细分tf.multiply()、tf.matmul()、tf.scalar_mul()函数

1. tf.multiply()
   释义：将两个矩阵中对应元素各自相乘

示例：

import tensorflow as tf

X = tf.constant([[1, 2, 3], [4, 5 ,6]], dtype=tf.float32, name=None)
Y = tf.constant([[1, 1, 1], [2, 2 ,2]], dtype=tf.float32, name=None)
Z = tf.multiply(X, Y)       # 乘法操作，对应位置元素相乘

with tf.Session() as sess:
    print(sess.run(Z))

[[ 1.  2.  3.]
 [ 8. 10. 12.]]

2. tf.matmul()
   释义：矩阵乘法

示例

X = tf.constant([[1, 2, 3], [4, 5, 6]], dtype=tf.float32, name=None)
Y = tf.constant([[1, 2], [1, 2], [1, 2]], dtype=tf.float32, name=None)
Z = tf.matmul(X, Y)         # 矩阵乘法操作

with tf.Session() as sess:
    print(sess.run(Z))

[[ 6. 12.]
 [15. 30.]]

3. tf.scalar_mul()
   释义：标量和张量相乘（标量乘矩阵或向量）

示例：

x = tf.constant(2, dtype=tf.float32, name=None)

Y1 = tf.constant(3, dtype=tf.float32, name=None)
Z1 = tf.scalar_mul(x, Y1)         # 标量×标量

Y2 = tf.constant([1, 2, 3], dtype=tf.float32, name=None)
Z2 = tf.scalar_mul(x, Y2)         # 标量×向量

Y3 = tf.constant([[1, 2, 3], [4, 5, 6]], dtype=tf.float32, name=None)
Z3 = tf.scalar_mul(x, Y3)         # 标量×矩阵

with tf.Session() as sess:
    print(sess.run(Z1))
    print('='*30)

    print(sess.run(Z2))
    print('='*30)

    print(sess.run(Z3))

6.0
==============================
[2. 4. 6.]
==============================
[[ 2.  4.  6.]
 [ 8. 10. 12.]]