tensorflow运行提示未编译使用SSE4.1,SSE4.2等问题的解决方法
时间:2022-07-22
本文章向大家介绍tensorflow运行提示未编译使用SSE4.1,SSE4.2等问题的解决方法,主要内容包括其使用实例、应用技巧、基本知识点总结和需要注意事项,具有一定的参考价值,需要的朋友可以参考一下。
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_jenkinshomeworkspacerelease-winmwindowspy35tensorflowcoreplatformcpu_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_jenkinshomeworkspacerelease-winmwindowspy35tensorflowcoreplatformcpu_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_jenkinshomeworkspacerelease-winmwindowspy35tensorflowcoreplatformcpu_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_jenkinshomeworkspacerelease-winmwindowspy35tensorflowcoreplatformcpu_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_jenkinshomeworkspacerelease-winmwindowspy35tensorflowcoreplatformcpu_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_jenkinshomeworkspacerelease-winmwindowspy35tensorflowcoreplatformcpu_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_jenkinshomeworkspacerelease-winmwindowspy35tensorflowcoreplatformcpu_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_jenkinshomeworkspacerelease-winmwindowspy35tensorflowcoreplatformcpu_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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