tf.truncated_normal
tf.truncated_normal
狼啸风云
修改于 2022-09-04 21:05:54
修改于 2022-09-04 21:05:54
tf.truncated_normal(shape, mean, stddev) :shape表示生成张量的维度，mean是均值，stddev是标准差。这个函数产生正太分布，均值和标准差自己设定。这是一个截断的产生正太分布的函数，就是说产生正太分布的值如果与均值的差值大于两倍的标准差，那就重新生成。
例:
import tensorflow as tf;
import numpy as np;
import matplotlib.pyplot as plt;
c = tf.truncated_normal(shape=[10,10], mean=0, stddev=1)
with tf.Session() as sess:
print sess.run(c)
输出:
--------------------------------------------------------------------------
[[ 0.21928115 -0.28152597 -0.7381363 -0.48565105 -0.0991328 -0.2203394
-1.0337437 -1.3260287 -0.0947044 0.29130432]
[-0.32038376 -0.14401251 -0.3000437 1.90986 -0.02789464 -1.75405
0.75386107 0.40255374 0.50969696 -0.5144246 ]
[-0.05934289 -0.13676012 -0.8187295 1.4812258 -0.7164898 0.31804
-0.11366758 -0.22108728 -0.2409874 0.36390948]
[ 1.709577 -0.20038871 0.40611205 0.9113553 -0.29350016 0.7514032
0.10839624 -0.46098515 0.557274 0.38821268]
[ 0.48130617 1.1131536 -1.1356065 0.41551134 0.14280558 0.56424123
-1.1711147 -0.58633757 -0.4785279 -1.3436842 ]
[-0.9562587 -0.20193478 -0.7506948 0.9922889 -0.7112647 -1.2335519
-1.0257992 0.18601827 -1.9078422 -0.57947254]
[-0.18983668 -0.59639853 0.1502351 -0.952213 -0.56599045 -0.4365256
1.390264 0.06290046 1.9184309 0.39992943]
[-0.16891228 0.7881672 -0.47331563 1.9109113 0.44252422 -0.12054163
-0.42039979 -0.65125275 0.02856164 -1.2874403 ]
[-0.15257804 -1.0795212 0.3381369 0.26832175 0.40943214 0.4222502
0.34631294 -0.10362091 0.70107377 -1.5168688 ]
[ 0.5576659 0.45390686 -0.7741634 1.3609529 -0.13846219 -0.31193045
0.06494585 0.52165216 -1.7784148 -1.1660533 ]]
----------------------------------------------------------------------------转载地址：https://blog.csdn.net/uestc_c2_403/article/details/72235565
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原始发表：2019年06月29日，如有侵权请联系 cloudcommunity@tencent.com 删除
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