Create UATs that test `dss` actually uses GPUs (NVIDIA)

### Why it needs to get done

In order to have e2e testing, an automated and repeatable testing framework is required to ensure `dss` can actually spin up Jupyter servers where GPU workloads can run on. Testing also covers the ML frameworks (pytorch and tensorflow) that users have access to, so this should also be considered.

### What needs to get done

1. Create notebooks that exercise Pytorch and Tensorflow in a CPU environment
2. Create notebooks that exercise Pytorch and Tensorflow in a GPU environment

### When is the task considered done

When the notebooks are placed in the [UATs](https://github.com/canonical/charmed-kubeflow-uats/tree/main) repository with instructions on how to run them.