It exposes the new local_threading option for the libE communications. This threading backend is not fully supported (cannot assign resources, etc.), and optimas only allows this option when using a FunctionEvaluator. However, it makes it possible to run optimas on a Jupyter notebook without issues (the default multiprocessing backend does not play well with IPython, especially on Windows and Mac, which use spawn).
This PR also removes the n_procs and n_gpus options of the FunctionEvaluator, which were anyways not having any effect.
Followup to https://github.com/Libensemble/libensemble/pull/1156.
It exposes the new
local_threading
option for the libE communications. This threading backend is not fully supported (cannot assign resources, etc.), and optimas only allows this option when using aFunctionEvaluator
. However, it makes it possible to run optimas on a Jupyter notebook without issues (the defaultmultiprocessing
backend does not play well with IPython, especially on Windows and Mac, which usespawn
).This PR also removes the
n_procs
andn_gpus
options of theFunctionEvaluator
, which were anyways not having any effect.