tf.stack

Posted 2023-02-02 青盏

tf.stack = tf.expand_dims + tf.concat

>>> t1 = tf.constant([[1, 2, 3], [4, 5, 6]])
>>> t2 = tf.constant([[7, 8, 9], [10, 11, 12]])
>>> c0=tf.stack([t1, t2], 0)
>>> c1=tf.stack([t1, t2], 1)
>>> c2=tf.stack([t1, t2], 2)
>>> with tf.Session() as sess:
...     print('c0')
...     print(sess.run(c0))
...     print('c1')
...     print(sess.run(c1))
...     print('c2')
...     print(sess.run(c2))


//结果如下：
c0
[[[ 1  2  3]
  [ 4  5  6]]

 [[ 7  8  9]
  [10 11 12]]]
c1
[[[ 1  2  3]
  [ 7  8  9]]

 [[ 4  5  6]
  [10 11 12]]]
c2
[[[ 1  7]
  [ 2  8]
  [ 3  9]]

 [[ 4 10]
  [ 5 11]
  [ 6 12]]]


>>> d1=tf.concat([tf.expand_dims(t1, axis=1), tf.expand_dims(t2, axis=1)], 1)
>>> d0=tf.concat([tf.expand_dims(t1, axis=0), tf.expand_dims(t2, axis=0)], 0)
>>> d2=tf.concat([tf.expand_dims(t1, axis=2), tf.expand_dims(t2, axis=2)], 2)
>>> with tf.Session() as sess:
...     print('d0')
...     print(sess.run(d0))
...     print('d1')
...     print(sess.run(d1))
...     print('d2')
...     print(sess.run(d2))


//结果如下： 
d0
[[[ 1  2  3]
  [ 4  5  6]]

 [[ 7  8  9]
  [10 11 12]]]
d1
[[[ 1  2  3]
  [ 7  8  9]]

 [[ 4  5  6]
  [10 11 12]]]
d2
[[[ 1  7]
  [ 2  8]
  [ 3  9]]

 [[ 4 10]
  [ 5 11]
  [ 6 12]]]