what does x = tf.placeholder(tf.float32, [None, 784]) means?

Question

I know basic use for tf.placeholder:

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.

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

Answer 1

From the tutorial: Deep MNIST for Experts

Here we assign it a shape of [None, 784], where 784 is the dimensionality of a single flattened 28 by 28 pixel MNIST image, and None indicates that the first dimension, corresponding to the batch size, can be of any size.