title: How to average summaries over multiple batches?
body: <p>Assuming I have a bunch of summaries defined like:</p>
  
  <pre class="lang-py prettyprint-override"><code>loss = ...
  tf.scalar_summary("loss", loss)
  # ...
  summaries = tf.merge_all_summaries()
  </code></pre>
  
  <p>I can evaluate the <code>summaries</code> tensor every few steps on the training data and pass the result to a <code>SummaryWriter</code>.
  The result will be noisy summaries, because they're only computed on one batch.</p>
  
  <p>However, I would like to compute the summaries on the entire validation dataset.
  Of course, I can't pass the validation dataset as a single batch, because it would be too big.
  So, I'll get summary outputs for each validation batch.</p>
  
  <p>Is there a way to average those summaries so that it appears as if the summaries have been computed on the entire validation set?</p>