I had the chance to play with Tensorflow, a high performance machine learning framework/library originally developed by Google. These are my installation notes.

I am working on the system with Red Hat Linux

cat /etc/redhat-release
# Output: Red Hat Enterprise Linux Server release 7.4 (Maipo)

The easiest option to install Tensorflow seems to be using Anaconda. I used the more lightweight version of Anaconda called Miniconda. To download and install Miniconda 3:

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
sh Miniconda3-latest-Linux-x86_64.sh

Accept the license, enter your preferred install location, then say ‘yes’ to prepend the install location to your $PATH environment variable.

Once conda has been installed, now it’s time to install Tensorflow. The instructions come from this Tensorflow page, but adapted a little bit for my purpose. I just downloaded the tensorflow-gpu package that is provided by Anaconda.

conda update conda
conda create -n tensorflow_conda pip python=2.7
source activate tensorflow_conda
conda install -c anaconda cudatoolkit=9.0
conda install -c anaconda tensorflow-gpu

To validate the installation, try the following in python:

import tensorflow as tf
# Output: 1.8.0
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
# Output: Hello, TensorFlow!

When you leave, you can call source deactivate to exit the conda environment. To get back again, call source activate tensorflow_conda.

Note that when the conda environment isactivated, the $PATH is prepended with <your-install-location>/envs/tensorflow_conda/bin. In some cases, you might also want to prepend $LD_LIBRARY_PATH with <your-install-location>/envs/tensorflow_conda/lib. This will help tensorflow find and import all the necessary CUDA libraries such as libcudart.so.XYZ, libcublas.so.XYZ, libcudnn.so.XYZ and whatnot.

Finally, to also install other machine learning-related libraries:

pip install -U pip
pip install keras sklearn matplotlib jupyter

In case you want to remove the environment:

conda remove --name tensorflow_conda --all