34 lines
863 B
Python
34 lines
863 B
Python
_base_ = [
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'../_base_/models/twins_svt_base.py',
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'../_base_/datasets/imagenet_bs64_swin_224.py',
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'../_base_/schedules/imagenet_bs1024_adamw_swin.py',
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'../_base_/default_runtime.py'
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]
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data = dict(samples_per_gpu=128)
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paramwise_cfg = dict(_delete=True, norm_decay_mult=0.0, bias_decay_mult=0.0)
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# for batch in each gpu is 128, 8 gpu
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# lr = 5e-4 * 128 * 8 / 512 = 0.001
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optimizer = dict(
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type='AdamW',
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lr=5e-4 * 128 * 8 / 512,
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weight_decay=0.05,
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eps=1e-8,
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betas=(0.9, 0.999),
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paramwise_cfg=paramwise_cfg)
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optimizer_config = dict(_delete_=True, grad_clip=dict(max_norm=5.0))
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# learning policy
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lr_config = dict(
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policy='CosineAnnealing',
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by_epoch=True,
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min_lr_ratio=1e-2,
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warmup='linear',
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warmup_ratio=1e-3,
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warmup_iters=5,
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warmup_by_epoch=True)
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evaluation = dict(interval=1, metric='accuracy')
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