CPU instructions not compiled with TensorFlow

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南笙
南笙 2020-12-29 15:16

MacBook Air: OSX El Capitan

When I run TensorFlow code in terminal (python 3 tfpractice.py), I get a longer than normal waiting time to get back output

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  • 2020-12-29 15:50

    Those are simply warnings. They are just informing you if you build TensorFlow from source it can be faster on your machine. Those instructions are not enabled by default on the builds available I think to be compatible with more CPUs as possible. If you have any other doubts regarding this please feel free to ask, otherwise this can be closed.

    Try export TF_CPP_MIN_LOG_LEVEL=2

    https://github.com/tensorflow/tensorflow/issues/7778

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  • 2020-12-29 15:54

    You can also compile using bazel with opt arguments:

    bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-msse4.1 --copt=-msse4.2 //tensorflow/tools/pip_package:build_pip_package
    

    I think you can find something in this discussion: How to compile Tensorflow with SSE4.2 and AVX instructions?

    Good luck!

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  • 2020-12-29 15:56

    NOTE : These are not error messages but mere warning messages.

    The best way to maximise TF performance (apart from writing good code !!), is to compile it from the sources

    When you do that, TF would ask you for a variety of options which will also involve options for these instructions.

    In my own experience, compilation from the source is better in performance on an average.

    If you are doing some intensive processing that could be done on a GPU then that might also explain your waiting time. For GPU support you would need to do pip3 install tensorflow-gpu

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  • 2020-12-29 15:56

    These are warning which mean it may be faster to build tensorflow on your pc from source.

    However if you want to disable them, you may use the code below

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

    this should silence the warnings. 'TF_CPP_MIN_LOG_LEVEL' represents the Tensorflow environment variable responsible for logging. Also if you are on Ubuntu you may use this code below

    export TF_CPP_MIN_LOG_LEVEL=2 
    

    I hope this helps.

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