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torch-geometric

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About torch-geometric

T

torch-geometric

Supports PyTorch Geometric (PyG) graph neural networks

torch-geometric is an agent skill for graph neural networks with PyTorch Geometric, the standard library for graph learning built on PyTorch. It covers node, link and graph classification, message-passing layers such as GCN, GAT, GraphSAGE and GIN, heterogeneous graphs, and scalable mini-batch training. The library provides graph data structures and more than 60 GNN layer implementations. The skill reviews torch-geometric 2.8.0.post1, released 1 October 2026, and its CPU examples were tested with Python 3.13 and PyTorch 2.14.1. The rolling documentation identifies 2.9.0, so the skill tells you to check the installed release before using a newer API. PyG 2.8 requires PyTorch 2.9 or newer. Basic tensor-based layers need no extensions, but neighbour sampling needs pyg-lib or torch-sparse, and spatial nearest-neighbour operators need pyg-lib in 2.8. The torch-cluster and torch-spline-conv packages are deprecated and ignored. Install the PyTorch build for your platform first, and never install wheels for a different PyTorch release just because core imports work. Use it when your data is naturally a graph, such as molecules, interaction networks or patient similarity networks.

View torch-geometricAll AI Skills apps
Price
Free
Made by
k-dense-ai
Category
AI Skills
Website
github.com/k-dense-ai/scientific-agent-skills/torch-geometric