TensorFlow 2.0 is driven by the community telling us they want an easy-to-use platform that is both flexible and powerful, and which supports deployment to any platform. TensorFlow 2.0 provides a comprehensive ecosystem of tools for developers, enterprises, and researchers who want to push the state-of-the-art in machine learning and build scalable ML-powered applications.
Coding with TensorFlow 2.0
TensorFlow 2.0 makes development of ML applications much easier. With tight integration of Keras into TensorFlow, eager execution by default, and Pythonic function execution, TensorFlow 2.0 makes the experience of developing applications as familiar as possible for Python developers. For researchers pushing the boundaries of ML, we have invested heavily in TensorFlow’s low-level API: We now export all ops that are used internally, and we provide inheritable interfaces for crucial concepts such as variables and checkpoints. This allows you to build onto the internals of TensorFlow without having to rebuild TensorFlow.
