import tensorflow as tf
import numpy as np
x = np.asarray([[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]])
print("初始变量x的维度是:",'\n',np.shape(x))
print("初始变量x的值是:",'\n',x)
x_p = tf.placeholder(tf.int32,[2,2,3])
y = tf.reduce_sum(x_p, axis=0) #修改axis=0 ===> 隔维列的方向相加
with tf.Session() as sess:
y = sess.run(y,feed_dict={x_p:x})
print("降维求和后的y的维度是:",'\n',sess.run(tf.shape(y)))
print("降维求和后的y值是:",'\n',y)
输出:
初始变量x的维度是:
(2, 2, 3)
初始变量x的值是:
[[[ 1 2 3]
[ 4 5 6]]
[[ 7 8 9]
[10 11 12]]]
降维求和后的y的维度是:
[2 3]
降维求和后的y值是:
[[ 8 10 12]
[14 16 18]]
import tensorflow as tf
import numpy as np
x = np.asarray