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import os
import traceback
from functools import partial
from tqdm import tqdm
def chunked_worker(worker_id, args_queue=None, results_queue=None, init_ctx_func=None):
ctx = init_ctx_func(worker_id) if init_ctx_func is not None else None
while True:
args = args_queue.get()
if args == '<KILL>':
return
job_idx, map_func, arg = args
try:
map_func_ = partial(map_func, ctx=ctx) if ctx is not None else map_func
if isinstance(arg, dict):
res = map_func_(**arg)
elif isinstance(arg, (list, tuple)):
res = map_func_(*arg)
else:
res = map_func_(arg)
results_queue.put((job_idx, res))
except:
traceback.print_exc()
results_queue.put((job_idx, None))
class MultiprocessManager:
def __init__(self, num_workers=None, init_ctx_func=None, multithread=False, queue_max=-1):
if multithread:
from multiprocessing.dummy import Queue, Process
else:
from multiprocessing import Queue, Process
if num_workers is None:
num_workers = int(os.getenv('N_PROC', os.cpu_count()))
self.num_workers = num_workers
self.results_queue = Queue(maxsize=-1)
self.jobs_pending = []
self.args_queue = Queue(maxsize=queue_max)
self.workers = []
self.total_jobs = 0
self.multithread = multithread
for i in range(num_workers):
if multithread:
p = Process(target=chunked_worker,
args=(i, self.args_queue, self.results_queue, init_ctx_func))
else:
p = Process(target=chunked_worker,
args=(i, self.args_queue, self.results_queue, init_ctx_func),
daemon=True)
self.workers.append(p)
p.start()
def add_job(self, func, args):
if not self.args_queue.full():
self.args_queue.put((self.total_jobs, func, args))
else:
self.jobs_pending.append((self.total_jobs, func, args))
self.total_jobs += 1
def get_results(self):
self.n_finished = 0
while self.n_finished < self.total_jobs:
while len(self.jobs_pending) > 0 and not self.args_queue.full():
self.args_queue.put(self.jobs_pending[0])
self.jobs_pending = self.jobs_pending[1:]
job_id, res = self.results_queue.get()
yield job_id, res
self.n_finished += 1
for w in range(self.num_workers):
self.args_queue.put("<KILL>")
for w in self.workers:
w.join()
def close(self):
if not self.multithread:
for w in self.workers:
w.terminate()
def __len__(self):
return self.total_jobs
def multiprocess_run_tqdm(map_func, args, num_workers=None, ordered=True, init_ctx_func=None,
multithread=False, queue_max=-1, desc=None):
for i, res in tqdm(
multiprocess_run(map_func, args, num_workers, ordered, init_ctx_func, multithread,
queue_max=queue_max),
total=len(args), desc=desc):
yield i, res
def multiprocess_run(map_func, args, num_workers=None, ordered=True, init_ctx_func=None, multithread=False,
queue_max=-1):
"""
Multiprocessing running chunked jobs.
Examples:
>>> for res in tqdm(multiprocess_run(job_func, args):
>>> print(res)
:param map_func:
:param args:
:param num_workers:
:param ordered:
:param init_ctx_func:
:param q_max_size:
:param multithread:
:return:
"""
if num_workers is None:
num_workers = int(os.getenv('N_PROC', os.cpu_count()))
# num_workers = 1
manager = MultiprocessManager(num_workers, init_ctx_func, multithread, queue_max=queue_max)
for arg in args:
manager.add_job(map_func, arg)
if ordered:
n_jobs = len(args)
results = ['<WAIT>' for _ in range(n_jobs)]
i_now = 0
for job_i, res in manager.get_results():
results[job_i] = res
while i_now < n_jobs and (not isinstance(results[i_now], str) or results[i_now] != '<WAIT>'):
yield i_now, results[i_now]
results[i_now] = None
i_now += 1
else:
for job_i, res in manager.get_results():
yield job_i, res
manager.close()
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