Tensorflow 中的导入警告

遗嘱_K

我在导入 tensorflow 时收到这些警告。

系统:Windows 10 64 位

蟒蛇:3.5.2

Tensorflow-CPU:1.1.0 每晚构建

2017-04-04 16:59:56.185045: W c:\tf_jenkins\home\workspace\nightly-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.
2017-04-04 16:59:56.185185: W c:\tf_jenkins\home\workspace\nightly-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.
2017-04-04 16:59:56.186551: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\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.
2017-04-04 16:59:56.187141: W c:\tf_jenkins\home\workspace\nightly-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.
2017-04-04 16:59:56.187629: W c:\tf_jenkins\home\workspace\nightly-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.
2017-04-04 16:59:56.188138: W c:\tf_jenkins\home\workspace\nightly-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.

虽然这些在 python 中运行时不是问题,但是当我从 MATLAB 调用 python 脚本时出现问题,我有一个朋友用 Theano 做了同样的事情,他告诉我你必须删除所有的错误和警告以便它在 MATLAB 上工作。我已经尝试了所有可用的解决方案,但仍然无法解决这些警告。

如果有人对此有答案,我将不胜感激

先感谢您

解析这个

如果您从源代码构建 tensorflow 并且使用高度实验性的bazel for windows

您可以使用这些参数:

bazel build -c opt --copt=-mavx --copt=-mavx2 \
   --copt=-mfma \
   --copt=-mfpmath=both \ 
   --copt=-msse4.2 \
   --config=cuda -k //tensorflow/tools/pip_package:build_pip_package

--config=cuda -k如果您没有使用 cuda 支持进行构建,请删除

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