Fixes and ok GNNlib

Author: aurorarossi

GNNGraphs/docs/src/index.md

@@ -1,6 +1,6 @@
 # GNNGraphs.jl
 
-GNNGraphs.jl is a package that provides graph data structures and helper functions specifically designed for working with graph neural networks. This package allows to store not only the graph structure, but also features associated with nodes, edges, and the graph itself. It is the core foundation for the GNNlib, GraphNeuralNetworks, and GNNLux packages.
+GNNGraphs.jl is a package that provides graph data structures and helper functions specifically designed for working with graph neural networks. This package allows to store not only the graph structure, but also features associated with nodes, edges, and the graph itself. It is the core foundation for the GNNlib.jl, GraphNeuralNetworks.jl, and GNNLux.jl packages.
 
 It supports three types of graphs: 
 

GNNlib/docs/src/index.md

@@ -1,6 +1,15 @@
 # GNNlib.jl
 
 GNNlib.jl is a package that provides the implementation of the basic message passing functions and 
-functional implementation of graph convolutional layers, which are used to build graph neural networks in both the Flux.jl and Lux.jl machine learning frameworks, created in the GraphNeuralNetworks.jl and GNNLux.jl packages, respectively.
+functional implementation of graph convolutional layers, which are used to build graph neural networks in both the [Flux.jl](https://fluxml.ai/Flux.jl/stable/) and [Lux.jl](https://lux.csail.mit.edu/stable/) machine learning frameworks, created in the GraphNeuralNetworks.jl and GNNLux.jl packages, respectively.
 
-This package depends on GNNGraphs.jl and NNlib.jl, and is primarily intended for developers looking to create new GNN architectures. For most users, the higher-level GraphNeuralNetworks.jl and GNNLux.jl packages are recommended.
+This package depends on GNNGraphs.jl and NNlib.jl, and is primarily intended for developers looking to create new GNN architectures. For most users, the higher-level GraphNeuralNetworks.jl and GNNLux.jl packages are recommended.
+
+## Installation
+
+The package can be installed with the Julia package manager.
+From the Julia REPL, type `]` to enter the Pkg REPL mode and run:
+    
+```julia
+pkg> add GNNlib
+```

GNNlib/docs/src/messagepassing.md

@@ -134,7 +134,7 @@ function (l::GCN)(g::GNNGraph, x::AbstractMatrix{T}) where T
 end
 ```
 
-See the `GATConv` implementation [here](https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/blob/master/src/layers/conv.jl) for a more complex example.
+See the `GATConv` implementation [here](https://juliagraphs.org/GraphNeuralNetworks.jl/graphneuralnetworks/api/conv/) for a more complex example.
 
 
 ## Built-in message functions