title: Tensorflow's place holder's parameter shape as a list with None vale
body: <p>I am reading <a href="https://github.com/nvcuong/variational-continual-learning/blob/b0827e5bded789d6307d664413cc977893ae43ca/ddm/alg/cla_models_multihead.py" rel="nofollow noreferrer">this module</a> from this <a href="https://github.com/nvcuong/variational-continual-learning" rel="nofollow noreferrer">github repo</a>. In Class_NN(), they have defined to placeholders:</p>
  <pre><code>def __init__(self, input_size, hidden_size, output_size, training_size):
      # input and output placeholders
      self.x = tf.placeholder(tf.float32, [None, input_size])# type and size of the input - why do we have [none,]?
      self.y = tf.placeholder(tf.float32, [None, output_size])
      self.task_idx = tf.placeholder(tf.int32)
  </code></pre>
  <p>I know that the first parameter of tf.placeholder, tf.float32, is the type of value that x supposed to get and the second parameter is the shape of x as a tensor. Here the shape parameter is assigned as a list. What I don't understand is why the 0_indexed value in this list is None?</p>