Multiprocessing#
By default, when you sample with PyMC3
, it will try to run chains in
parallel using Python’s multiprocessing module. This is pretty much always
what you want, but it can also cause some headaches (mostly on macOS or Windows)
for the large and computationally expensive models tackled by exoplanet
. In
particular, you might sometimes get hit by the “dreaded broken pipe” error where
your sampler crashes for no obvious reason or (worse!) you might find you
sampler hanging indefinitely before it even starts running. The official
PyMC3
solution is to use the mp_ctx="forkserver"
option when calling
pm.sample
on macOS or Windows. Unfortunately, this (for reasons that I don’t
totally understand) will often cause a huge performance hit that can increase
your runtime by orders of magnitude.
Throughout these documentation pages and for the Case Studies, we have tried to
design the example models such that you shouldn’t run into issues with
multiprocessing but, if you do, please open an issue on GitHub. For your own projects, if
you run into multiprocessing issues, you can try adjusting the mp_ctx
and
pickle_backend
parameters (see the PyMC3 docs), or as a last
resort, set cores=1
to get serial sampling.