kamurani / zaphod

Installing deep learning packages

conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
conda install -c conda-forge jupyterlab

# to make VScode recognise kernels on remote jupyter server
conda install ipykernel
conda install nb_conda_kernels

conda install lightning -c conda-forge
conda install -c conda-forge torchmetrics
conda install pyg -c pyg

Running VScode locally while connecting to Zaphod jupyter kernel

Make sure to run (base)$ conda install nb_conda_kernels to make environments visible.

# Using `zaphod` alias in ~/.ssh/config 
ssh zaphod
screen -R persistent_jupyter_server

# setup desired environment for jupyter server
# e.g. conda activate <ENV_NAME>

mkdir jupyter_servers_workdir

# start jupyter server
jupyter notebook \
--notebook-dir=$HOME/jupyter_servers_workdir \
--no-browser # stop browser opening on startup \
--port=8888 # leave as default


# oneliner
jupyter notebook --notebook-dir=$HOME/jupyter_servers_workdir --no-browser --port=8888

Should receive URL like http://localhost:${SERVER_PORT_NUMBER}/?token=5f11a3 ... where SERVER_PORT_NUMBER is 8888 in this case.

Exit screen instance using Ctrl+A+D.
[detached from 486658.persistent_jupyter_server]

Note: to reattach later, use screen -x persistent_jupyter_server

Return to local machine with exit. Connection to 129.... closed.

ssh -N -f -L $LOCAL_PORT_NUMBER:localhost:$SERVER_PORT_NUMBER $HOSTNAME

# i.e.
ssh -N -f -L 8888:localhost:8888 zaphod

Then, open VScode (locally) and open notebook. Connect to kernel and paste in URL (replacing SERVER_PORT_NUMBER with LOCAL_PORT_NUMBER)

Confirm connection with:

>>> import multiprocessing as mp 
>>> mp.cpu_count()
64