tensorflow运行提示未编译使用SSE4.1，SSE4.2等问题的解决方法

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发布于 2020-07-22 17:47:51

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发布于 2020-07-22 17:47:51

问题描述

每次运行TensorFlow 程序时，总是会提示未编译使用SSE4.1，SSE4.2等warnings 警告。

import tensorflow as tf
a = tf.constant(32)
b = tf.constant(2)
x = tf.add(a,b)

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

运行结果：

2018-06-22 20:45:54.006037: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
2018-06-22 20:45:54.031420: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
2018-06-22 20:45:54.035185: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2018-06-22 20:45:54.039599: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-06-22 20:45:54.043053: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-06-22 20:45:54.048017: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-06-22 20:45:54.054038: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2018-06-22 20:45:54.061881: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
34

解决方法

在开始时导入

import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'

即可解决，还你一个清爽的结果。解救强迫症。

import tensorflow as tf
import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
a = tf.constant(32)
b = tf.constant(2)
x = tf.add(a,b)

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

输出： 34

大功告成！

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原始发表：2018-06-22 ，如有侵权请联系 cloudcommunity@tencent.com 删除

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