deep_learning_Function_tf.add()、tf.subtract()、tf.multiply()、tf.div()

时间:2023-03-10 04:49:26
deep_learning_Function_tf.add()、tf.subtract()、tf.multiply()、tf.div()

tf.add()、tf.subtract()、tf.multiply()、tf.div()函数介绍和示例

1. tf.add()

释义:加法操作

示例:

x = tf.constant(2, dtype=tf.float32, name=None)
y = tf.constant(3, dtype=tf.float32, name=None)
z = tf.add(x, y) # 加法操作 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.add(X, Y) # 矩阵加法操作,对应位置元素相加 with tf.Session() as sess:
print(sess.run(z))
print('='*30) print(sess.run(Z))
5.0
==============================
[[2. 3. 4.]
[6. 7. 8.]]

2. tf.subtract()

释义:减法操作

示例:

x = tf.constant(10, dtype=tf.float32, name=None)
y = tf.constant(4, dtype=tf.float32, name=None)
z = tf.subtract(x, y) # 减法操作 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.subtract(X, Y) # 矩阵减法操作,对应位置元素相减 with tf.Session() as sess:
print(sess.run(z))
print('='*30) print(sess.run(Z))
6.0
==============================
[[0. 1. 2.]
[2. 3. 4.]]

3. 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.]]

tf.matmul()和tf.scalar_mul()函数介绍和示例见csdn 博客

4. tf.div()

释义:除法操作

示例:

x = tf.constant(6, dtype=tf.float32, name=None)
y = tf.constant(3, dtype=tf.float32, name=None)
z = tf.div(x, y) # 标量/标量 X1 = tf.constant(6, dtype=tf.float32, name=None)
Y1 = tf.constant([[1, 2], [2, 3]], dtype=tf.float32, name=None)
Z1 = tf.div(X1, Y1) # 标量/矩阵 X2 = tf.constant([[6, 12], [6, 12]], dtype=tf.float32, name=None)
Y2 = tf.constant([[1, 2], [2, 3]], dtype=tf.float32, name=None)
Z2 = tf.div(X2, Y2) # 矩阵/矩阵,对应元素相除 with tf.Session() as sess:
print(sess.run(z))
print('='*30) print(sess.run(Z1))
print('='*30) print(sess.run(Z2))
2.0
==============================
[[6. 3.]
[3. 2.]]
==============================
[[6. 6.]
[3. 4.]]

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原文链接:https://blog.csdn.net/qq_36512295/article/details/100600390