How TensorFlow Handles Backward Compatibility Across Versions

This guide explains how TensorFlow manages backward compatibility and versioning across its APIs, SavedModels, GraphDefs, and checkpoints. It covers Semantic Versioning 2.0 rules for major, minor, and patch releases, what’s included in the public API guarantee, and how TensorFlow Lite and its extension APIs follow separate version schedules. Developers will also learn about data versioning for graphs and checkpoints, how forward and backward compatibility are maintained, and the specific steps for safely evolving or removing operations.