Enable remaining enzyme test (#2442)

Author: wsmoses

Project.toml

@@ -46,7 +46,7 @@ Functors = "0.4"
 MLUtils = "0.4"
 MacroTools = "0.5"
 Metal = "0.5, 1"
-NNlib = "0.9.14"
+NNlib = "0.9.15"
 OneHotArrays = "0.2.4"
 Optimisers = "0.3.3"
 Preferences = "1"

test/ext_enzyme/enzyme.jl

@@ -6,10 +6,6 @@ using Functors
 using FiniteDifferences
 using CUDA
 
-Enzyme.API.typeWarning!(false) # suppresses a warning with Bilinear https://github.com/EnzymeAD/Enzyme.jl/issues/1341
-Enzyme.API.runtimeActivity!(true) # for Enzyme debugging 
-# Enzyme.Compiler.bitcode_replacement!(false)
-
 _make_zero(x::Union{Number,AbstractArray}) = zero(x)
 _make_zero(x) = x
 make_zero(model) = fmap(_make_zero, model)
@@ -121,6 +117,7 @@ end
         (SkipConnection(Dense(2 => 2), vcat), randn(Float32, 2, 3), "SkipConnection"),
         (Flux.Bilinear((2, 2) => 3), randn(Float32, 2, 1), "Bilinear"),        
         (GRU(3 => 5), randn(Float32, 3, 10), "GRU"),
+        (ConvTranspose((3, 3), 3 => 2, stride=2), rand(Float32, 5, 5, 3, 1), "ConvTranspose"),
     ]
 
     for (model, x, name) in models_xs
@@ -155,32 +152,3 @@ end
         end
     end
 end
-
-@testset "Broken Models" begin
-    function loss(model, x)
-        Flux.reset!(model)
-        sum(model(x))
-    end
-
-    device = Flux.get_device()
-
-    models_xs = [
-        # Pending https://github.com/FluxML/NNlib.jl/issues/565 
-        (ConvTranspose((3, 3), 3 => 2, stride=2), rand(Float32, 5, 5, 3, 1), "ConvTranspose"),
-        ]
-
-    for (model, x, name) in models_xs
-        @testset "check grad $name" begin
-            println("testing $name")
-            broken = false
-            try
-                test_enzyme_grad(loss, model, x)
-            catch e
-                println(e)
-                broken = true
-            end
-            @test broken
-        end
-    end
-end
-