如何在没有来自源的安装张量流的情况下使用SSE4.1指令？

Question

我曾尝试根据其官方网站上的指南从源代码安装Tensorflow,但这种体验非常不愉快.

无法从源代码安装的直接结果我可以看到如下:

W 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.
W 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.
W 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.
W 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.
W 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.

我想知道是否有办法"使用SSE4.1指令"和上面提到的其他说明而无需从源代码安装Tensorflow.

谢谢!

Answer 1

如果不从源代码构建TensorFlow,则无法使用SIMD指令.

默认情况下,TensorFlow二进制文件没有进行此优化,以提高与更广泛的CPU架构的兼容性.

如果您想使警告静音,但您可以将其设置TF_CPP_MIN_LOG_LEVEL为2:

import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
import tensorflow as tf

此TF环境变量默认为0,显示所有日志.将其设置为1将过滤INFO日志并2另外使WARNING日志静音.