tile(
  input,
  multiples,
  name=None
)

import tensorflow as tf
a = tf.constant([7,19])
a1 = tf.tile(a,multiples=[3]) #第一个维度扩充3遍
b = tf.constant([[4,5],[3,5]])
b1 = tf.tile(b,multiples=[2,3])#第一个维度扩充2遍，第二个维度扩充3遍
with tf.Session() as sess:
  print(sess.run(a))
  print(sess.run(a1))
  print(sess.run(b))
  print(sess.run(b1))

# 将input的某一维度复制多少次, len(input.shape()) 等于 len(multiples)
# tf.tile(input, multiples, name=None)
t = tf.constant([[1, 1, 1, 9], [2, 2, 2, 9], [7, 7, 7, 9]])
# 第一维度和第二维度都保持不变
z0 = tf.tile(t, multiples=[1, 1])
# 第1维度不变, 第二维度复制为2份
z1 = tf.tile(t, multiples=[1, 2])
# 第1维度复制为两份, 第二维度不变
z2 = tf.tile(t, multiples=[2, 1])
# tf.contrib.seq2seq.tile_batch(encoder_outputs, multiplier=self.beam_size)
encoder_outputs = tf.constant([[[1, 3, 1], [2, 3, 2]], [[2, 3, 4], [2, 3, 2]]])
print(encoder_outputs.get_shape()) # (2, 2, 3)
# 将batch内的每个样本复制3次, tile_batch() 的第2个参数是一个 int 类型数据
z4 = tf.contrib.seq2seq.tile_batch(encoder_outputs, multiplier=3)

with tf.Session() as sess:
  print(sess.run(z0))
  print(sess.run(z1))
  print(sess.run(z2))
 输出: 
 [[1 1 1 9]
 [2 2 2 9]
 [7 7 7 9]]
 
[[1 1 1 9 1 1 1 9]
 [2 2 2 9 2 2 2 9]
 [7 7 7 9 7 7 7 9]]
 
[[1 1 1 9]
 [2 2 2 9]
 [7 7 7 9]
 [1 1 1 9]
 [2 2 2 9]
 [7 7 7 9]]
 
[[[1 3 1]
 [2 3 2]]

 [[1 3 1]
 [2 3 2]]

 [[1 3 1]
 [2 3 2]]

 [[2 3 4]
 [2 3 2]]

 [[2 3 4]
 [2 3 2]]

 [[2 3 4]
 [2 3 2]]]