fix stuff

Author: CarloLucibello

.github/workflows/test_GNNLux.yml

@@ -41,7 +41,7 @@ jobs:
           Pkg.test("GNNLux"; coverage=true)
       - uses: julia-actions/julia-processcoverage@v1
         with:
-          directories: GNNLux/src,GNNLux/ext,GNNGraphs/src,GNNGraphs/ext,GNNlib/src,GNNlib/ext
+          directories: GNNLux/src,GNNGraphs/src,GNNGraphs/ext,GNNlib/src,GNNlib/ext
       - uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}

.github/workflows/test_GraphNeuralNetworks.yml

@@ -41,7 +41,7 @@ jobs:
           Pkg.test("GraphNeuralNetworks"; coverage=true)
       - uses: julia-actions/julia-processcoverage@v1
         with:
-          directories: GraphNeuralNetworks/src,GraphNeuralNetworks/ext,GNNGraphs/src,GNNGraphs/ext,GNNlib/src,GNNlib/ext
+          directories: GraphNeuralNetworks/src,GNNGraphs/src,GNNGraphs/ext,GNNlib/src,GNNlib/ext
       - uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}

GraphNeuralNetworks/test/layers/conv.jl

@@ -102,8 +102,17 @@ end
     l = ChebConv(D_IN => D_OUT, k)
     for g in TEST_GRAPHS
         has_isolated_nodes(g) && continue
-        broken = get_graph_type(g) == :sparse || gpu_backend() == "AMDGPU"
+
+        broken = gpu_backend() == "AMDGPU"
         @test size(l(g, g.x)) == (D_OUT, g.num_nodes) broken=broken
+        
+        if gpu_backend() == "AMDGPU"
+            broken = true
+        elseif gpu_backend() == "CUDA" && get_graph_type(g) == :sparse
+            broken = true
+        else
+            broken = false
+        end
         @test test_gradients(
             l, g, g.x, rtol = RTOL_LOW, test_gpu = true, compare_finite_diff = false
         ) broken=broken

GraphNeuralNetworks/test/test_module.jl

@@ -3,7 +3,7 @@
 using Pkg
 
 ## Uncomment below to change the default test settings
-# ENV["GNN_TEST_CUDA"] = "true"
+ENV["GNN_TEST_CUDA"] = "true"
 # ENV["GNN_TEST_AMDGPU"] = "true"
 # ENV["GNN_TEST_Metal"] = "true"
 
@@ -39,7 +39,7 @@ using SparseArrays
 export mean, randn, SparseArrays, AbstractSparseMatrix
 
 # from Flux.jl
-export Flux, gradient, Dense, Chain, relu
+export Flux, gradient, Dense, Chain, relu,
        BatchNorm, LayerNorm, Dropout, Parallel,
        gpu_device, cpu_device, get_device,
        CPUDevice, CUDADevice, AMDGPUDevice, MetalDevice