title: How to create only one copy of graph in tensorboard events file with custom tf.Estimator?
body: <p>I'm using a custom <code>tf. Estimator</code> object to train a neural network. The problem is in the size of the events file after training - it is unreasonably large.
  I've already solved the problem with saving part of a dataset as constant by using <code>tf.Dataset.from_generator()</code>.
  However, the size is still quite large and while starting <code>tensorboard</code> I'm getting the message</p>
  <p><code>W0225 10:38:07.443567 140693578311424 tf_logging.py:120] Found more than one metagraph event per run. Overwriting the metagraph with the newest event.</code></p>
  <p>So, I suppose, that I'm creating and saving many different graphs in this event file. Is it possible to turn off this saving or how to save an only first copy?</p>
  <p>For know, I found only the way to delete all the default logs by deleting the events filts with</p>
  <pre class="lang-py prettyprint-override"><code>list(map(os.remove, glob.glob(os.path.join(runtime_params['model_dir'], 'events.out.tfevents*'))))
  </code></pre>
  <p>However, it is a bad solution for me, as I would prefer to keep the summaries and, ideally, <strong>one</strong> copy of the graph.</p>
  <p>From the documentation, I can see that</p>
  <p>Estimators <strong>automatically</strong> write the following to disk:</p>
  <ul>
  <li>checkpoints, which are versions of the model created during training.</li>
  <li><strong>event files</strong>, which contain information that TensorBoard uses to create visualizations.
  Is it a way to turn off writing of the <strong>events file</strong>?</li>
  </ul>