Model Explorer: Simplifying ML models for Edge devices

Model Explorer is a newly released graph visualization tool from Google AI Edge, designed to help developers visualize and understand the architecture and data flow of large machine learning models, especially when optimizing for edge devices. Originally developed for Google's internal use, this tool supports popular ML frameworks such as JAX, PyTorch, TensorFlow, and TensorFlow Lite, and offers features like hierarchical visualization, customizable data overlays, and a smooth 60 FPS rendering experience using WebGL and three.js. Model Explorer can run locally, in Colab notebooks, or within Python files, allowing users to visualize models from multiple sources and formats, including through specialized APIs for PyTorch models. It simplifies tasks such as debugging model conversion errors, analyzing performance and numerical accuracy, and providing insights into model architecture by breaking down complex models into hierarchical layers. It has been effectively utilized by teams at Google, including Waymo and Google Silicon, to optimize on-device models, and future enhancements are planned to refine UI features and improve tool extensibility.

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