add with tf.device(d):

9/gpu_pi.py

@@ -3,18 +3,19 @@
 c = []
 #Distribute the work between the GPUs
 for d in ['/gpu:0', '/gpu:1', '/gpu:2', '/gpu:3']:
-    #Generate the random 2D samples
-    i=tf.constant(np.random.uniform(size=10000), shape=[5000,2])
-    with tf.Session() as sess:
-        tf.initialize_all_variables()
-        #Calculate the euclidean distance to the origin
-        distances=tf.reduce_sum(tf.pow(i,2),1)
-        #Sum the samples inside the circle
-        tempsum = sess.run(tf.reduce_sum(tf.cast(tf.greater_equal(tf.cast(1.0,tf.float64),distances),tf.float64)))
-        #append the current result to the results array
-        c.append( tempsum)
-    #Do the final ratio calculation on the CPU
-    with tf.device('/cpu:0'):
+    with tf.device(d):
+        #Generate the random 2D samples
+        i=tf.constant(np.random.uniform(size=10000), shape=[5000,2])
         with tf.Session() as sess:
-            sum = tf.add_n(c)
-            print (sess.run(sum/20000.0)*4.0)
+            tf.initialize_all_variables()
+            #Calculate the euclidean distance to the origin
+            distances=tf.reduce_sum(tf.pow(i,2),1)
+            #Sum the samples inside the circle
+            tempsum = sess.run(tf.reduce_sum(tf.cast(tf.greater_equal(tf.cast(1.0,tf.float64),distances),tf.float64)))
+            #append the current result to the results array
+            c.append( tempsum)
+#Do the final ratio calculation on the CPU
+with tf.device('/cpu:0'):
+    with tf.Session() as sess:
+        sum = tf.add_n(c)
+        print (sess.run(sum/20000.0)*4.0)