Projekt_AI-Automatyczny_saper/venv/Lib/site-packages/torch/multiprocessing/pool.py
2021-06-01 17:38:31 +02:00

44 lines
1.6 KiB
Python

import multiprocessing.pool
import multiprocessing.util as util
from .queue import SimpleQueue
def clean_worker(*args, **kwargs):
import gc
multiprocessing.pool.worker(*args, **kwargs)
# Regular multiprocessing workers don't fully clean up after themselves,
# so we have to explicitly trigger garbage collection to make sure that all
# destructors are called...
gc.collect()
class Pool(multiprocessing.pool.Pool):
"""Pool implementation which uses our version of SimpleQueue.
This lets us pass tensors in shared memory across processes instead of
serializing the underlying data."""
def _setup_queues(self):
self._inqueue = SimpleQueue()
self._outqueue = SimpleQueue()
self._quick_put = self._inqueue._writer.send
self._quick_get = self._outqueue._reader.recv
def _repopulate_pool(self):
"""Bring the number of pool processes up to the specified number,
for use after reaping workers which have exited.
"""
for i in range(self._processes - len(self._pool)):
# changed worker -> clean_worker
args = (self._inqueue, self._outqueue,
self._initializer,
self._initargs, self._maxtasksperchild)
if hasattr(self, '_wrap_exception'):
args += (self._wrap_exception,)
w = self.Process(target=clean_worker, args=args)
self._pool.append(w)
w.name = w.name.replace('Process', 'PoolWorker')
w.daemon = True
w.start()
util.debug('added worker')