title: What is the upside of using `tf.nn.rnn` instead of `tf.nn.dynamic_rnn` in TensorFlow?
body: <p>What is the upside of using <a href="https://web.archive.org/web/20170220232722/https://www.tensorflow.org/versions/r0.10/api_docs/python/nn/recurrent_neural_networks#rnn" rel="nofollow noreferrer"><code>tf.nn.rnn</code></a> instead of <a href="https://web.archive.org/web/20170220232722/https://www.tensorflow.org/versions/r0.10/api_docs/python/nn/recurrent_neural_networks#dynamic_rnn" rel="nofollow noreferrer"><code>tf.nn.dynamic_rnn</code></a>?</p>
  
  <p>The <a href="https://web.archive.org/web/20170220232722/https://www.tensorflow.org/versions/r0.10/api_docs/python/nn/recurrent_neural_networks#dynamic_rnn" rel="nofollow noreferrer">documentation</a>  says :</p>
  
  <blockquote>
    <p>[<code>dynamic_rnn</code>] is functionally identical to the function <code>rnn</code> above, but performs fully dynamic unrolling of inputs.</p>
  </blockquote>
  
  <p>Is there any case where one might prefer to use <code>tf.nn.rnn</code> instead of <code>tf.nn.dynamic_rnn</code>?</p>