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| # GraphNeuralNetworks Monorepo | ||
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| 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: | ||
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| - `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. | ||
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| * 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. | ||
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| - `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. | ||
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| - `GNNGraphs.jl`: Package that contains the graph data structures and helper functions for working with graph data. It depends on Graphs.jl package. | ||
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| Here is a schema of the dependencies between the packages: | ||
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| 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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