title: Why use None for the batch dimension in tensorflow?
body: <p>In the following code, the <code>None</code> is used to declare the size of the placeholders. </p>
  
  <pre><code>x_data = tf.placeholder(tf.int32, [None, max_sequence_length]) 
  y_output = tf.placeholder(tf.int32, [None])
  </code></pre>
  
  <p>As I know, this <code>None</code> is used to specify a variable batch dimension. But, in each code, we have a variable that shows the batch size, such as:</p>
  
  <pre><code>batch_size = 250
  </code></pre>
  
  <p>So, is there any reason to use <code>None</code> in such cases instead of simply declaring the placeholders as?</p>
  
  <pre><code>x_data = tf.placeholder(tf.int32, [batch_size, max_sequence_length]) 
  y_output = tf.placeholder(tf.int32, [batch_size])
  </code></pre>