# 如果你在分布式环境中部署TensorFlow

# 你或许需要指定job name和task ID

# 来将变量放置在参数服务器上

# 将操作放在worker job

import tensorflow as tf

with tf.device("/job:ps/task:0"):

    weights_1 = tf.Variable(tf.truncated_normal([784, 100]))

    biases_1 = tf.Variable(tf.zeroes[100])

with tf.device("/job:ps/task:1"):

    weights_2 = tf.Variable(tf.truncated_normal([100, 10]))

    biases_2 = tf.Variable(tf.zeroes([10]))

with tf.device("/job:worker"):

    layer_1 = tf.matmul(train_batch, weights_1) + biases_1

    layer_2 = tf.matmul(train_batch, weights_2) + biases_2