I'm out of the layers -- how to make a custom TensorFlow 2 layer.

TensorFlow 2 made the machine learning framework far easier to use, still retaining its flexibility to build its models. One of its new features is building new layers through integrated Keras API and easily debugging this API with the usage of eager-execution. In this article, you will learn how to build custom neural network layers in TensorFlow 2 framework. Writing this article I assume you have a basic understanding of object-oriented programming in Python 3. The best would be if you review __init__, __call__, class inheritance and method overriding before reading this article. Let's start from a template, based on it you will build most of your layers.