CODEWITHSUNDEEP
pythontensorflow
Abhai Kollara
Abhai Kollara

Reputation: 675

How do I resolve these tensorflow warnings?

I just installed Tensorflow 1.0.0 using pip. When running, I get warnings like the one shown below.

W 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.

I get 5 more similar warning for SSE4.1, SSE4.2, AVX, AVX2, FMA.

Despite these warnings the program seems to run fine.

Upvotes: 14

Views: 11968

Answers (7)

Aashish Kumar
Aashish Kumar

Reputation: 2879

As the warnings say you should only compile TF with these flags if you need to make TF faster.

You can use TF environment variable TF_CPP_MIN_LOG_LEVEL and it works as follows:

  • It defaults to 0, displaying all logs
  • To filter out INFO logs set it to 1
  • WARNINGS additionally, 2
  • and to additionally filter out ERROR logs set it to 3

So you can do the following to silence the warnings:

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

Upvotes: 1

jcamdr
jcamdr

Reputation: 316

My proposed way to solve the problem:

#!/usr/bin/env python3
import os
import tensorflow as tf
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

Should work at least on any Debian or Ubuntu systems.

Upvotes: 5

Ajay Singh
Ajay Singh

Reputation: 1281

export TF_CPP_MIN_LOG_LEVEL=2 solved the problem for me on Ubuntu.

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

Upvotes: 6

123
123

Reputation: 315

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.

Upvotes: 0

dartdog
dartdog

Reputation: 10872

It would seem that the PIP build for the GPU is bad as well as I get the warnings with the GPU version and the GPU installed...

Upvotes: 0

Neil Halelamien
Neil Halelamien

Reputation: 13

It seems that even if you don't have a compatible (i.e. Nvidia) GPU, you can actually still install the precompiled package for tensorflow-gpu via pip install tensorflow-gpu. It looks like in addition to the GPU support it also supports (or at least doesn't complain about) the CPU instruction set extensions like SSE3, AVX, etc. The only downside I've observed is that the Python wheel is a fair bit larger: 90MB for tensorflow-gpu instead of 42MB for plain tensorflow.

On my machine without an Nvidia GPU I've confirmed that tensorflow-gpu 1.0 runs fine without displaying the cpu_feature_guard warnings.

Upvotes: 1

Christian Frei
Christian Frei

Reputation: 481

I don't know much about C, but I found this

bazel build --linkopt='-lrt' -c opt --copt=-mavx --copt=-msse4.2 --copt=-msse4.1 --copt=-msse3-k //tensorflow/tools/pip_package:build_pip_package

How you build you program?

Upvotes: 2

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