Practical Coding in TensorFlow 2.0

Fierce competition with PyTorch brought us a new version of TensorFlow (TF). The package has undergone many changes, but the key one is the retirement of session.run(). Instead of a familiar pattern of building and executing a static graph, TF 2 uses eager mode by default. Such code can be written in a pythonic fashion and converted into a computational graph. To execute the code as a static graph, a developer has to decorate the desired function with @tf.function.