给定2d张量(矩阵),我想将它分成几个大小相等的小张量。您可以将其视为最大池的预处理。例如,
1 2 3 4 5 6 7 8
2 3 4 5 6 7 8 9
3 4 5 6 7 8 9 10
4 5 6 7 8 9 10 11
如果动态desired_size
为2 * 4,则输出应为:
1 2 3 4
2 3 4 5
5 6 7 8
6 7 8 9
3 4 5 6
4 5 6 7
7 8 9 10
8 9 10 11
我已经研究了slice
和gather
一段时间了。但我仍然不知道该怎么做。你能告诉我怎么做吗?提前谢谢!
答案 0 :(得分:1)
你可以使用tf.extract_image_patches
,尽管结果有些冗长:
import numpy as np
import tensorflow as tf
x = tf.constant(np.arange(8) + np.arange(1,5)[:,np.newaxis])
e = tf.extract_image_patches(x[tf.newaxis,:,:,tf.newaxis],
[1, 2, 4, 1], [1, 2, 4, 1], [1, 1, 1, 1], padding='VALID')
e = tf.reshape(e, [-1, 2, 4])
sess = tf.InteractiveSession()
e.eval()
# returns
# array([[[ 1, 2, 3, 4],
# [ 2, 3, 4, 5]],
# [[ 5, 6, 7, 8],
# [ 6, 7, 8, 9]],
# [[ 3, 4, 5, 6],
# [ 4, 5, 6, 7]],
# [[ 7, 8, 9, 10],
# [ 8, 9, 10, 11]]])
答案 1 :(得分:1)
我与tf.split()
绑定:
num_splits = 2
desired_size = (2, 4)
A = tf.constant(a)
C = tf.concat(tf.split(A, desired_size[0], 0),1)
D = tf.reshape(tf.concat(tf.split(C, num_splits*desired_size[0], 1), 0), (-1, desired_size[0], desired_size[1]))
#The result
[[[ 1 2 3 4]
[ 2 3 4 5]]
[[ 5 6 7 8]
[ 6 7 8 9]]
[[ 3 4 5 6]
[ 4 5 6 7]]
[[ 7 8 9 10]
[ 8 9 10 11]]]
# For num_splits = 4, desired_size = (2, 2) you get
[[[ 1 2]
[ 2 3]]
[[ 3 4]
[ 4 5]]
[[ 5 6]
[ 6 7]]
[[ 7 8]
[ 8 9]]
[[ 3 4]
[ 4 5]]
[[ 5 6]
[ 6 7]]
[[ 7 8]
[ 8 9]]
[[ 9 10]
[10 11]]]