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Source code for mmrazor.utils.setup_env

# Copyright (c) OpenMMLab. All rights reserved.
import datetime
import os
import platform
import warnings

import cv2
import torch.multiprocessing as mp
from mmengine import DefaultScope


[docs]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)
[docs]def register_all_modules(init_default_scope: bool = True) -> None: """Register all modules in mmrazor into the registries. Args: init_default_scope (bool): Whether initialize the mmrazor default scope. When `init_default_scope=True`, the global default scope will be set to `mmrazor`, and all registries will build modules from mmrazor's registry node. To understand more about the registry, please refer to https://github.com/open-mmlab/mmengine/blob/main/docs/en/tutorials/registry.md Defaults to True. """ # noqa import mmrazor.datasets # noqa: F401,F403 import mmrazor.engine # noqa: F401,F403 import mmrazor.implementations # noqa: F401,F403 import mmrazor.models # noqa: F401,F403 import mmrazor.structures # noqa: F401,F403 if init_default_scope: never_created = DefaultScope.get_current_instance() is None \ or not DefaultScope.check_instance_created('mmrazor') if never_created: DefaultScope.get_instance('mmrazor', scope_name='mmrazor') return current_scope = DefaultScope.get_current_instance() if current_scope.scope_name != 'mmrazor': # type: ignore warnings.warn( 'The current default scope ' # type: ignore f'"{current_scope.scope_name}" is not ' '"mmrazor", `register_all_modules` will force the current' 'default scope to be "mmrazor". If this is not expected, ' 'please set `init_default_scope=False`.') # avoid name conflict new_instance_name = f'mmrazor-{datetime.datetime.now()}' DefaultScope.get_instance(new_instance_name, scope_name='mmrazor')
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