39 lines
1.1 KiB
Python
39 lines
1.1 KiB
Python
_base_ = [
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'../_base_/models/byol.py',
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'../_base_/datasets/imagenet_byol.py',
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'../_base_/schedules/lars_coslr-200e_in1k.py',
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'../_base_/default_runtime.py',
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]
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# dataset summary
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data = dict(samples_per_gpu=256)
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# additional hooks
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# interval for accumulate gradient, total 8*256*2(interval)=4096
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update_interval = 2
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custom_hooks = [
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dict(type='BYOLHook', end_momentum=1., update_interval=update_interval)
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]
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# optimizer
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optimizer = dict(
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type='LARS',
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lr=4.8,
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momentum=0.9,
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weight_decay=1e-6,
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paramwise_options={
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'(bn|gn)(\\d+)?.(weight|bias)':
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dict(weight_decay=0., lars_exclude=True),
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'bias': dict(weight_decay=0., lars_exclude=True)
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})
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optimizer_config = dict(update_interval=update_interval)
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# fp16
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fp16 = dict(loss_scale=512.)
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# runtime settings
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# the max_keep_ckpts controls the max number of ckpt file in your work_dirs
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# if it is 3, when CheckpointHook (in mmcv) saves the 4th ckpt
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# it will remove the oldest one to keep the number of total ckpts as 3
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checkpoint_config = dict(interval=10, max_keep_ckpts=3)
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