title: How to feed a placeholder?
body: <p>I am trying to implement a simple feed forward network. However, I can't figure out how to feed a <code>Placeholder</code>. This example:</p>
  
  <pre><code>import tensorflow as tf
  
  num_input  = 2
  num_hidden = 3
  num_output = 2
  
  x  = tf.placeholder("float", [num_input, 1])
  W_hidden = tf.Variable(tf.zeros([num_hidden, num_input]))
  W_out    = tf.Variable(tf.zeros([num_output, num_hidden]))
  b_hidden = tf.Variable(tf.zeros([num_hidden]))
  b_out    = tf.Variable(tf.zeros([num_output]))
  
  h = tf.nn.softmax(tf.matmul(W_hidden,x) + b_hidden)
  
  sess = tf.Session()
  
  with sess.as_default():
      print h.eval()
  </code></pre>
  
  <p>Gives me the following error:</p>
  
  <pre><code>  ...
      results = self._do_run(target_list, unique_fetch_targets, feed_dict_string)
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 419, in _do_run
      e.code)
  tensorflow.python.framework.errors.InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder' with dtype float and shape dim { size: 2 } dim { size: 1 }
       [[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=[2,1], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
  Caused by op u'Placeholder', defined at:
    File "/home/sfalk/workspace/SemEval2016/java/semeval2016-python/slot1_tf.py", line 8, in &lt;module&gt;
      x  = tf.placeholder("float", [num_input, 1])
    ...
  </code></pre>
  
  <p>I have tried</p>
  
  <pre><code>tf.assign([tf.Variable(1.0), tf.Variable(1.0)], x)
  tf.assign([1.0, 1.0], x)
  </code></pre>
  
  <p>but that does not work apparently.</p>