40 lines
988 B
Python
40 lines
988 B
Python
_base_ = [
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'../_base_/models/convmixer/convmixer-1024-20.py',
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'../_base_/datasets/imagenet_bs64_convmixer_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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# schedule setting
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optim_wrapper = dict(
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optimizer=dict(lr=0.01),
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clip_grad=dict(max_norm=5.0),
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)
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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=1e-3,
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by_epoch=True,
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begin=0,
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end=20,
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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=130,
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eta_min=1e-5,
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by_epoch=True,
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begin=20,
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end=150)
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]
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train_cfg = dict(by_epoch=True, max_epochs=150)
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# NOTE: `auto_scale_lr` is for automatically scaling LR
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# based on the actual training batch size.
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# base_batch_size = (10 GPUs) x (64 samples per GPU)
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auto_scale_lr = dict(base_batch_size=640)
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