title: Tensorflow: When are variable assignments done in sess.run with a list?
body: <p>I have thought that variable assignments are done after all operations in a list given to sess.run, but the following code returns different results at different execution. It seems randomly run operations in the list and assign the variable after the run of the operation in the list.</p>
  
  <pre><code>a = tf.Variable(0)
  b = tf.Variable(1)
  c = tf.Variable(1)
  update_a = tf.assign(a, b + c)
  update_b = tf.assign(b, c + a)
  update_c = tf.assign(c, a + b)
  
  with tf.Session() as sess:
    sess.run(initialize_all_variables)
    for i in range(5):
      a_, b_, c_ = sess.run([update_a, update_b, update_c])
  </code></pre>
  
  <p>I'd like to know the timing of variable assignments.
  Which are correct: "update_x -> assign x -> ... -> udpate_z -> assign z" or "update_x -> udpate_y -> udpate_z -> assign a, b, c"? (where (x, y, z) is a permutation of (a, b, c))
  In addition, if there is a way that realize the latter assignment (assignment are done after all operations in the list are done), please let me know how to realize it.</p>