Tensorflow install fails with "compiletime version 3.5 of module does not match runtime version 3.6"

RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6

This is a known issue, which is got prioritized and likely to be fixed soon. Right now the workaround is to use python 3.5.

UPDATE:

The issue has been fixed in the nightly tensorflow builds: "tf-nightly and tf-nightly-gpu now has a python3.6 binary built from scratch for Linux."

I.e., the following command should work with python 3.6:

# tf-nightly or tf-nightly-gpupip3 install tf-nightly

Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX

This warning comes from the fact that the default tensorflow distributions are compiled without CPU extensions support (more on this here). If you want to get a CPU optimized tensorflow package, your only option is to build it yourself. It's a bit tedious, but absolutely doable. The build will produce the wheel file, which you can install with just

pip3 install /path/to/the/tensorflow.whl

But if you just want to suppress the warning, this will do:

import osos.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

I got the same issue and I was able to solve it by installing 1.3 version rather than using 1.4 of tensorflow. Use the following command to do so.

 pip3 install tensorflow==1.3.0

I encountered the same problem and I fixed it by:

pip install --ignore-installed tensorflow

The problem occurred because I complied a local version of tensorflow (to enable some CPU features) with python 3.5 earlier. I installed python 3.6 recently and the new tensorlfow already supported those CPU features, so I just installed the official version.

Update:

After some update of tensorflow the approach above doesn't work any more.

Another workaround is using virtual environment such as anaconda to create a python3.5 environment:

conda create -n py35 python=3.5source activate py35pip install tensorflow

To work with ipython or jupyter notebook, be sure to install ipykernel inside the virtual environment:

pip install ipykernel