I’m using an account I have on a university server to do my fastai work, as it has a GPU (tesla p100) I can use. I was able to install fastai without a problem and I’ve been using this setup for my coursework without an issue.
(To be specific: I
ssh into my uni account, then I
ssh from there onto a GPU node. In that GPU-node shell, I
source activate my conda env, and try to do all my installing/updating in there.)
My account doesn’t have root permissions, however, so sometimes this causes issues when I’m trying to update conda, fastai, etc. In particular, I can’t run
conda update conda, or use
conda to update fastai, so I’ve been using
pip install --upgrade fastai, even though I’m working in a conda environment. But this has started causing issues, I’ve gotten some errors about how conda is out of date when I try this - these started this week.
When I run
conda update conda when I’m not inside my conda virtual environment, I get this message:
CondaIOError: Missing write permissions in: /gpfs1/arch/x86_64-rhel7/anaconda3-5.0.1
# You don't appear to have the necessary permissions to update packages
# into the install area '/gpfs1/arch/x86_64-rhel7/anaconda3-5.0.1'.
# However you can clone this environment into your home directory and
# then make changes to it.
# This may be done using the command:
# $ conda create -n my_root --clone="/gpfs1/arch/x86_64-rhel7/anaconda3-5.0.1"
But when I activate my conda environment and try the same command, I get:
$ conda update conda
PackageNotInstalledError: Package is not installed in prefix.
package name: conda
I haven’t been able to figure out how to get my env to recognize that conda is available as a package.
I know this is sort of a bespoke problem, but hoping someone may be able to help me out here - I’ve googled around for the errors I’m getting, but all the answers I’ve found seem to rely on the ability to exercise
sudo (or they involve doing Linux-y things beyond my current level of understanding).
I’m on RHEL 7.5, conda 4.3.30, Python 3.6.6. Thanks in advance!