ApplioRVC-Inference / utils /multiprocess_utils.py
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import os
import traceback
from multiprocessing import Queue, Process
def chunked_worker(worker_id, map_func, args, results_queue=None, init_ctx_func=None):
ctx = init_ctx_func(worker_id) if init_ctx_func is not None else None
for job_idx, arg in args:
try:
if ctx is not None:
res = map_func(*arg, ctx=ctx)
else:
res = map_func(*arg)
results_queue.put((job_idx, res))
except:
traceback.print_exc()
results_queue.put((job_idx, None))
def chunked_multiprocess_run(map_func, args, num_workers=None, ordered=True, init_ctx_func=None, q_max_size=1000):
args = zip(range(len(args)), args)
args = list(args)
n_jobs = len(args)
if num_workers is None:
num_workers = int(os.getenv('N_PROC', os.cpu_count()))
results_queues = []
if ordered:
for i in range(num_workers):
results_queues.append(Queue(maxsize=q_max_size // num_workers))
else:
results_queue = Queue(maxsize=q_max_size)
for i in range(num_workers):
results_queues.append(results_queue)
workers = []
for i in range(num_workers):
args_worker = args[i::num_workers]
p = Process(target=chunked_worker, args=(
i, map_func, args_worker, results_queues[i], init_ctx_func), daemon=True)
workers.append(p)
p.start()
for n_finished in range(n_jobs):
results_queue = results_queues[n_finished % num_workers]
job_idx, res = results_queue.get()
assert job_idx == n_finished or not ordered, (job_idx, n_finished)
yield res
for w in workers:
w.join()
w.close()