alterlab-torch-geometric
CommunityBuild scalable graph neural networks with PyG.
AuthorAlterLab-IEU
Version1.0.0
Installs0
System Documentation
What problem does it solve?
PyTorch Geometric (PyG) provides a comprehensive, production-ready toolkit to design, train, and deploy graph neural networks on real-world graph data, reducing boilerplate and expediting model experimentation.
Core Features & Use Cases
- Graph neural network primitives (GCNConv, GATConv, GraphSAGE, GIN) for node and graph-level tasks.
- Data handling and datasets (Data objects, Planetoid, TUDataset, MoleculeNet, OGB) with transforms and loaders.
- End-to-end workflows including model templates, training loops, evaluation utilities, benchmarking scripts, and templates for rapid experimentation.
Quick Start
Install PyG, load a dataset, define a simple GNN model, and start training.
Dependency Matrix
Required Modules
torchtorch_geometricnumpy
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: alterlab-torch-geometric Download link: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/archive/main.zip#alterlab-torch-geometric Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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