title: Adding tensorboard to federated setting
body: <p>I am new in using TensorBoard, and I want to add it to this project:</p>
  
  <p><a href="https://github.com/TalwalkarLab/leaf" rel="nofollow noreferrer">https://github.com/TalwalkarLab/leaf</a></p>
  
  <p>My specific case is the FE-MNIST model, which is in here:
  <a href="https://github.com/TalwalkarLab/leaf/blob/master/models/femnist/cnn.py" rel="nofollow noreferrer">https://github.com/TalwalkarLab/leaf/blob/master/models/femnist/cnn.py</a></p>
  
  <p>The challenge of adding tensorboard to Federated Setting for people who do not know the setting is that in here, have a server that aggregate the models, and we have random number of clients that does the training, and they have a Client_id.</p>
  
  <p>I want to have a tensorboard folder for each of the clients, and log for the server model (which no training is done there)</p>
  
  <p>I want to know how to access layers weights and biases, and store them based on the client ids, which is the place that is calling the training.</p>
  
  <p>I have seen <a href="https://stackoverflow.com/questions/44731808/how-do-i-use-tensor-board-with-tf-layers">How do I use tensor board with tf.layers?</a></p>
  
  <p>in here it says that we can use </p>
  
  <p><strong>Code</strong></p>
  
  <pre><code>for var in tf.trainable_variables():
      tf.summary.histogram(var.name, var)
  merged_summary = tf.summary.merge_all()
  </code></pre>
  
  <p>(which I am not sure where should I add it)</p>
  
  <p>How can I pass the client id to a session, so it can store in the respective folders?</p>