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# defaults to use registries in mmcls | |
default_scope = 'mmcls' | |
# configure default hooks | |
default_hooks = dict( | |
# record the time of every iteration. | |
timer=dict(type='IterTimerHook'), | |
# print log every 100 iterations. | |
logger=dict(type='LoggerHook', interval=100), | |
# enable the parameter scheduler. | |
param_scheduler=dict(type='ParamSchedulerHook'), | |
# save checkpoint per epoch. | |
checkpoint=dict(type='CheckpointHook', interval=1), | |
# set sampler seed in distributed evrionment. | |
sampler_seed=dict(type='DistSamplerSeedHook'), | |
# validation results visualization, set True to enable it. | |
visualization=dict(type='VisualizationHook', enable=False), | |
) | |
# configure environment | |
env_cfg = dict( | |
# whether to enable cudnn benchmark | |
cudnn_benchmark=False, | |
# set multi process parameters | |
mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), | |
# set distributed parameters | |
dist_cfg=dict(backend='nccl'), | |
) | |
# set visualizer | |
vis_backends = [dict(type='LocalVisBackend')] | |
visualizer = dict(type='ClsVisualizer', vis_backends=vis_backends) | |
# set log level | |
log_level = 'INFO' | |
# load from which checkpoint | |
load_from = None | |
# whether to resume training from the loaded checkpoint | |
resume = False | |
# Defaults to use random seed and disable `deterministic` | |
randomness = dict(seed=None, deterministic=False) | |