what does x = tf.placeholder(tf.float32, [None, 784]) means? : <p>I know basic use for tf.placeholder:</p>

<pre><code>x = tf.placeholder(tf.float32, shape=(1024, 1024))
y = tf.matmul(x, x)

with tf.Session() as sess:
   print(sess.run(y))  # ERROR: will fail because x was not fed.

   rand_array = np.random.rand(1024, 1024)
   print(sess.run(y, feed_dict={x: rand_array}))  # Will succeed.
</code></pre>

<p>I know the second parameter is about <strong>shape</strong>. However I don't know what is that mean when the first one is <strong>None</strong> in the shape. ex:[None,784].</p>
