ignore pluto for the time being

Author: CarloLucibello

docs/make.jl

@@ -11,11 +11,10 @@ tutorial_menu = Array{Pair{String,String},1}()
 #
 # Generate Pluto Tutorial HTMLs
 
-# First tutorial with AD
-pluto_src_folder = joinpath(@__DIR__, "src", "tutorials")
-pluto_output_folder = joinpath(@__DIR__, "src", "tutorials")
-pluto_relative_path = "tutorials/"
-mkpath(pluto_output_folder)
+# pluto_src_folder = joinpath(@__DIR__, "src", "tutorials")
+# pluto_output_folder = joinpath(@__DIR__, "src", "tutorials")
+# pluto_relative_path = "tutorials/"
+# mkpath(pluto_output_folder)
 
 # """
 #     build()
@@ -35,39 +34,39 @@ mkpath(pluto_output_folder)
 #     build()
 # end
 
-# Please do not use the same name as for a(n old) literate Tutorial
-pluto_files = [
-    "gnn_intro_pluto",
-    "graph_classification_pluto",
-]
-pluto_titles = [
-    "Intro to Graph Neural Networks ",
-    "Graph Classification",
-]
+# # Please do not use the same name as for a(n old) literate Tutorial
+# pluto_files = [
+#     "gnn_intro_pluto",
+#     "graph_classification_pluto",
+# ]
+# pluto_titles = [
+#     "Intro to Graph Neural Networks ",
+#     "Graph Classification",
+# ]
 
-# build menu and write files myself - tp set edit url correctly.
-for (title, file) in zip(pluto_titles, pluto_files)
-    global tutorial_menu
-    rendered = build_notebooks( #though not really parallel here
-        BuildOptions(
-            pluto_src_folder;
-            output_format=documenter_output,
-            write_files=false,
-            use_distributed=false,
-        ),
-        ["$(file).jl"],
-    )
-    write(
-        joinpath(pluto_output_folder, file * ".md"),
-        """
-        ```@meta
-        EditURL = "$(joinpath(pluto_src_folder, file * ".jl"))"
-        ```
-        $(rendered[1])
-        """,
-    )
-    push!(tutorial_menu, title => joinpath(pluto_relative_path, file * ".md"))
-end
+# # build menu and write files myself - tp set edit url correctly.
+# for (title, file) in zip(pluto_titles, pluto_files)
+#     global tutorial_menu
+#     rendered = build_notebooks( #though not really parallel here
+#         BuildOptions(
+#             pluto_src_folder;
+#             output_format=documenter_output,
+#             write_files=false,
+#             use_distributed=false,
+#         ),
+#         ["$(file).jl"],
+#     )
+#     write(
+#         joinpath(pluto_output_folder, file * ".md"),
+#         """
+#         ```@meta
+#         EditURL = "$(joinpath(pluto_src_folder, file * ".jl"))"
+#         ```
+#         $(rendered[1])
+#         """,
+#     )
+#     push!(tutorial_menu, title => joinpath(pluto_relative_path, file * ".md"))
+# end
 
 DocMeta.setdocmeta!(GraphNeuralNetworks, :DocTestSetup, 
     :(using GraphNeuralNetworks, Graphs, SparseArrays, NNlib, Flux); 
@@ -87,7 +86,7 @@ makedocs(;
              "Message Passing" => "messagepassing.md",
              "Model Building" => "models.md",
              "Datasets" => "datasets.md",
-             "Tutorials" => tutorial_menu,
+            #  "Tutorials" => tutorial_menu,
             #  "Tutorials" => 
             #     [
             #         "Intro to Graph Neural Networks" => "gnn_intro_pluto.md",

examples/link_prediction_pubmed.jl

@@ -16,7 +16,7 @@ Base.@kwdef mutable struct Args
     η = 1f-3             # learning rate
     epochs = 200          # number of epochs
     seed = 17             # set seed > 0 for reproducibility
-    usecuda = false      # if true use cuda (if available)
+    usecuda = true      # if true use cuda (if available)
     nhidden = 64        # dimension of hidden features
     infotime = 10 	     # report every `infotime` epochs
 end

src/GNNGraphs/transform.jl

@@ -614,9 +614,9 @@ function rand_edge_split(g::GNNGraph, frac; bidirected=is_bidirected(g))
         s1, t1 = s[eids[1:size1]], t[eids[1:size1]]
         s2, t2 = s[eids[size1+1:end]], t[eids[size1+1:end]]
     else
-        @assert is_bidirected(g)
-        @assert !has_self_loops(g)
-        @assert !has_multi_edges(g)
+        # @assert is_bidirected(g)
+        # @assert !has_self_loops(g)
+        # @assert !has_multi_edges(g)
         mask = s .< t
         s, t = s[mask], t[mask]
         s1, t1 = s[eids[1:size1]], t[eids[1:size1]]

src/GNNGraphs/utils.jl

@@ -13,6 +13,18 @@ function sort_edge_index(u, v)
     return u[p], v[p]
 end
 
+
+function sort_edge_index(u, v)
+    uv = collect(zip(u, v))
+    p = sortperm(uv) # isless lexicographically defined for tuples
+    return u[p], v[p]
+end
+
+function sort_edge_index(u::AnyCuArray, v::AnyCuArray)
+    #TODO proper cuda friendly implementation
+    sort_edge_index(u |> Flux.cpu, v |> Flux.cpu) |> Flux.gpu
+end
+
 cat_features(x1::Nothing, x2::Nothing) = nothing 
 cat_features(x1::AbstractArray, x2::AbstractArray) = cat(x1, x2, dims=ndims(x1))
 cat_features(x1::Union{Number, AbstractVector}, x2::Union{Number, AbstractVector}) =