How to average summaries over multiple batches? : <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>
