123、TensorFlow的Job

# 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