title: What is the suggested practice for storing multiple runs of a summary writer in TensorFlow?
body: <p>I am learning to use TensorBoard and every time I launch tensorboard I get in my terminal the message:</p>
  
  <pre><code>WARNING:tensorflow:Found more than one graph event per run. Overwriting the graph with the newest event.
  </code></pre>
  
  <p>I assume is because I've run the same model multiple times with the same name. I just want to run my model multiple times and be able to inspect what its doing using tensorflow. Is just re running:</p>
  
  <pre><code>tensorboard --logdir=path/to/log-directory
  </code></pre>
  
  <p>not the usual way to do it? Or what is the suggestion for doing this type of work when I want to run the same model multiple times with and explore different learning algorithms, step-sizes, initilization, etc. Is it really neccessary to set up a new log directory each time?</p>