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New introduction to monorepo (#512)
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* New monorepo docs

* Better version
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aurorarossi authored Nov 6, 2024
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# GraphNeuralNetworks Monorepo

This is the documentation page for [GraphNeuralNetworks.jl](https://github.com/JuliaGraphs/GraphNeuralNetworks.jl), a graph neural network library written in Julia and based on the deep learning framework [Flux.jl](https://github.com/FluxML/Flux.jl).
GraphNeuralNetworks.jl is largely inspired by [PyTorch Geometric](https://pytorch-geometric.readthedocs.io/en/latest/), [Deep Graph Library](https://docs.dgl.ai/),
and [GeometricFlux.jl](https://fluxml.ai/GeometricFlux.jl/stable/).
This is the monorepository for the GraphNeuralNetworks project, bringing together all code into a unified structure to facilitate code sharing and reusability across different project components. It contains the following packages:

- `GraphNeuralNetwork.jl`: Package that contains stateful graph convolutional layers based on the machine learning framework [Flux.jl](https://fluxml.ai/Flux.jl/stable/). This is fronted package for Flux users. It depends on GNNlib.jl, GNNGraphs.jl, and Flux.jl packages.

* Implements common graph convolutional layers.
* Supports computations on batched graphs.
* Easy to define custom layers.
* CUDA support.
* Integration with [Graphs.jl](https://github.com/JuliaGraphs/Graphs.jl).
* [Examples](https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/tree/master/examples) of node, edge, and graph level machine learning tasks.
- `GNNLux.jl`: Package that contains stateless graph convolutional layers based on the machine learning framework [Lux.jl](https://lux.csail.mit.edu/stable/). This is fronted package for Lux users. It depends on GNNlib.jl, GNNGraphs.jl, and Lux.jl packages.

- `GNNlib.jl`: Package that contains the core graph neural network layers and utilities. It depends on GNNGraphs.jl and GNNlib.jl packages and serves for code base for GraphNeuralNetwork.jl and GNNLux.jl packages.

- `GNNGraphs.jl`: Package that contains the graph data structures and helper functions for working with graph data. It depends on Graphs.jl package.

Here is a schema of the dependencies between the packages:

![Monorepo schema](assets/schema.png)




Usage examples on real datasets can be found in the [examples](https://github.com/JuliaGraphs/GraphNeuralNetworks.jl/tree/master/examples) folder.

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