In the middle of the desert you can say anything you want

12 Jul 2022

Slurm blues

Things that work for my specific instance:

  • ssh-copy-id to log in via public key
  • kitty +kitten ssh shamotskyi@v-slurm-login
  • sshfs
  • set -o vi in ~/.bashrc

Problem: how to install packages to run my stuff

Problem: how to install my python packages?

  • There’s no pip and I have no admin rights to install python3-ensurepip
  • pyxls that does “containers” is there

Sample from documentation about using pyxls:

srun --mem=16384 -c4 --gres=gpu:v100:2 \
--container-image tensorflow/tensorflow:latest-gpu \
--container-mounts=/slurm/$(id -u -n):/data \
--container-workdir /data \

Sadly my code needs some additional packages not installed by default there or anywhere, I need to install spacy language packs etc.

I have a Docker image I can use with everything installed on it, but it’s not on any public registry and I’m not gonna setup one just for this.

Solution - Container that gets saved!

You can start interactive jobs, in this case inside a docker container and it drops you inside a shell:

 srun --mem=16384 -c4 --gres=gpu:v100:2 --container-image tensorflow/tensorflow:latest-gpu --container-mounts=/slurm/$(id -u -n):/data --container-workdir /data --pty bash

Couldn’t add users or install packages because nothing was writeablea, so I open the documentation, find interesting flags there:

                              [pyxis] the image to use for the container
                              filesystem. Can be either a docker image given as
                              an enroot URI, or a path to a squashfs file on the
                              remote host filesystem.
--container-name=NAME   [pyxis] name to use for saving and loading the
                        container on the host. Unnamed containers are
                        removed after the slurm task is complete; named
                        containers are not. If a container with this name
                        already exists, the existing container is used and
                        the import is skipped.
--container-save=PATH   [pyxis] Save the container state to a squashfs
                        file on the remote host filesystem.
--container-writable    [pyxis] make the container filesystem writable
      --container-readonly    [pyxis] make the container filesystem read-only

So, I can get an image from Docker hub, save that container locally, and then provide that saved one instead of the image from the registry. Nice.

Or just give it a name, it will reuse it instead of reading it.

I can also make it writable.

=> I can create my own docker image, install everything there, and just go inside it to start trainings?

Final command:

 srun --mem=16384 -c4 --gres=gpu:v100:2 --container-image ./test_saved_path --container-save ./test_saved_path_2 --container-mounts=/slurm/$(id -u -n)/data:/data --container-workdir /data  --container-name my_container_name --container-writable --pty bash


  • Opens the container image locally, but more likely - reopens the one under its name
  • Opens a shell
  • Is writable, any changes I do get saved
  • At the end the container itself gets saved in ./test_saved_paths_2, just in case the open-the-named-container-by-name ever fails me.
  • As a bonus - I can do stuff to make the container usable, instead of the very raw default settings of the server I have no rights to change.

And a folder that locally I have mounted with sshfs that the docker image also has transparent access to makes the entire workflow fast.

The final solution was:

  1. Set up the perfect Container based on the TF docker image
  2. Create two scripts, one that just starts the training inside it and one that drops you in a shell in that container. Both based on the command above.

(But I still wonder how the rest are doing it, I can’t believe that’s the common way to run stuff that needs an installed package…)

Nel mezzo del deserto posso dire tutto quello che voglio.