fix tests again

Author: amontoison

src/enzyme.jl

@@ -148,20 +148,18 @@ end
 @init begin
   @require Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9" begin
 
-    import Enzyme: Const, Reverse, Forward, Duplicated, DuplicatedNoNeed
-
     function ADNLPModels.gradient(::EnzymeReverseADGradient, f, x)
       g = similar(x)
-      Enzyme.gradient!(Reverse, g, Const(f), x)
+      Enzyme.gradient!(Enzyme.Reverse, g, Enzyme.Const(f), x)
       return g
     end
 
     function ADNLPModels.gradient!(::EnzymeReverseADGradient, g, f, x)
-      Enzyme.autodiff(Reverse, Const(f), Active, Duplicated(x, g))
+      Enzyme.autodiff(Enzyme.Reverse, Enzyme.Const(f), Enzyme.Active, Enzyme.Duplicated(x, g))
       return g
     end
 
-    jacobian(::EnzymeReverseADJacobian, f, x) = Enzyme.jacobian(Reverse, f, x)
+    jacobian(::EnzymeReverseADJacobian, f, x) = Enzyme.jacobian(Enzyme.Reverse, f, x)
 
     function hessian(::EnzymeReverseADHessian, f, x)
       seed = similar(x)
@@ -170,32 +168,32 @@ end
       tmp = similar(x)
       for i in 1:length(x)
         seed[i] = one(eltype(seed))
-        Enzyme.hvp!(tmp, Const(f), x, seed)
+        Enzyme.hvp!(tmp, Enzyme.Const(f), x, seed)
         hess[:, i] .= tmp
         seed[i] = zero(eltype(seed))
       end
       return hess
     end
 
     function Jprod!(b::EnzymeReverseADJprod, Jv, c!, x, v, ::Val)
-      Enzyme.autodiff(Enzyme.Forward, Const(c!), Duplicated(b.x, Jv), Duplicated(x, v))
+      Enzyme.autodiff(Enzyme.Forward, Enzyme.Const(c!), Enzyme.Duplicated(b.x, Jv), Enzyme.Duplicated(x, v))
       return Jv
     end
 
     function Jtprod!(b::EnzymeReverseADJtprod, Jtv, c!, x, v, ::Val)
-      Enzyme.autodiff(Reverse, Const(c!), Duplicated(b.x, Jtv), Duplicated(x, v))
+      Enzyme.autodiff(Enzyme.Reverse, Enzyme.Const(c!), Enzyme.Duplicated(b.x, Jtv), Enzyme.Duplicated(x, v))
       return Jtv
     end
 
     function Hvprod!(b::EnzymeReverseADHvprod, Hv, x, v, f, args...)
       # What to do with args?
       Enzyme.autodiff(
-        Forward,
-        Const(Enzyme.gradient!),
-        Const(Reverse),
-        DuplicatedNoNeed(b.grad, Hv),
-        Const(f),
-        Duplicated(x, v),
+        Enzyme.Forward,
+        Enzyme.Const(Enzyme.gradient!),
+        Enzyme.Const(Enzyme.Reverse),
+        Enzyme.DuplicatedNoNeed(b.grad, Hv),
+        Enzyme.Const(f),
+        Enzyme.Duplicated(x, v),
       )
       return Hv
     end
@@ -211,13 +209,13 @@ end
       obj_weight::Real = one(eltype(x)),
     )
       Enzyme.autodiff(
-        Forward,
-        Const(Enzyme.gradient!),
-        Const(Reverse),
-        DuplicatedNoNeed(b.grad, Hv),
-        Const(ℓ),
-        Duplicated(x, v),
-        Const(y),
+        Enzyme.Forward,
+        Enzyme.Const(Enzyme.gradient!),
+        Enzyme.Const(Enzyme.Reverse),
+        Enzyme.DuplicatedNoNeed(b.grad, Hv),
+        Enzyme.Const(ℓ),
+        Enzyme.Duplicated(x, v),
+        Enzyme.Const(y),
       )
 
       return Hv
@@ -233,13 +231,13 @@ end
       obj_weight::Real = one(eltype(x)),
     )
       Enzyme.autodiff(
-        Forward,
-        Const(Enzyme.gradient!),
-        Const(Reverse),
-        DuplicatedNoNeed(b.grad, Hv),
-        Const(f),
-        Duplicated(x, v),
-        Const(y),
+        Enzyme.Forward,
+        Enzyme.Const(Enzyme.gradient!),
+        Enzyme.Const(Enzyme.Reverse),
+        Enzyme.DuplicatedNoNeed(b.grad, Hv),
+        Enzyme.Const(f),
+        Enzyme.Duplicated(x, v),
+        Enzyme.Const(y),
       )
       return Hv
     end
@@ -264,7 +262,7 @@ end
 
         # b.compressed_jacobian is just a vector Jv here
         # We don't use the vector mode
-        Enzyme.autodiff(Enzyme.Forward, Const(c!), Duplicated(b.buffer, b.compressed_jacobian), Duplicated(x, b.v))
+        Enzyme.autodiff(Enzyme.Forward, Enzyme.Const(c!), Enzyme.Duplicated(b.buffer, b.compressed_jacobian), Enzyme.Duplicated(x, b.v))
 
         # Update the columns of the Jacobian that have the color `icol`
         decompress_single_color!(A, b.compressed_jacobian, icol, b.result_coloring)