用法：

a1 = tf.nn.embedding_lookup(a, index)

index是索引，a是输入，通过index来选取a中对应的元素返回给a1，注意index是从0开始算起

例子：

import tensorflow as tfa = tf.constant([5, 6, 7, 8, 9])
index = tf.constant([1, 3])
a1 = tf.nn.embedding_lookup(a, index)with tf.Session() as sess:sess.run(tf.global_variables_initializer())print(sess.run(a1))

输出：[6 8]，可知输出了a中索引为1和3的元素

当a是二维数组时，输出第index行元素

import tensorflow as tfa = tf.constant([[0, 1, 2], [3, 4, 5], [6, 7, 8]])
index = tf.constant([1])
a1 = tf.nn.embedding_lookup(a, index)with tf.Session() as sess:sess.run(tf.global_variables_initializer())print(sess.run(a))print(sess.run(a1))

输出：

[[0 1 2]
 [3 4 5]
 [6 7 8]]            

 

[[3 4 5]]