Tensorflow：在多个节点上运行代码

Question

import json
import tensorflow as tf

num_devices=3
with open('clusterspec.json', 'r') as f:
  clusterspec = json.load(f)

cluster = tf.train.ClusterSpec(clusterspec)


a = tf.constant(3)
b = tf.constant(2)

for i in range(num_devices):
    with tf.device("/job:worker/task:%d"%i):

            if( i == 0):
                    x = tf.mul(a,b)
            if( i == 1):
                    y = tf.mul(a,b)
            if( i == 2):
                    z = tf.mul(a,b)


server = tf.train.Server(cluster, job_name="master", task_index=0)
with tf.Session(server.target) as sess:
  print "here"
  print(sess.run([x,y,z]))

有人可以建议在多台机器上运行这个简单示例的更好方法。我不希望有三个不同的张量x，y和z。相反，我只想要一个张量，而根本不使用图中的分支。