title: Can some one explain logging device placement in tensorflow tutorial ?
body: <p><a href="https://www.tensorflow.org/tutorials/using_gpu" rel="nofollow noreferrer">Link for the tf tutorial</a></p>
  
  <pre><code># Creates a graph.
  with tf.device('/cpu:0'):
    a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
    b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
    c = tf.matmul(a, b)
  # Creates a session with log_device_placement set to True.
  sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
  # Runs the op.
  print sess.run(c)
  </code></pre>
  
  <p>In above example cpu:0 has assigned to the execution process. <strong>With the log_device_placement</strong> true. So this is solution for the above code that the have mentioned</p>
  
  <pre><code>Device mapping:
  /job:localhost/replica:0/task:0/gpu:0 -&gt; device: 0, name: Tesla K40c, pci bus
  id: 0000:05:00.0
  b: /job:localhost/replica:0/task:0/cpu:0
  a: /job:localhost/replica:0/task:0/cpu:0
  MatMul: /job:localhost/replica:0/task:0/gpu:0
  [[ 22.  28.]
   [ 49.  64.]]  
  </code></pre>
  
  <p>Now here place holders a, b and the matmul operation c which runs inside a session is inside the device log cpu:o but in the log device description <strong><em>why only MatMul has been executed in gpu:0 ?</em></strong></p>