To make a Keras model's variables trainable within a GPflow kernel, simply assign the model as a direct attribute. This works because modern GPflow automatically discovers all variables within tf.Module objects (like Keras models), and eliminate the need for a special wrapper. Please refer this gist for the example implemented approach.