test: mark inversemodel tests as broken

Author: AayushSabharwal

test/downstream/inversemodel.jl

@@ -148,19 +148,27 @@ sol = solve(prob, Rodas5P())
 Sf, simplified_sys = Blocks.get_sensitivity_function(model, :y) # This should work without providing an operating opint containing a dummy derivative
 x, _ = ModelingToolkit.get_u0_p(simplified_sys, op)
 p = ModelingToolkit.MTKParameters(simplified_sys, op)
-matrices1 = Sf(x, p, 0)
-matrices2, _ = Blocks.get_sensitivity(model, :y; op) # Test that we get the same result when calling the higher-level API
-@test_broken matrices1.f_x ≈ matrices2.A[1:7, 1:7]
-nsys = get_named_sensitivity(model, :y; op) # Test that we get the same result when calling an even higher-level API
-@test matrices2.A ≈ nsys.A
+# If this somehow passes, mention it on
+# https://github.com/SciML/ModelingToolkit.jl/issues/2786
+@test_broken begin
+    matrices1 = Sf(x, p, 0)
+    matrices2, _ = Blocks.get_sensitivity(model, :y; op) # Test that we get the same result when calling the higher-level API
+    @test matrices1.f_x ≈ matrices2.A[1:7, 1:7]
+    nsys = get_named_sensitivity(model, :y; op) # Test that we get the same result when calling an even higher-level API
+    @test matrices2.A ≈ nsys.A
+end
 
 # Test the same thing for comp sensitivities
 
 Sf, simplified_sys = Blocks.get_comp_sensitivity_function(model, :y) # This should work without providing an operating opint containing a dummy derivative
 x, _ = ModelingToolkit.get_u0_p(simplified_sys, op)
 p = ModelingToolkit.MTKParameters(simplified_sys, op)
-matrices1 = Sf(x, p, 0)
-matrices2, _ = Blocks.get_comp_sensitivity(model, :y; op) # Test that we get the same result when calling the higher-level API
-@test_broken matrices1.f_x ≈ matrices2.A[1:7, 1:7]
-nsys = get_named_comp_sensitivity(model, :y; op) # Test that we get the same result when calling an even higher-level API
-@test matrices2.A ≈ nsys.A
+# If this somehow passes, mention it on
+# https://github.com/SciML/ModelingToolkit.jl/issues/2786
+@test_broken begin
+    matrices1 = Sf(x, p, 0)
+    matrices2, _ = Blocks.get_comp_sensitivity(model, :y; op) # Test that we get the same result when calling the higher-level API
+    @test matrices1.f_x ≈ matrices2.A[1:7, 1:7]
+    nsys = get_named_comp_sensitivity(model, :y; op) # Test that we get the same result when calling an even higher-level API
+    @test matrices2.A ≈ nsys.A
+end