Thanks for reporting. I confirm that the problem is related to the infrastructure and not to your notebooks. We use shared GPUs for the notebooks, and we cannot limit the amount of memory that each process can use. The only workaround is that each learner stops the notebook once finished, for releasing the resources and collectively reduce the odds of having the issue. Nothing else we can do for now. Just keep learners informed.