title: Tensorflow `set_random_seed` not working
body: <h3>Calling <code>tf.set_random_seed(SEED)</code> has no effect that I can tell...</h3>
  
  <p>For example, running the code below several times <em>inside an IPython notebook</em> produces different output each time:</p>
  
  <pre><code>import tensorflow as tf
  tf.set_random_seed(42)
  sess = tf.InteractiveSession()
  a = tf.constant([1, 2, 3, 4, 5])
  tf.initialize_all_variables().run()
  a_shuf = tf.random_shuffle(a)
  print(a.eval())
  print(a_shuf.eval())
  sess.close()
  </code></pre>
  
  <p>If I set the seed explicitly: <code>a_shuf = tf.random_shuffle(a, seed=42)</code>, the output is the same after each run. But why do I need to set the seed if I already call <code>tf.set_random_seed(42)</code>?</p>
  
  <hr>
  
  <p>The equivalent code using numpy just works:</p>
  
  <pre><code>import numpy as np
  np.random.seed(42)
  a = [1,2,3,4,5]
  np.random.shuffle(a)
  print(a)
  </code></pre>