title: What is the recommended way to mix TensorFlow and TensorFlow Federated code?
body: <p>TensorFlow (TF) and TensorFlow Federated (TFF) are different layers of functionality that are designed to play well together (as the names implie).</p>
  
  <p>Still, they are different things designed to solve different problems.</p>
  
  <p>I wonder what is the best way to describe computation in a way that can be used by both vanilla TF and in TFF workloads, as well as the kind of pitfalls that one might want to avoid.</p>