fix

GNNGraphs/docs/make.jl

@@ -46,7 +46,8 @@ makedocs(;
             "GNNHeteroGraph" => "api/heterograph.md",
             "TemporalSnapshotsGNNGraph" => "api/temporalgraph.md",
             "Samplers" => "api/samplers.md",
-        ],      
+            "Datasets" => "api/datasets.md",
+        ],
     ]
 )
 

GNNGraphs/docs/src/api/datasets.md

@@ -0,0 +1,10 @@
+```@meta
+CurrentModule = GNNGraphs
+CollapsedDocStrings = true
+```
+
+# Datasets
+
+```@docs
+mldataset2gnngraph
+```

GNNGraphs/docs/src/api/gnngraph.md

@@ -21,42 +21,42 @@ Base.copy
 
 ## DataStore
 
-```@autodocs
+```@autodocs; canonical = true
 Modules = [GNNGraphs]
 Pages   = ["datastore.jl"]
 Private = false
 ```
 
 ## Query
 
-```@autodocs
+```@autodocs; canonical = true
 Modules = [GNNGraphs]
 Pages   = ["src/query.jl"]
 Private = false
 ```
 
-```@docs
+```@docs; canonical = true
 Graphs.neighbors(::GNNGraph, ::Integer)
 ```
 
 ## Transform
 
-```@autodocs
+```@autodocs; canonical = true
 Modules = [GNNGraphs]
 Pages   = ["src/transform.jl"]
 Private = false
 ```
 
 ## Utils
 
-```@docs
+```@docs; canonical = true
 GNNGraphs.sort_edge_index
 GNNGraphs.color_refinement
 ``` 
 
 ## Generate
 
-```@autodocs
+```@autodocs; canonical = true
 Modules = [GNNGraphs]
 Pages   = ["src/generate.jl"]
 Private = false
@@ -65,24 +65,24 @@ Filter = t -> typeof(t) <: Function && t!=rand_temporal_radius_graph && t!=rand_
 
 ## Operators
 
-```@autodocs
+```@autodocs; canonical = true
 Modules = [GNNGraphs]
 Pages   = ["src/operators.jl"]
 Private = false
 ```
 
-```@docs
+```@docs; canonical = true
 Base.intersect
 ```
 
 ## Sampling 
 
-```@autodocs
+```@autodocs; canonical = true
 Modules = [GNNGraphs]
 Pages   = ["src/sampling.jl"]
 Private = false
 ```
 
-```@docs
+```@docs; canonical = true
 Graphs.induced_subgraph(::GNNGraph, ::Vector{Int})
 ```

GNNGraphs/docs/src/guides/datasets.md

@@ -5,6 +5,3 @@ For graphs with static structures and temporal features, datasets such as METRLA
 
 GraphNeuralNetworks.jl provides the [`mldataset2gnngraph`](@ref) method for interfacing with MLDatasets.jl.
 
-```@docs
-mldataset2gnngraph
-```

GNNLux/docs/make.jl

@@ -68,6 +68,7 @@ makedocs(;
                 "GNNHeteroGraph" => "GNNGraphs/api/heterograph.md",
                 "TemporalSnapshotsGNNGraph" => "GNNGraphs/api/temporalgraph.md",
                 "Samplers" => "GNNGraphs/api/samplers.md",
+                "Datasets" => "GNNGraphs/api/datasets.md",
             ]
 
             "Message Passing (GNNlib.jl)" => [

GNNlib/docs/make.jl

@@ -7,6 +7,7 @@ Pkg.instantiate()
 using Documenter
 using GNNlib
 using GNNGraphs
+import Graphs
 using DocumenterInterLinks
 
 assets=[]
@@ -17,24 +18,35 @@ interlinks = InterLinks(
     "NNlib" => "https://fluxml.ai/NNlib.jl/stable/",
 )
 
+# Copy the docs from GNNGraphs. Will be removed at the end of the script
+cp(joinpath(@__DIR__, "../../GNNGraphs/docs/src/"),
+   joinpath(@__DIR__, "src/GNNGraphs/"), force=true)
 
 makedocs(;
-    modules = [GNNlib],
-    doctest = false,
-    clean = true,
+    modules = [GNNlib, GNNGraphs],
+    doctest = false, # TODO enable doctest
     plugins = [interlinks],
     format = Documenter.HTML(; mathengine, prettyurls, assets = assets, size_threshold=nothing),
     sitename = "GNNlib.jl",
     pages = [
         "Home" => "index.md",
         "Message Passing" => "guides/messagepassing.md",
         "API Reference" => [
+            "Graphs (GNNGraphs.jl)" => [
+                "GNNGraph" => "GNNGraphs/api/gnngraph.md",
+                "GNNHeteroGraph" => "GNNGraphs/api/heterograph.md",
+                "TemporalSnapshotsGNNGraph" => "GNNGraphs/api/temporalgraph.md",
+                "Samplers" => "GNNGraphs/api/samplers.md",
+                "Datasets" => "GNNGraphs/api/datasets.md",
+            ],
             "Message Passing" => "api/messagepassing.md",
             "Utils" => "api/utils.md",
         ]
     ]
 )
 
+rm(joinpath(@__DIR__, "src/GNNGraphs"), force=true, recursive=true)
+
 deploydocs(
     repo = "github.com/JuliaGraphs/GraphNeuralNetworks.jl", 
     target = "build",

GNNlib/src/msgpass.jl

@@ -22,7 +22,7 @@ providing as input `f` a closure.
 - `g`: A `GNNGraph`.
 - `xi`: An array or a named tuple containing arrays whose last dimension's size 
         is `g.num_nodes`. It will be appropriately materialized on the
-        target node of each edge (see also [`edge_index`](@ref)).
+        target node of each edge (see also [`edge_index`](@ref GNNGraphs.edge_index)).
 - `xj`: As `xj`, but to be materialized on edges' sources. 
 - `e`: An array or a named tuple containing arrays whose last dimension's size is `g.num_edges`.
 - `fmsg`: A generic function that will be passed over to [`apply_edges`](@ref). 
@@ -100,7 +100,7 @@ such tensors.
 - `g`: An `AbstractGNNGraph`.
 - `xi`: An array or a named tuple containing arrays whose last dimension's size 
         is `g.num_nodes`. It will be appropriately materialized on the
-        target node of each edge (see also [`edge_index`](@ref)).
+        target node of each edge (see also [`edge_index`](@ref GNNGraphs.edge_index)).
 - `xj`: As `xi`, but now to be materialized on each edge's source node. 
 - `e`: An array or a named tuple containing arrays whose last dimension's size is `g.num_edges`.
 - `fmsg`: A function that takes as inputs the edge-materialized `xi`, `xj`, and `e`.

GraphNeuralNetworks/docs/make.jl

@@ -74,6 +74,7 @@ makedocs(;
                 "GNNHeteroGraph" => "GNNGraphs/api/heterograph.md",
                 "TemporalSnapshotsGNNGraph" => "GNNGraphs/api/temporalgraph.md",
                 "Samplers" => "GNNGraphs/api/samplers.md",
+                "Datasets" => "GNNGraphs/api/datasets.md",
             ]
 
             "Message Passing (GNNlib.jl)" => [