55 lines
1.4 KiB
Python
55 lines
1.4 KiB
Python
default_scope = 'mmpose'
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# hooks
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default_hooks = dict(
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timer=dict(type='IterTimerHook'),
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logger=dict(type='LoggerHook', interval=50),
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param_scheduler=dict(type='ParamSchedulerHook'),
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checkpoint=dict(type='CheckpointHook', interval=10),
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sampler_seed=dict(type='DistSamplerSeedHook'),
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visualization=dict(type='PoseVisualizationHook', enable=False),
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badcase=dict(
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type='BadCaseAnalysisHook',
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enable=False,
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out_dir='badcase',
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metric_type='loss',
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badcase_thr=5))
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# custom hooks
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custom_hooks = [
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# Synchronize model buffers such as running_mean and running_var in BN
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# at the end of each epoch
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dict(type='SyncBuffersHook')
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]
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# multi-processing backend
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env_cfg = dict(
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cudnn_benchmark=False,
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mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
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dist_cfg=dict(backend='nccl'),
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)
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# visualizer
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vis_backends = [
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dict(type='LocalVisBackend'),
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# dict(type='TensorboardVisBackend'),
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# dict(type='WandbVisBackend'),
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]
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visualizer = dict(
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type='PoseLocalVisualizer', vis_backends=vis_backends, name='visualizer')
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# logger
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log_processor = dict(
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type='LogProcessor', window_size=50, by_epoch=True, num_digits=6)
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log_level = 'INFO'
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load_from = None
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resume = False
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# file I/O backend
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backend_args = dict(backend='local')
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# training/validation/testing progress
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train_cfg = dict(by_epoch=True)
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val_cfg = dict()
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test_cfg = dict()
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