PaddlePaddle/PGL
A graph learning framework built on PaddlePaddle for training graph neural networks at scale.
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Paddle Graph Learning (PGL) is a deep learning framework specialized for graph neural networks, built on top of PaddlePaddle. It provides efficient implementations of message passing, sampling, and heterogeneous graph operations. The framework includes domain-specific applications for knowledge graph embedding (Graph4KG), recommender systems (Graph4Rec), and large-scale graph training with GNNAutoScale, achieving top results in OGB-LSC KDD CUP 2021 competitions.
Frequently asked
- What is PaddlePaddle/PGL?
- A graph learning framework built on PaddlePaddle for training graph neural networks at scale.
- Is PGL open source?
- Yes — PaddlePaddle/PGL is open source, released under the Apache-2.0 license.
- What language is PGL written in?
- PaddlePaddle/PGL is primarily written in Python.
- How popular is PGL?
- PaddlePaddle/PGL has 1.6k stars on GitHub.
- Where can I find PGL?
- PaddlePaddle/PGL is on GitHub at https://github.com/PaddlePaddle/PGL.