TensorFlow未编译为使用SSE（等）指令，但这些指令可用

Question

我是第一次运行TensorFlow并使用一些示例代码。运行我的代码时出现此错误。有谁知道为什么会这样，以及如何解决它？谢谢！

2017-03-31 02:12:59.346109: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\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.
2017-03-31 02:12:59.346968: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\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.
2017-03-31 02:12:59.346975: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow libbrary wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2017-03-31 02:12:59.346979: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\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.
2017-03-31 02:12:59.346983: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\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.
2017-03-31 02:12:59.346987: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\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.
2017-03-31 02:12:59.346991: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\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.
2017-03-31 02:12:59.346995: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\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.

Answer 1

这些是警告，而不是错误（由结肠后的W表示。错误在那里有E）。

警告指的是您的CPU支持SSE Instructions这一事实，它允许一些快速的硬件并行操作。启用这些操作是一个编译时操作（即使用SSE，您需要从源代码构建库，启用您所针对的特定SSE版本），在这种情况下，您可能需要take a look at this question。

但请注意，SSE支持仅影响计算速度。 Tensorflow可以使用或不使用SSE，但运行代码可能需要更长时间。另请注意，这仅影响CPU。如果您正在使用Tensorflow的GPU构建，则在GPU上运行的所有操作都不会受益于SSE指令。

Answer 2

要隐藏这些警告，您可以在实际代码之前执行此操作。

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

有关详细讨论，请参阅https://github.com/tensorflow/tensorflow/issues/7778

我希望，它可以帮助对方。 :)

Answer 3

这不是错误，只是警告说如果你从源代码构建TensorFlow，它可以在你的机器上更快。

就像警告说的那样，如果你需要更快地使用TF，你应该只用这些标志编译TF。

您可以使用TF环境变量TF_CPP_MIN_LOG_LEVEL，它的工作原理如下：

• 默认为0，显示所有日志
• 要过滤掉INFO日志，请将其设置为1
• WARNINGS另外，2
• 并额外过滤掉ERROR日志设置为3

因此，您可以执行以下操作来消除警告：

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

有关详细讨论，请参阅How to compile tensorflow using SSE4.1, SSE4.2, and AVX.