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Whenever I use tensorflow, it displays the message "The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations" and 2 more similar messages. So I decided to build tensorflow from source to get rid of these messages. I'm using python 3.5 on Debian, and followed the instructions at https://www.tensorflow.org/install/install_sources (CPU only, no GPU). It asked during the build if the build should be for the machine it's doing the build on, I selected that, it included -march=native in some compiler option. Everything seemed to work, but when I ran python3 to test the build, it still gives the messages about "The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available ..." etc. How to I make the build use the hardware that it's running on?

zizzler
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  • Possible duplicate of [How to compile Tensorflow with SSE4.2 and AVX instructions?](http://stackoverflow.com/questions/41293077/how-to-compile-tensorflow-with-sse4-2-and-avx-instructions) – Salvador Dali Apr 22 '17 at 21:20

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There have been similar questions, and most of the answers to them are wrong. They say it's necessary to specify options like "--copt=-msse4.1 --copt=-msse4.2" in the build; it isn't. With the default option "-march=native", the GNU compiler will use SSE4.1 and SSE4.2 instructions if they are available.

The real problem is that if you build tensorflow from source, after installing the default build with pip, pip won't replace the old build with the new build. Everything will seem to work, but your old build remains in place in a directory under ~/.local. The solution is simply to uninstall the old tensorflow with pip ('pip uninstall tensorflow' or 'pip3 uninstall tensorflow'), and then rebuild from source. If you have already done a build, and wondered why nothing seemed to change, you needn't repeat the build but can just execute the last couple of steps (https://www.tensorflow.org/install/install_sources), namely bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg , followed by the pip install.

zizzler
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