np.dot()、np.multiply()、tf.matmul()、tf.multiply()

import tensorflow as tf
import numpy as np

x1 = ([[1, 2, 3], [1, 2, 3], [1, 2, 3]])
x2 = ([[2, 1, 1], [2, 1, 1], [2, 1, 1]])
y1 = np.dot(x1, x2)
y2 = np.multiply(x1, x2)
print('1、np.dot\n', y1)
print('2、np.multiply\n', y2)

x3 = tf.constant([[1, 2, 3], [1, 2, 3], [1, 2, 3]])
x4 = tf.constant([[2, 1, 1], [2, 1, 1], [2, 1, 1]])
y3 = tf.matmul(x3, x4)
y4 = tf.multiply(x3, x4)

with tf.Session() as sess:
    print('3、tf.matmul\n',sess.run(y3))
    print('4、tf.multiply\n',sess.run(y4))
    print('5、np.dot\n',sess.run(np.dot(x3,x4)))
    print('6、np.multiply\n',sess.run(np.multiply(x3,x4)))

输出：

1、np.dot
 [[12  6  6]
 [12  6  6]
 [12  6  6]]
2、np.multiply
 [[2 2 3]
 [2 2 3]
 [2 2 3]]
3、tf.matmul
 [[12  6  6]
 [12  6  6]
 [12  6  6]]
4、tf.multiply
 [[2 2 3]
 [2 2 3]
 [2 2 3]]
5、np.dot
 [[2 2 3]
 [2 2 3]
 [2 2 3]]
6、np.multiply
 [[2 2 3]
 [2 2 3]
 [2 2 3]]

• tf.matmul() 为矩阵乘法
• tf.multiply() 为矩阵点乘
• np.dot() 为矩阵乘法
• np.multiply() 为矩阵点乘

---

注意：

 print('np.dot\n',sess.run(np.dot(x3,x4)))
 print('np.multiply\n',sess.run(np.multiply(x3,x4)))

这两个都是输出：

 [[2 2 3]
 [2 2 3]
 [2 2 3]]

就不知道为什么了！