ports/misc/py-torch-geometric/pkg-descr

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PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and
train Graph Neural Networks (GNNs) for a wide range of applications related
to structured data.
It consists of various methods for deep learning on graphs and other irregular
structures, also known as geometric deep learning, from a variety of published
papers. In addition, it consists of easy-to-use mini-batch loaders for
operating on many small and single giant graphs, multi GPU-support,
torch.compile support, DataPipe support, a large number of common benchmark
datasets (based on simple interfaces to create your own), the GraphGym
experiment manager, and helpful transforms, both for learning on arbitrary
graphs as well as on 3D meshes or point clouds.