成功解决Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

灰太狼 2021-01-24 03:26 860阅读 0赞

## 解决问题 ##

在导入tensorflow后，进行运算时，出现了红色错误！

import tensorflow as tf

import numpy as np

![SouthEast][]

## 资料参考 ##

[Advanced Vector Extensions][] (AVX, also known as Sandy Bridge New Extensions) 先进的矢量扩展（AVX，也称为桑迪桥新的扩展）是从英特尔和英特尔在2008年3月提出的微处理器的X86指令集架构的扩展，第一次由英特尔支持，在第2011季度和以后的SoeBoE桥处理器装运。AMD与推土机处理器航运在Q3 2011。AVX提供了新的特性、新的指令和新的编码方案。AVX2将大多数整数命令扩展为256位，并介绍了融合乘法累加（FMA）操作。AVX-512扩展AVX到512位支持使用一个新的EVEX前缀编码由英特尔提出的2013年7月，第一次支持英特尔与骑士着陆处理器，在2016装运。

![70][]

![SouthEast 1][]

![SouthEast 2][]

import os 
       os.environ[ "TF_CPP_MIN_LOG_LEVEL"]= '1' # 这是默认的显示等级，显示所有信息 
       os.environ[ "TF_CPP_MIN_LOG_LEVEL"]= '2' # 只显示 warning 和 Error 
       os.environ[ "TF_CPP_MIN_LOG_LEVEL"]= '3' # 只显示 Error

## 思路分析 ##

参考网友的评论解释：这个意思其实是，您下载的TensorFlow太low了，根本没有通过兼容AVX来Compile。如果您下载源代码在该电脑上重新compile，就可以支持AVX。其实你的电脑是支持AVX的，只是编译好的TensorFlow不支持。

**网友分析比较正确请参考理解**

**1、第一位网友**

https://github.com/lakshayg/tensorflow-build 这有别人编译好的  
![20181227142223734.png][]

**2、第二位网友**  
![20181227141432272.png][]

**3、第三位网友**

社区里说需要从源代码安装TensorFlow，以编译支持SIMD指令集的TF，这样可以更快的使用tf，https://www.tensorflow.org/install/source

![20190825172337761.png][]

## 解决办法 ##

在最顶行写入

import os  
os.environ\['TF\_CPP\_MIN\_LOG\_LEVEL'\] = '2'

![SouthEast 3][]

此方法，只能可以临时屏蔽警告信息，看起来舒服了一些。因为博主能力有限，如果网友们，有更好的解决办法，群策群力，请留言探讨，共同学习啦！

[SouthEast]: /images/1611458736683.png
[Advanced Vector Extensions]: https://en.wikipedia.org/wiki/Advanced_Vector_Extensions#CPUs_with_AVX
[70]: /images/1611458664544.png
[SouthEast 1]: /images/1611458631884.png
[SouthEast 2]: /images/1611458606133.png
[20181227142223734.png]: /images/1611458579368.png
[20181227141432272.png]: /images/1611458554567.png
[20190825172337761.png]: /images/1611458533615.png
[SouthEast 3]: /images/1611458508295.png

成功解决Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

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