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# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Helper file for running the async data generation process in OSS."""
import contextlib
import multiprocessing
import multiprocessing.pool
def get_forkpool(num_workers, init_worker=None, closing=True):
pool = multiprocessing.Pool(processes=num_workers, initializer=init_worker)
return contextlib.closing(pool) if closing else pool
def get_threadpool(num_workers, init_worker=None, closing=True):
pool = multiprocessing.pool.ThreadPool(processes=num_workers,
initializer=init_worker)
return contextlib.closing(pool) if closing else pool
class FauxPool(object):
"""Mimic a pool using for loops.
This class is used in place of proper pools when true determinism is desired
for testing or debugging.
"""
def __init__(self, *args, **kwargs):
pass
def map(self, func, iterable, chunksize=None):
return [func(i) for i in iterable]
def imap(self, func, iterable, chunksize=1):
for i in iterable:
yield func(i)
def close(self):
pass
def terminate(self):
pass
def join(self):
pass
def get_fauxpool(num_workers, init_worker=None, closing=True):
pool = FauxPool(processes=num_workers, initializer=init_worker)
return contextlib.closing(pool) if closing else pool
def worker_job():
return "worker"
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