diff --git a/src/layers/conv.jl b/src/layers/conv.jl
index d6c97a0b8..8c3565dce 100644
--- a/src/layers/conv.jl
+++ b/src/layers/conv.jl
@@ -300,8 +300,7 @@ l = GATConv(in_channel => out_channel, add_self_loops = false, bias = false; hea
 y = l(g, x)       
 ```
 """
-struct GATConv{DX <: Dense, DE <: Union{Dense, Nothing}, DV, T, A <: AbstractMatrix, F, B} <:
-       GNNLayer
+struct GATConv{DX<:Dense,DE<:Union{Dense, Nothing},DV,T,A<:AbstractMatrix,F,B} <: GNNLayer
     dense_x::DX
     dense_e::DE
     bias::B
@@ -316,7 +315,7 @@ struct GATConv{DX <: Dense, DE <: Union{Dense, Nothing}, DV, T, A <: AbstractMat
 end
 
 Flux.@layer GATConv
-Flux.trainable(l::GATConv) = (dense_x = l.dense_x, dense_e = l.dense_e, bias = l.bias, a = l.a)
+Flux.trainable(l::GATConv) = (; l.dense_x, l.dense_e, l.bias, l.a)
 
 GATConv(ch::Pair{Int, Int}, args...; kws...) = GATConv((ch[1], 0) => ch[2], args...; kws...)
 
diff --git a/test/runtests.jl b/test/runtests.jl
index 8e518ec3d..05cb6fd5f 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -35,14 +35,11 @@ tests = [
 !CUDA.functional() && @warn("CUDA unavailable, not testing GPU support")
 
 # @testset "GraphNeuralNetworks: graph format $graph_type" for graph_type in (:coo, :dense, :sparse)
-# for graph_type in (:coo, :dense, :sparse)
-for graph_type in (:dense,)
+for graph_type in (:coo, :dense, :sparse)
 
     @info "Testing graph format :$graph_type"
     global GRAPH_T = graph_type
     global TEST_GPU = CUDA.functional() && (GRAPH_T != :sparse)
-    # global GRAPH_T = :sparse
-    # global TEST_GPU = false
 
     @testset "$t" for t in tests
         startswith(t, "examples") && GRAPH_T == :dense && continue     # not testing :dense since causes OutOfMememory on github's CI