cleanup

test/ext_enzyme/enzyme.jl

@@ -17,8 +17,8 @@ using Enzyme: Enzyme, Duplicated, Const, Active
         (SkipConnection(Dense(2 => 2), vcat), randn(Float32, 2, 3), "SkipConnection"),
         (Flux.Bilinear((2, 2) => 3), randn(Float32, 2, 1), "Bilinear"),
         (ConvTranspose((3, 3), 3 => 2, stride=2), rand(Float32, 5, 5, 3, 1), "ConvTranspose"),
-        # (first ∘ LayerNorm(2), randn(Float32, 2, 10), "LayerNorm"),
-        # (BatchNorm(2), randn(Float32, 2, 10), "BatchNorm"),
+        (first ∘ LayerNorm(2), randn(Float32, 2, 10), "LayerNorm"),
+        (BatchNorm(2), randn(Float32, 2, 10), "BatchNorm"),
         (first ∘ MultiHeadAttention(16), randn32(16, 20, 2), "MultiHeadAttention"),
     ]
 
@@ -36,11 +36,11 @@ end
     end
 
     models_xs = [
-        # (RNN(3 => 2), randn(Float32, 3, 2), "RNN"), 
-        # (LSTM(3 => 5), randn(Float32, 3, 2), "LSTM"),
-        # (GRU(3 => 5), randn(Float32, 3, 10), "GRU"),
-        # (Chain(RNN(3 => 4), RNN(4 => 3)), randn(Float32, 3, 2), "Chain(RNN, RNN)"),
-        # (Chain(LSTM(3 => 5), LSTM(5 => 3)), randn(Float32, 3, 2), "Chain(LSTM, LSTM)"),
+        (RNN(3 => 2), randn(Float32, 3, 2), "RNN"), 
+        (LSTM(3 => 5), randn(Float32, 3, 2), "LSTM"),
+        (GRU(3 => 5), randn(Float32, 3, 10), "GRU"),
+        (Chain(RNN(3 => 4), RNN(4 => 3)), randn(Float32, 3, 2), "Chain(RNN, RNN)"),
+        (Chain(LSTM(3 => 5), LSTM(5 => 3)), randn(Float32, 3, 2), "Chain(LSTM, LSTM)"),
     ]
 
     for (model, x, name) in models_xs

test/runtests.jl

@@ -35,11 +35,6 @@ if FLUX_TEST_ENZYME || FLUX_TEST_REACTANT
   using Enzyme: Enzyme
 end
 
-if FLUX_TEST_REACTANT
-  Pkg.add("Reactant")
-  using Reactant: Reactant
-end
-
 include("test_utils.jl") # for test_gradients
 
 Random.seed!(0)
@@ -185,6 +180,13 @@ end
   end
 
   if FLUX_TEST_REACTANT
+    ## This Pg.add has to be done after Pkg.add("CUDA") otherwise CUDA.jl
+    ## will not be functional and complain with: 
+    # ┌ Error: CUDA.jl could not find an appropriate CUDA runtime to use.
+    # │ 
+    # │ CUDA.jl's JLLs were precompiled without an NVIDIA driver present.
+    Pkg.add("Reactant")
+    using Reactant: Reactant
     @testset "Reactant" begin
       include("ext_reactant/test_utils_reactant.jl")
       include("ext_reactant/reactant.jl")

test/test_utils.jl

@@ -37,6 +37,7 @@ end
 
 function check_equal_leaves(a, b; rtol=1e-4, atol=1e-4)
     fmapstructure_with_path(a, b) do kp, x, y
+        # @show kp
         if x isa AbstractArray
             @test x ≈ y rtol=rtol atol=atol
         elseif x isa Number
@@ -66,6 +67,8 @@ function test_gradients(
         error("You should either compare numerical gradients methods or CPU vs GPU.")
     end
 
+    Flux.trainmode!(f) # for layers like BatchNorm
+
     ## Let's make sure first that the forward pass works.
     l = loss(f, xs...)
     @test l isa Number