Eager execution

At the time of this writing, Google had just introduced the eager execution API to TensorFlow. Eager Execution is TensorFlow's answer to another deep learning library called PyTorch. It allows you to bypass the usual TensorFlow way of working where you must first define a computational graph and then execute the graph to get a result. This is known as static graph computation. Instead, with Eager Execution, you can now create the so-called dynamic graphs that are defined on the fly as you run your program. This allows for a more traditional, imperative way of programming when using TensorFlow. Unfortunately, eager execution is still under development with some features still missing, and will not be featured in this book. More information on Eager Execution can be found at the TensorFlow website.