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Add helpful hints to multiprocess doc for avoiding mem leaks #753

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6 changes: 6 additions & 0 deletions doc/tutorials/basic/part4.rst
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Expand Up @@ -53,6 +53,12 @@ toolbox.
import multiprocessing

pool = multiprocessing.Pool()
# OR use the following to ensure releasing memory after each evaluate call
# This helps in situation where an external library holds memory, ex: Tensorflow
# when maxtaskperchild is set to 1, a new process is forked after each completed task
# https://docs.python.org/3/library/multiprocessing.html#module-multiprocessing.pool
# pool = multiprocessing.Pool(maxtasksperchild=1)

toolbox.register("map", pool.map)

# Continue on with the evolutionary algorithm
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