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- _base_ = 'yolact_r50_1xb8-55e_coco.py'
- # optimizer
- optim_wrapper = dict(
- type='OptimWrapper',
- optimizer=dict(lr=8e-3),
- clip_grad=dict(max_norm=35, norm_type=2))
- # learning rate
- max_epochs = 55
- param_scheduler = [
- dict(type='LinearLR', start_factor=0.1, by_epoch=False, begin=0, end=1000),
- dict(
- type='MultiStepLR',
- begin=0,
- end=max_epochs,
- by_epoch=True,
- milestones=[20, 42, 49, 52],
- gamma=0.1)
- ]
- # NOTE: `auto_scale_lr` is for automatically scaling LR,
- # USER SHOULD NOT CHANGE ITS VALUES.
- # base_batch_size = (8 GPUs) x (8 samples per GPU)
- auto_scale_lr = dict(base_batch_size=64)
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