Pyro: MCMC with parallel chains get stuck in jupyter notebook on Ubuntu

[neerajprad]

As reported by @activatedgeek. MCMC with multiprocessing seems to work fine on mac, and even Ubuntu when run from the terminal, but gets stuck in Ubuntu when run in the notebook environment. I am opening this issue so that we can investigate further if this is a common issue faced by other users.

Jupyter version:

jupyter-client==5.2.4
jupyter-console==6.0.0
jupyter-core==4.4.0
jupyterlab==1.2.5
jupyterlab-server==1.0.6

[fehiepsi]

I believe this is related to these issues: https://github.com/pytorch/pytorch/issues/17680 and https://github.com/pytorch/pytorch/issues/20375.

Not related but I put here some observations in a terminal for reference:

• Without torch.multiprocessing.set_start_method("spawn") (or forkserver) line, baseball example will fail with the default fork method due to this issue.
• Under spawn method, the default sharing strategy file_descriptor in Linux will lead to bad value(s) in fds_in_keep issue. This does not happen with forkserver.

[neerajprad]

I think #20375 is the reason why this fails - the default on Ubuntu and python 3.8 across all platforms is "spawn" context which causes issues. I can replicate it in mac too if I set mp_context="spawn". I suppose one solution would be to change the default depending on the notebook environment.

@activatedgeek - In the meantime, to get around this issue, you could try to use mp_context='forkserver' when running in the notebook. Let us know if that works, or still causes issues.

[fehiepsi]

It might be better to add a note/warning to MCMC class so that users know about these gross of PyTorch multiprocessing. WDYT? I worry about forkserver might not be available on some platform.

[activatedgeek]

Thanks for the info @fehiepsi

@neerajprad The issue seems to still exist with mp_context='forkserver'.