renable diaghessian test

Author: oxinabox

test/utils.jl

@@ -25,24 +25,10 @@ end
   xs, y = randn(2,3), rand()
   f34(xs, y) = xs[1] * (sum(xs .^ (1:3)') + y^4)  # non-diagonal Hessian, two arguments
 
-  # Following should work once we workout what ForwardDiff should do when `Float64` is called on a `Dual`
-  # https://github.com/JuliaDiff/ForwardDiff.jl/pull/538
-  # else might need a custom overload of `(;;ChainRulesCore.ProjectTo)(::Dual)`
-  # When fixed uncomment  the below and delete the broken function
-  #==
   dx, dy = diaghessian(f34, xs, y)
   @test size(dx) == size(xs)
   @test vec(dx) ≈ diag(hessian(x -> f34(x,y), xs))
   @test dy ≈ hessian(y -> f34(xs,y), y)
-  ==#  
-  function broken()
-    dx, dy = diaghessian(f34, xs, y) # This fails becase ProjectTo can't project a Dual onto a Float
-    c1 = size(dx) == size(xs)
-    c2 = vec(dx) ≈ diag(hessian(x -> f34(x,y), xs))
-    c3 = dy ≈ hessian(y -> f34(xs,y), y)
-    return all([c1, c2, c3])
-  end
-  @test_broken broken()
 
   zs = randn(7,13)  # test chunk mode
   @test length(zs) > ForwardDiff.DEFAULT_CHUNK_THRESHOLD