pyg-team/pytorch_geometric

Graph Positional and Structural Encoder

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#8,310 建立於 2023年11月1日

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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 :)

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貢獻者指南

技術棧
pythonpytorch
領域
machine learning
議題類型
feature
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
5
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over 1 week
活動狀態議題目前的可參與程度：新鮮、活躍、陳舊、阻塞或等待維護者輸入。
active
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
clear
前置要求
PyTorchPyG basicsgraph neural networks
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
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.