深度学习-TF函数-layers.concatenate用法

环境： tensorfow 2.*

def concatenate(inputs, axis=-1, **kwargs):

axis=n表示从第n个维度进行拼接，对于一个三维矩阵，axis的取值可以为[-3, -2, -1, 0, 1, 2]。

代码

import numpy as np
import tensorflow as tf

t1 = tf.Variable(np.array([[[1, 2], [2, 3]], [[4, 4], [5, 3]]]))
t2 = tf.Variable(np.array([[[7, 4], [8, 4]], [[2, 10], [15, 11]]]))

d0 = tf.keras.layers.concatenate([t1, t2], axis=0)
d1 = tf.keras.layers.concatenate([t1, t2], axis=1)
d2 = tf.keras.layers.concatenate([t1, t2], axis=2)
d3 = tf.keras.layers.concatenate([t1, t2], axis=-1)

print(d0)
print(d1)
print(d2)
print(d3)

结果：

tf.Tensor(
[[[ 1  2]
  [ 2  3]]

 [[ 4  4]
  [ 5  3]]

 [[ 7  4]
  [ 8  4]]

 [[ 2 10]
  [15 11]]], shape=(4, 2, 2), dtype=int32)
tf.Tensor(
[[[ 1  2]
  [ 2  3]
  [ 7  4]
  [ 8  4]]

 [[ 4  4]
  [ 5  3]
  [ 2 10]
  [15 11]]], shape=(2, 4, 2), dtype=int32)
tf.Tensor(
[[[ 1  2  7  4]
  [ 2  3  8  4]]

 [[ 4  4  2 10]
  [ 5  3 15 11]]], shape=(2, 2, 4), dtype=int32)
tf.Tensor(
[[[ 1  2  7  4]
  [ 2  3  8  4]]

 [[ 4  4  2 10]
  [ 5  3 15 11]]], shape=(2, 2, 4), dtype=int32)

Process finished with exit code 0