diff options
Diffstat (limited to 'resources/libraries/python/PLRsearch')
| -rw-r--r-- | resources/libraries/python/PLRsearch/PLRsearch.py | 25 |
1 files changed, 15 insertions, 10 deletions
diff --git a/resources/libraries/python/PLRsearch/PLRsearch.py b/resources/libraries/python/PLRsearch/PLRsearch.py index ce65fd2ec8..0e78cc936d 100644 --- a/resources/libraries/python/PLRsearch/PLRsearch.py +++ b/resources/libraries/python/PLRsearch/PLRsearch.py @@ -1,4 +1,4 @@ -# Copyright (c) 2021 Cisco and/or its affiliates. +# Copyright (c) 2022 Cisco and/or its affiliates. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at: @@ -564,6 +564,20 @@ class PLRsearch: :rtype: multiprocessing.Connection """ + boss_pipe_end, worker_pipe_end = multiprocessing.Pipe() + # Starting the worker first. Contrary to documentation + # https://docs.python.org/3/library/multiprocessing.html#multiprocessing.connection.Connection + # sending of large object without active listener on the other side + # results in a deadlock, not in a ValueError. + # See https://stackoverflow.com/questions/15137292/large-objects-and-multiprocessing-pipes-and-send + worker = multiprocessing.Process( + target=Integrator.try_estimate_nd, + args=(worker_pipe_end, 10.0, self.trace_enabled) + ) + worker.daemon = True + worker.start() + + # Only now it is safe to send the function to compute with. def value_logweight_func(trace, x_mrr, x_spread): """Return log of critical rate and log of likelihood. @@ -609,15 +623,6 @@ class PLRsearch: return value, logweight dilled_function = dill.dumps(value_logweight_func) - boss_pipe_end, worker_pipe_end = multiprocessing.Pipe() - # Do not send yet, run the worker first to avoid a deadlock. - # See https://stackoverflow.com/a/15716500 - worker = multiprocessing.Process( - target=Integrator.try_estimate_nd, - args=(worker_pipe_end, 10.0, self.trace_enabled) - ) - worker.daemon = True - worker.start() boss_pipe_end.send( (dimension, dilled_function, focus_tracker, max_samples) ) |