title: Tensorflow uses too much memory when initializing with constants
body: <p>I've noticed a weird thing recently, Tensorflow seems to use too much memory when initializing the variables with constants. Can someone help me understand the example below?</p>
  
  <pre><code>$ python -m memory_profiler test.py 
  [0 1 2 3 4 5 6 7 8 9]
  Filename: test.py
  
  Line #    Mem usage    Increment   Line Contents
  ================================================
   4  144.531 MiB    0.000 MiB   @profile
   5                             def go():
   6  907.312 MiB  762.781 MiB    a = np.arange(100000000)
   7  910.980 MiB    3.668 MiB    s = tf.Session()
   8 1674.133 MiB  763.152 MiB    b = tf.Variable(a)
   9 3963.000 MiB 2288.867 MiB    s.run(tf.variables_initializer([b]))
  10 3963.145 MiB    0.145 MiB    print(s.run(b)[:10])
  </code></pre>