Graph Nets is a neural network library for building graph network architectures in TensorFlow. It provides tools to create networks that operate on graph-structured data, where nodes, edges, and global attributes are processed to produce updated graph outputs. The library implements the relational inductive biases described in the DeepMind paper on graph networks and integrates with Sonnet, DeepMind’s neural network library.