simplify documentation

.github/workflows/test_GNNGraphs.yml

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

.github/workflows/test_GNNLux.yml

@@ -41,8 +41,7 @@ jobs:
           Pkg.test("GNNLux"; coverage=true)
       - uses: julia-actions/julia-processcoverage@v1
         with:
-          # directories: ./GNNLux/src, ./GNNLux/ext
-          directories: ./GNNLux/src
+          directories: GNNLux/src,GNNGraphs/src,GNNGraphs/ext,GNNlib/src,GNNlib/ext
       - uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}

.github/workflows/test_GNNlib.yml

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

.gitignore

@@ -15,4 +15,5 @@ GNNGraphs/docs/build
 GNNlib/docs/build
 GNNLux/docs/build
 GraphNeuralNetworks/docs/build
-tutorials/docs/build
+GraphNeuralNetworks/docs/src/other
+tutorials/docs/build

GNNGraphs/docs/make.jl

@@ -16,8 +16,10 @@ makedocs(;
          format = Documenter.HTML(; mathengine, prettyurls, assets = assets, size_threshold=nothing),
          sitename = "GNNGraphs.jl",
          pages = ["Home" => "index.md",
-            "Graphs" => ["gnngraph.md", "heterograph.md", "temporalgraph.md"],
-            "Datasets" => "datasets.md",
+            "Guides" => [
+               "Graphs" => ["guides/gnngraph.md", "guides/heterograph.md", "guides/temporalgraph.md"],
+               "Datasets" => "guides/datasets.md",
+            ],
             "API Reference" => [
                  "GNNGraph" => "api/gnngraph.md",
                  "GNNHeteroGraph" => "api/heterograph.md",

GNNlib/docs/make.jl

@@ -21,7 +21,7 @@ makedocs(;
          format = Documenter.HTML(; mathengine, prettyurls, assets = assets, size_threshold=nothing),
          sitename = "GNNlib.jl",
          pages = ["Home" => "index.md",
-            "Message Passing" => "messagepassing.md",
+            "Message Passing" => "guides/messagepassing.md",
 
             "API Reference" => [
 

GNNlib/test/msgpass.jl

@@ -168,8 +168,7 @@ end
 
     @testset "copy_xj +" begin
         for g in TEST_GRAPHS
-            dev = gpu_device(force=true)
-            broken = get_graph_type(g) == :sparse && dev isa AMDGPUDevice
+            broken = get_graph_type(g) == :sparse && gpu_backend() == "AMDGPU"
             f(g, x) = propagate(copy_xj, g, +, xj = x)
             @test test_gradients(
                 f, g, g.x; test_gpu=true, test_grad_f=false, compare_finite_diff=false
@@ -179,8 +178,7 @@ end
 
     @testset "copy_xj mean" begin
         for g in TEST_GRAPHS
-            dev = gpu_device(force=true)
-            broken = get_graph_type(g) == :sparse && dev isa AMDGPUDevice
+            broken = get_graph_type(g) == :sparse && gpu_backend() == "AMDGPU"
             f(g, x) = propagate(copy_xj, g, mean, xj = x)
             @test test_gradients(
                 f, g, g.x; test_gpu=true, test_grad_f=false, compare_finite_diff=false
@@ -190,8 +188,7 @@ end
 
     @testset "e_mul_xj +" begin
         for g in TEST_GRAPHS
-            dev = gpu_device(force=true)
-            broken = get_graph_type(g) == :sparse && dev isa AMDGPUDevice
+            broken = get_graph_type(g) == :sparse && gpu_backend() == "AMDGPU"
             e = rand(Float32, size(g.x, 1), g.num_edges)
             f(g, x, e) = propagate(e_mul_xj, g, +; xj = x, e)
             @test test_gradients(
@@ -207,7 +204,6 @@ end
                 g = set_edge_weight(g, w)
                 return propagate(w_mul_xj, g, +, xj = x)
             end
-            dev = gpu_device(force=true)
             # @show get_graph_type(g) has_isolated_nodes(g)
             # broken = get_graph_type(g) == :sparse
             broken = true

GNNlib/test/test_module.jl

@@ -45,7 +45,7 @@ using Flux: Flux
 # from this module
 export D_IN, D_OUT, GRAPH_TYPES, TEST_GRAPHS,
        test_gradients, finitediff_withgradient, 
-       check_equal_leaves
+       check_equal_leaves, gpu_backend
 
 
 const D_IN = 3
@@ -177,4 +177,18 @@ TEST_GRAPHS = [generate_test_graphs(:coo)...,
                generate_test_graphs(:dense)...,
                generate_test_graphs(:sparse)...]
 
+
+function gpu_backend()
+    dev = gpu_device()
+    if dev isa CUDADevice
+        return "CUDA"
+    elseif dev isa AMDGPUDevice
+        return "AMDGPU"
+    elseif dev isa MetalDevice
+        return "Metal"
+    else
+        return "Unknown"
+    end
+end
+
 end # module

GraphNeuralNetworks/docs/make.jl

@@ -14,34 +14,44 @@ interlinks = InterLinks(
 
    )
 
+# Copy the guides from GNNGraphs and GNNlib
+dest_guides_dir = joinpath(@__DIR__, "src/other")
+gnngraphs_guides_dir = joinpath(@__DIR__, "../../GNNGraphs/docs/src/guides")
+gnnlib_guides_dir = joinpath(@__DIR__, "../../GNNlib/docs/src/guides") 
+for file in readdir(gnngraphs_guides_dir)
+    cp(joinpath(gnngraphs_guides_dir, file), joinpath(dest_guides_dir, file), force=true)
+end
+for file in readdir(gnnlib_guides_dir)
+    cp(joinpath(gnnlib_guides_dir, file), joinpath(dest_guides_dir, file), force=true)
+end
+
 makedocs(;
-         modules = [GraphNeuralNetworks],
-         doctest = false,
-         clean = true,
-         plugins = [interlinks],
-         format = Documenter.HTML(; mathengine, prettyurls, assets = assets, size_threshold=nothing),
-         sitename = "GraphNeuralNetworks.jl",
-         pages = ["Monorepo" => [ 
-               "Home" => "index.md",
-               "Developer guide" => "dev.md",
-               "Google Summer of Code" => "gsoc.md",
-            ],
-            "GraphNeuralNetworks.jl" =>[
-            "Home" => "home.md",
-            "Models" => "models.md",],
+    modules = [GraphNeuralNetworks],
+    doctest = false, # TODO: enable doctest
+    clean = true,
+    plugins = [interlinks],
+    format = Documenter.HTML(; mathengine, prettyurls, assets = assets, size_threshold=nothing),
+    sitename = "GraphNeuralNetworks.jl",
+    pages = [
+
+    "Home" => "index.md",
+
+    "Guides" => [
+        "Graphs" => ["other/gnngraph.md", "other/heterograph.md", "other/temporalgraph.md"],
+        "Message Passing" => "other/messagepassing.md",
+        "Models" => "guides/models.md",
+        "Datasets" => "other/datasets.md",
+    ],
 
-            "API Reference" => [
-
-                  "Basic" => "api/basic.md",
-                  "Convolutional layers" => "api/conv.md",
-                  "Pooling layers" => "api/pool.md",
-                  "Temporal Convolutional layers" => "api/temporalconv.md",
-                  "Hetero Convolutional layers" => "api/heteroconv.md",
-
-
-              ],
-
-         ],
-         )
+    "API Reference" => [
+            "Basic" => "api/basic.md",
+            "Convolutional layers" => "api/conv.md",
+            "Pooling layers" => "api/pool.md",
+            "Temporal Convolutional layers" => "api/temporalconv.md",
+            "Hetero Convolutional layers" => "api/heteroconv.md",
+        ],
+        "Developer guide" => "dev.md",
+    ],
+)
 
 deploydocs(;repo = "github.com/JuliaGraphs/GraphNeuralNetworks.jl.git", devbranch = "master", dirname= "GraphNeuralNetworks")