x0)
-@test H1 == H2
-res = Array{Float64}(undef, 2)
-optprob.cons(res, x0)
-@test res == [0.0, 0.0]
-J = Array{Float64}(undef, 2, 2)
-optprob.cons_j(J, [5.0, 3.0])
-@test all(isapprox(J, [10.0 6.0; -0.149013 -0.958924]; rtol = 1e-3))
-H3 = [Array{Float64}(undef, 2, 2), Array{Float64}(undef, 2, 2)]
-optprob.cons_h(H3, x0)
-H3 == [[2.0 0.0; 0.0 2.0], [-0.0 1.0; 1.0 0.0]]
+    optf = OptimizationFunction(rosenbrock, Optimization.AutoEnzyme(), cons = con2_c)
+    optprob = Optimization.instantiate_function(optf, x0, Optimization.AutoEnzyme(),
+        nothing, 2)
+    optprob.grad(G2, x0)
+    @test G1 == G2
+    optprob.hess(H2, x0)
+    @test H1 == H2
+    res = Array{Float64}(undef, 2)
+    optprob.cons(res, x0)
+    @test res == [0.0, 0.0]
+    J = Array{Float64}(undef, 2, 2)
+    optprob.cons_j(J, [5.0, 3.0])
+    @test all(isapprox(J, [10.0 6.0; -0.149013 -0.958924]; rtol = 1e-3))
+    H3 = [Array{Float64}(undef, 2, 2), Array{Float64}(undef, 2, 2)]
+    optprob.cons_h(H3, x0)
+    @test H3 == [[2.0 0.0; 0.0 2.0], [-0.0 1.0; 1.0 0.0]]
+end
 
 G2 = Array{Float64}(undef, 2)
 H2 = Array{Float64}(undef, 2, 2)