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# optimizer
optimizer = dict(type='AdamW', lr=0.001, weight_decay=0.1)
optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer, clip_grad=None)
# learning policy
param_scheduler = [
dict(
type='LinearLR', start_factor=3e-2, begin=0, end=12000,
by_epoch=False),
dict(
type='PolyLRRatio',
eta_min_ratio=3e-2,
power=0.9,
begin=12000,
end=24000,
by_epoch=False),
dict(type='ConstantLR', by_epoch=False, factor=1, begin=24000, end=25000)
]
# training schedule for 25k
train_cfg = dict(type='IterBasedTrainLoop', max_iters=25000, val_interval=1000)
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')
default_hooks = dict(
timer=dict(type='IterTimerHook'),
logger=dict(type='LoggerHook', interval=50, log_metric_by_epoch=False),
param_scheduler=dict(type='ParamSchedulerHook'),
checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=2000),
sampler_seed=dict(type='DistSamplerSeedHook'),
visualization=dict(type='SegVisualizationHook'))
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