3. Creation of a Python virtual environment

Here are some examples how you might use /vol/bitbucket in the course of a GPU cluster project.

Please note: Use a lab PC to prepare your Python environment, avoid running 'pip' or 'git' commands when logged in to gpucluster2.doc.ic.ac.uk or gpucluster3.doc.ic.ac.uk or you may encounter 'out of space' errors. For further guidance, consult the Python virtual environment guide)

Installation of Python Virtual Environment:

# connect to a random lab PC - remember to use a lab PC to create envs, use pip and git
ssh shell1.doc.ic.ac.uk
/vol/linux/bin/sshtolab
cd /vol/bitbucket/${USER}
python3 -m virtualenv /vol/bitbucket/${USER}/myvenv

Again, consult the Python Virtual Environment guide for more about managing virtual environments in your account.

Example Python environment

There exists a 'base' read-only environment, located at /vol/bitbucket/starter with Pytorch and tensorflow pre-installed using 'pip' and may suffice when first submitting jobs. Enable this in scripts with:

source /vol/bitbucket/starter/bin/activate

Follow the previous steps when you need to create an environment using your specific required pip/conda packages.