title: Analysis of the output from tf.nn.dynamic_rnn tensorflow function
body: <p>I am not able to understand the output from <code>tf.nn.dynamic_rnn</code> tensorflow function. The document just tells about the size of the output, but it doesn't tell what does each row/column means. From the documentation:</p>
  
  <blockquote>
    <p><strong>outputs</strong>: The RNN output <code>Tensor</code>.</p>
    
    <p>If time_major == False (default), this will be a <code>Tensor</code> shaped:
        <code>[batch_size, max_time, cell.output_size]</code>.</p>
    
    <p>If time_major == True, this will be a <code>Tensor</code> shaped:
        <code>[max_time, batch_size, cell.output_size]</code>.</p>
    
    <p>Note, if <code>cell.output_size</code> is a (possibly nested) tuple of integers
    or <code>TensorShape</code> objects, then <code>outputs</code> will be a tuple having the<br>
    same structure as <code>cell.output_size</code>, containing Tensors having shapes
    corresponding to the shape data in <code>cell.output_size</code>.</p>
    
    <p><strong>state</strong>: The final state.  If <code>cell.state_size</code> is an int, this   will
    be shaped <code>[batch_size, cell.state_size]</code>.  If it is a<br>
    <code>TensorShape</code>, this will be shaped <code>[batch_size] + cell.state_size</code>.<br>
    If it is a (possibly nested) tuple of ints or <code>TensorShape</code>, this will
    be a tuple having the corresponding shapes.</p>
  </blockquote>
  
  <p>The <code>outputs</code> tensor is a 3-D matrix but what does each row/column represent?</p>