title: How to inspect client model updates in Tensorflow Federated
body: <p>I've been learning the <a href="https://www.tensorflow.org/federated" rel="nofollow noreferrer">TensorFlow Federated</a> framework recently but have run into a problem. I'd like to look at the trained client weights sent to the central server before aggregation.</p>
  <p>For example, in <a href="https://www.tensorflow.org/federated/tutorials/federated_learning_for_image_classification" rel="nofollow noreferrer">this</a> tutorial, I have access to the state variable:</p>
  <pre><code>NUM_ROUNDS = 11
  for round_num in range(2, NUM_ROUNDS):
    state, metrics = iterative_process.next(state, federated_train_data)
    print('round {:2d}, metrics={}'.format(round_num, metrics))
  </code></pre>
  <p>The state variables holds the weights of the central model (created by aggregating client weights). Is there anyway to inspect the weights that were sent by the clients prior to aggregation in TensorFlow Federated?</p>
  <p>Thanks, any help appreciated.</p>