When you decorate a function with `tf.function` decorator, sometimes you need to keep state between invocations of this function.

Tensorflow 2 uses so called Eager mode by default. In this mode, it is easy to define tensors interactively, for example, in ipython and see their values. However, in Eager mode the execution is slow, which becomes noticable during model training.