title: Tensorflow custom layer with backpropagation
body: <p>I want to create the custom keras layer in Tensorflow. For instance, custom activation layer based on sigmoid function with trainable parameters <strong>a</strong> and <strong>b</strong>, so my function looks like:
  1 / (1 + exp(a*x + b)).
  I looked into Tensorflow tutorials, but they address custom layers derived from already existing layers. So, the question is How can I implement the desired functionality?</p>
  <p>The functionality is provided for example purposes. In general, the question targets creation of custom tensorflow.keras layer with trainable parameters (weights).</p>