- tensorFlow中常见的几种随机函数用法
- 参考博客:https://blog.csdn.net/uestc_c2_403/article/details/72810506
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 29 16:12:58 2018
@author: muli
"""
import tensorflow as tf
#tf.random_normal(shape,mean=0.0,stddev=1.0,dtype=tf.float32)
#tf.truncated_normal(shape, mean=0.0, stddev=1.0, dtype=tf.float32)
#tf.random_uniform(shape,minval=0,maxval=None,dtype=tf.float32)
#这几个都是用于生成随机数tensor的。尺寸是shape
#random_normal: 正太分布随机数,均值mean,标准差stddev
#truncated_normal:截断正态分布随机数,均值mean,标准差stddev,不过只保留[mean-2*stddev,mean+2*stddev]范围内的随机数
#random_uniform:均匀分布随机数,范围为[minval,maxval]
# 生成2*2的矩阵
x=tf.random_normal((2,2))
y=tf.truncated_normal((2,2))
z=tf.random_uniform((2,2),-1,1)
with tf.Session() as sess:
print(sess.run(x))
print("------------------------------------")
print(sess.run(y))
print("------------------------------------")
print(sess.run(z))