ahsanmemon/Gradient-Tape

Creating custom routines in Tensorflow has never been easy. Mostly because of the complexities involved in writing the code. With tensorflow 2.0 eager-execution and GradientTape, I find it relatively easier to write models while avoiding the confusing sub-classing APIs that Tensorflow provides. This repository contains some of the code that I wrote to understand and implement models using GradientTape instead of the classical model.fit or model.compile methods that Keras and Tensorflow 2 provide.