[Enhance] Add setup multi-processing both in train and test. (#671)

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Ma Zerun 2022-01-27 10:18:36 +08:00 committed by GitHub
parent 833152b1f4
commit f552419e45
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6 changed files with 130 additions and 3 deletions

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@ -1,5 +1,8 @@
# Copyright (c) OpenMMLab. All rights reserved.
from .collect_env import collect_env
from .logger import get_root_logger, load_json_log
from .setup_env import setup_multi_processes
__all__ = ['collect_env', 'get_root_logger', 'load_json_log']
__all__ = [
'collect_env', 'get_root_logger', 'load_json_log', 'setup_multi_processes'
]

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@ -0,0 +1,47 @@
# Copyright (c) OpenMMLab. All rights reserved.
import os
import platform
import warnings
import cv2
import torch.multiprocessing as mp
def setup_multi_processes(cfg):
"""Setup multi-processing environment variables."""
# set multi-process start method as `fork` to speed up the training
if platform.system() != 'Windows':
mp_start_method = cfg.get('mp_start_method', 'fork')
current_method = mp.get_start_method(allow_none=True)
if current_method is not None and current_method != mp_start_method:
warnings.warn(
f'Multi-processing start method `{mp_start_method}` is '
f'different from the previous setting `{current_method}`.'
f'It will be force set to `{mp_start_method}`. You can change '
f'this behavior by changing `mp_start_method` in your config.')
mp.set_start_method(mp_start_method, force=True)
# disable opencv multithreading to avoid system being overloaded
opencv_num_threads = cfg.get('opencv_num_threads', 0)
cv2.setNumThreads(opencv_num_threads)
# setup OMP threads
# This code is referred from https://github.com/pytorch/pytorch/blob/master/torch/distributed/run.py # noqa
if 'OMP_NUM_THREADS' not in os.environ and cfg.data.workers_per_gpu > 1:
omp_num_threads = 1
warnings.warn(
f'Setting OMP_NUM_THREADS environment variable for each process '
f'to be {omp_num_threads} in default, to avoid your system being '
f'overloaded, please further tune the variable for optimal '
f'performance in your application as needed.')
os.environ['OMP_NUM_THREADS'] = str(omp_num_threads)
# setup MKL threads
if 'MKL_NUM_THREADS' not in os.environ and cfg.data.workers_per_gpu > 1:
mkl_num_threads = 1
warnings.warn(
f'Setting MKL_NUM_THREADS environment variable for each process '
f'to be {mkl_num_threads} in default, to avoid your system being '
f'overloaded, please further tune the variable for optimal '
f'performance in your application as needed.')
os.environ['MKL_NUM_THREADS'] = str(mkl_num_threads)

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@ -14,7 +14,7 @@ line_length = 79
multi_line_output = 0
known_standard_library = pkg_resources,setuptools
known_first_party = mmcls
known_third_party = PIL,matplotlib,mmcv,mmdet,modelindex,numpy,onnxruntime,packaging,pytest,pytorch_sphinx_theme,requests,rich,sphinx,tensorflow,torch,torchvision,ts
known_third_party = PIL,cv2,matplotlib,mmcv,mmdet,modelindex,numpy,onnxruntime,packaging,pytest,pytorch_sphinx_theme,requests,rich,sphinx,tensorflow,torch,torchvision,ts
no_lines_before = STDLIB,LOCALFOLDER
default_section = THIRDPARTY

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@ -0,0 +1,68 @@
# Copyright (c) OpenMMLab. All rights reserved.
import multiprocessing as mp
import os
import platform
import cv2
from mmcv import Config
from mmcls.utils import setup_multi_processes
def test_setup_multi_processes():
# temp save system setting
sys_start_mehod = mp.get_start_method(allow_none=True)
sys_cv_threads = cv2.getNumThreads()
# pop and temp save system env vars
sys_omp_threads = os.environ.pop('OMP_NUM_THREADS', default=None)
sys_mkl_threads = os.environ.pop('MKL_NUM_THREADS', default=None)
# test config without setting env
config = dict(data=dict(workers_per_gpu=2))
cfg = Config(config)
setup_multi_processes(cfg)
assert os.getenv('OMP_NUM_THREADS') == '1'
assert os.getenv('MKL_NUM_THREADS') == '1'
# when set to 0, the num threads will be 1
assert cv2.getNumThreads() == 1
if platform.system() != 'Windows':
assert mp.get_start_method() == 'fork'
# test num workers <= 1
os.environ.pop('OMP_NUM_THREADS')
os.environ.pop('MKL_NUM_THREADS')
config = dict(data=dict(workers_per_gpu=0))
cfg = Config(config)
setup_multi_processes(cfg)
assert 'OMP_NUM_THREADS' not in os.environ
assert 'MKL_NUM_THREADS' not in os.environ
# test manually set env var
os.environ['OMP_NUM_THREADS'] = '4'
config = dict(data=dict(workers_per_gpu=2))
cfg = Config(config)
setup_multi_processes(cfg)
assert os.getenv('OMP_NUM_THREADS') == '4'
# test manually set opencv threads and mp start method
config = dict(
data=dict(workers_per_gpu=2),
opencv_num_threads=4,
mp_start_method='spawn')
cfg = Config(config)
setup_multi_processes(cfg)
assert cv2.getNumThreads() == 4
assert mp.get_start_method() == 'spawn'
# revert setting to avoid affecting other programs
if sys_start_mehod:
mp.set_start_method(sys_start_mehod, force=True)
cv2.setNumThreads(sys_cv_threads)
if sys_omp_threads:
os.environ['OMP_NUM_THREADS'] = sys_omp_threads
else:
os.environ.pop('OMP_NUM_THREADS')
if sys_mkl_threads:
os.environ['MKL_NUM_THREADS'] = sys_mkl_threads
else:
os.environ.pop('MKL_NUM_THREADS')

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@ -14,6 +14,7 @@ from mmcv.runner import get_dist_info, init_dist, load_checkpoint
from mmcls.apis import multi_gpu_test, single_gpu_test
from mmcls.datasets import build_dataloader, build_dataset
from mmcls.models import build_classifier
from mmcls.utils import setup_multi_processes
# TODO import `wrap_fp16_model` from mmcv and delete them from mmcls
try:
@ -119,6 +120,10 @@ def main():
cfg = mmcv.Config.fromfile(args.config)
if args.cfg_options is not None:
cfg.merge_from_dict(args.cfg_options)
# set multi-process settings
setup_multi_processes(cfg)
# set cudnn_benchmark
if cfg.get('cudnn_benchmark', False):
torch.backends.cudnn.benchmark = True

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@ -15,7 +15,7 @@ from mmcls import __version__
from mmcls.apis import init_random_seed, set_random_seed, train_model
from mmcls.datasets import build_dataset
from mmcls.models import build_classifier
from mmcls.utils import collect_env, get_root_logger
from mmcls.utils import collect_env, get_root_logger, setup_multi_processes
def parse_args():
@ -90,6 +90,10 @@ def main():
cfg = Config.fromfile(args.config)
if args.cfg_options is not None:
cfg.merge_from_dict(args.cfg_options)
# set multi-process settings
setup_multi_processes(cfg)
# set cudnn_benchmark
if cfg.get('cudnn_benchmark', False):
torch.backends.cudnn.benchmark = True