not able to install tensorflow on server

Question

I am trying to use tensorflow on my college server, as some of the things that I have written are too heavy for my laptop. So I don't have sudo privileges. Below is what I unsuccessfully tried.

I am able to install tensorflow by pip install --user <url> . But when I import tensorflow I get the error glibc 2.17 not found.

I found this link which solved the exact same problem but when I run

virtualenv --system-site-packages ~/tensorflow

I get this error:

ImportError: No module named pkg_resources

For resolving this I tried:

wget https://bitbucket.org/pypa/setuptools/raw/bootstrap/ez_setup.py -O - | python

And then I get following error:

[Errno 13] Permission denied: '/opt/anaconda/lib/python2.7/site-packages/test-easy-install-10463.write-test'

And I don't have sudo access so I can't use sudo with above command.

For installing virtualenv I used:

curl -sL https://raw.githubusercontent.com/brainsik/virtualenv-burrito/master/virtualenv-burrito.sh | $SHELL

I think that the problem is with virtualenv setup but I tried removing it and installing virtualenv by:

pip install --user virtualenv

But this fails and I get:

InsecurePlatformWarning Could not find a version that satisfies the requirement vitualenv (from versions: ) No matching distribution found for vitualenv

I have looked at many (1,2) SO answers dealing with this problem but none work for me. I get stuck at some other error.

I am now stuck in a loop of errors without sudo privilege.

So, my question is that do I necessarily have to install virtualenv or can my problem of installing a working tensorflow be solved much simply.

It is a linux server and default python version is 2.6. So, I had to install 2.7 separately for my use.

Answer 1

Try building from source instead of using the precompiled binary version. That way you won't have to worry about the glibc incompatibility with the installed system one.