configs/_base_/schedules/schedule_25k.py

# 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'))