TensorFlow 没有被编译为使用 SSE(等)指令，但这些是可用的 [英] TensorFlow wasn't compiled to use SSE (etc.) instructions, but these are available

问题描述

我是第一次使用一些示例代码运行 TensorFlow.运行我的代码时收到以下警告.有谁知道为什么会发生这种情况，以及如何解决它?

I am running TensorFlow for the first time using some example code. I got the following warnings when running my code. Does anybody know why this happened, and how to fix it?

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.

推荐答案

那些是警告(如冒号后的 W 所示.错误有一个 E 那里).

Those are warnings (as indicated by the W after the colon. Errors have an E there).

警告是指您的 CPU 支持 SSE 指令，这允许一些快速硬件并行操作.启用这些操作是一个编译时操作(即，要使用 SSE，您需要从源代码构建库以启用您所针对的特定 SSE 版本)，在这种情况下，您可能看看这个问题.

The warnings refer to the fact that your CPU supports SSE Instructions, which allow some fast in-hardware-parallel operations. Enabling these operations is a compile-time operation (i.e. to use SSE you need to build the library from the source enabling the specific SSE version you're targeting), in which case you might take a look at this question.

但是请注意，SSE 支持仅影响计算速度.Tensorflow 可以在有或没有 SSE 的情况下工作，但您的代码运行可能需要更长的时间.另请注意，这仅影响 CPU.如果您使用的是 Tensorflow 的 GPU 版本，则在 GPU 上运行的所有操作都不会受益于 SSE 指令.

Note, however, that SSE support influences only the computation speed. Tensorflow will work with or without SSE, but it might take longer for your code to run. Note, also, that this influences only the CPU. If you're using the GPU build of Tensorflow, all the operations run on the GPU will not benefit of SSE instructions.

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