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Guide for building Graph Neural Networks with PyTorch Geometric (PyG). Use this skill whenever the user asks about graph neural networks, GNNs, node…
PyTorch Geometric (PyG) PyG is the standard library for Graph Neural Networks built on PyTorch. It provides data structures for graphs, 60+ GNN layer implementations, scalable mini-batch training, and support for heterogeneous graphs. Install: uv add torch_geometric (or uv pip install torch_geometric; requires PyTorch). Optional: pyg-lib, torch-scatter, torch-sparse, torch-cluster for accelerated ops. Core Concepts Graph Data: Data and HeteroData A graph lives in a Data object. The key attributes: from torch_geometric.data import Data
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