TensorFlow GNN (TF-GNN) is a scalable library for Graph Neural Networks in TensorFlow. It is designed from the bottom up to support the kinds of rich heterogeneous graph data that occurs in today's information ecosystems. Many production models at Google use TF-GNN and it has been recently released as an open source project. In this paper, we describe the TF-GNN data model, its Keras modeling API, and relevant capabilities such as graph sampling, distributed training, and accelerator support.
翻译:TensorFlow GNN(TF-GNN)是TensorFlow的图形神经网络的可扩展图书馆,设计自下而上,用于支持当今信息生态系统中出现的丰富多彩的多彩图表数据。谷歌的许多生产模型使用TF-GNN,最近作为开放源码项目发布。本文描述了TF-GNN数据模型、其Keras型API模型,以及相关能力,如图表取样、分布式培训和加速器支持。