Resources:

To be able to use tensorflow you need to install it for your project. We recommend to use uv for creating your tensorflow python project.

Setup your project

uv will create and use a python virtual environment transparently so there is no need to create one separately. Use the storage on /scratch/userdata/$USER for your project, this is on the local disk of the ada-Xs as not all have the same python versions so the virtual environment must be recreated for every ada-X.

Initialize the project

export UV_NO_CACHE=1
cd /scratch/userdata/$USER

uv init new-uv-project

Install tensorflow and cuda in the project

cd /scratch/userdata/$USER/new-uv-project
uv add tensorflow[and-cuda]

# if you didn't set UV_NO_CACHE your cache could be big.
uv cache clean

Run your python code

To run you need to use uv you cannot simply use python as this will not load the virtual environment:

cd /scratch/userdata/$USER/new-uv-project
uv run main.py
  • As over time the central clients will have different python versions you need to reinitialize the virtual environment on each client you want to work on.
  • uv can install the cuda libraries apart from the python code.
  • Some cuda or tensorflow versions are not compatible with all GPUs here you find the list of GPUs installed in the central clients: <../central-clients/>