pyg-team/pytorch_geometric

Graph Positional and Structural Encoder

Open

#8,310 创建于 2023年11月1日

在 GitHub 查看
 (21 评论) (0 反应) (0 负责人)Python (19,985 star) (3,514 fork)batch import
featuregood first issuehelp wantednn

描述

🚀 The feature, motivation and pitch

It would be great to add the "GPSE" (Graph Positional and Structural Encoder) module to PyG, which acts as a trained encoder for Graph Transformers. Most importantly, we should support loading pre-trained encoders and provide them to the user, e.g., via

encoder = GPSE.from_pretrained("molpcba")

Code: https://github.com/G-Taxonomy-Workgroup/GPSE Paper: https://arxiv.org/abs/2307.07107 Twitter: https://twitter.com/RemyLau3/status/1717194030986190899

Any help on this is highly appreciated :)

Alternatives

No response

Additional context

No response

贡献者指南

技术栈
pythonpytorch
领域
machine learning
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
5
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
over 1 week
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
active
清晰度议题是否清楚说明期望改动、验收标准和下一步。
clear
前置要求
PyTorchPyG basicsgraph neural networks
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
15
研究方向
Review the GPSE repository at https://github.com/G Taxonomy Workgroup/GPSE and the paper for architecture details. Look at existing encoder implementations in PyG (e.g., torch geometric.nn.models) for structure. Implement the GPSE module with a from pretrained method that loads pre trained weights. Ensure integration with PyG's data flow.