47 lines
1.1 KiB
Python
47 lines
1.1 KiB
Python
_base_ = [
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'../_base_/models/resnet50.py',
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'../_base_/datasets/imagenet_bs256_rsb_a12.py',
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'../_base_/schedules/imagenet_bs2048_rsb.py',
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'../_base_/default_runtime.py'
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]
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# model settings
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model = dict(
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backbone=dict(
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norm_cfg=dict(type='SyncBN', requires_grad=True),
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drop_path_rate=0.05,
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),
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head=dict(loss=dict(use_sigmoid=True)),
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train_cfg=dict(augments=[
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dict(type='Mixup', alpha=0.1),
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dict(type='CutMix', alpha=1.0)
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]))
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# dataset settings
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train_dataloader = dict(sampler=dict(type='RepeatAugSampler', shuffle=True))
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# schedule settings
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optim_wrapper = dict(
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paramwise_cfg=dict(bias_decay_mult=0., norm_decay_mult=0.))
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param_scheduler = [
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# warm up learning rate scheduler
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dict(
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type='LinearLR',
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start_factor=0.0001,
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by_epoch=True,
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begin=0,
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end=5,
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# update by iter
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convert_to_iter_based=True),
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# main learning rate scheduler
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dict(
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type='CosineAnnealingLR',
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T_max=295,
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eta_min=1.0e-6,
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by_epoch=True,
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begin=5,
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end=300)
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]
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train_cfg = dict(by_epoch=True, max_epochs=300)
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