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Libraries supporting GNNs are now located in the [cugraph-gnn repository](https://github.com/rapidsai/cugraph-gnn)
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*[pylibwholegraph](https://github.com/rapidsai/cugraph-gnn/tree/HEAD/python/) - the [Wholegraph](https://docs.rapids.ai/api/cugraph/nightly/wholegraph/) library for client memory management supporting both cuGraph-DGL and cuGraph-PyG for even greater scalability
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*[cugraph_dgl](https://github.com/rapidsai/cugraph-gnn/blob/main/readme_pages/cugraph_dgl.md) enables the ability to use cugraph Property Graphs with Deep Graph Library (DGL)
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*[cugraph_pyg](https://github.com/rapidsai/cugraph-gnn/blob/main/readme_pages/cugraph_pyg.md) enables the ability to use cugraph Property Graphs with PyTorch Geometric (PyG).
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[RAPIDS nx-cugraph](https://rapids.ai/nx-cugraph/) is now located in the [nx-cugraph repository](https://github.com/rapidsai/nx-cugraph) containing a backend to NetworkX for running supported algorithms with GPU acceleration.
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