TensorFlow tf.nn.max_pool实现池化操作方式

import tensorflow as tf
 
a=tf.constant([
  [[1.0,2.0,3.0,4.0],
  [5.0,6.0,7.0,8.0],
  [8.0,7.0,6.0,5.0],
  [4.0,3.0,2.0,1.0]],
  [[4.0,3.0,2.0,1.0],
   [8.0,7.0,6.0,5.0],
   [1.0,2.0,3.0,4.0],
   [5.0,6.0,7.0,8.0]]
 ])
 
a=tf.reshape(a,[1,4,4,2])
 
pooling=tf.nn.max_pool(a,[1,2,2,1],[1,1,1,1],padding='VALID')
with tf.Session() as sess:
 print("image:")
 image=sess.run(a)
 print (image)
 print("reslut:")
 result=sess.run(pooling)
 print (result)

image:
[[[[ 1. 2.]
 [ 3. 4.]
 [ 5. 6.]
 [ 7. 8.]]
 
 [[ 8. 7.]
 [ 6. 5.]
 [ 4. 3.]
 [ 2. 1.]]
 
 [[ 4. 3.]
 [ 2. 1.]
 [ 8. 7.]
 [ 6. 5.]]
 
 [[ 1. 2.]
 [ 3. 4.]
 [ 5. 6.]
 [ 7. 8.]]]]
reslut:
[[[[ 8. 7.]
 [ 6. 6.]
 [ 7. 8.]]
 
 [[ 8. 7.]
 [ 8. 7.]
 [ 8. 7.]]
 
 [[ 4. 4.]
 [ 8. 7.]
 [ 8. 8.]]]]

pooling=tf.nn.max_pool(a,[1,2,2,1],[1,2,2,1],padding='VALID')

reslut:
[[[[ 8. 7.]
 [ 7. 8.]]
 
 [[ 4. 4.]
 [ 8. 8.]]]]