25 lines
670 B
Python
25 lines
670 B
Python
_base_ = [
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'../_base_/models/convnext/convnext-base.py',
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'../_base_/datasets/imagenet21k_bs128.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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# model setting
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model = dict(head=dict(num_classes=21841))
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# dataset setting
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data_preprocessor = dict(num_classes=21841)
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train_dataloader = dict(batch_size=128)
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# schedule setting
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optim_wrapper = dict(
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optimizer=dict(lr=4e-3),
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clip_grad=dict(max_norm=5.0),
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)
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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 = (32 GPUs) x (128 samples per GPU)
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auto_scale_lr = dict(base_batch_size=4096)
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