torch-geometric
PyTorch Geometric (PyG) for graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use when working with torch_geometric, not for general NetworkX analytics or non-graph PyTorch models.
- Version
- 1.2
- License
- MIT
- Compatibility
- Requires Python 3.10+, PyTorch 2.6+, and torch-geometric 2.7.x. Optional extension wheels (pyg-lib, torch-scatter, torch-sparse, torch-cluster) must match your PyTorch/CUDA build from https://data.pyg.org/whl.
Pinned to revision df088027ff23, so it is the text this page describes rather than whatever the author pushed since.
Files
- skills/torch-geometric/SKILL.md
- skills/torch-geometric/references/custom_datasets.md
- skills/torch-geometric/references/explainability.md
- skills/torch-geometric/references/heterogeneous.md
- skills/torch-geometric/references/link_prediction.md
- skills/torch-geometric/references/message_passing.md
- skills/torch-geometric/references/scaling.md
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