2021-12-28 17:34:27 +08:00
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_base_ = ['./regnetx-400mf_8xb128_in1k.py']
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# model settings
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model = dict(
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backbone=dict(type='RegNet', arch='regnetx_8.0gf'),
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head=dict(in_channels=1920, ))
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2022-06-01 14:11:53 +08:00
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# dataset settings
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train_dataloader = dict(batch_size=64)
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2021-12-28 17:34:27 +08:00
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2022-06-01 14:11:53 +08:00
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# schedule settings
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2022-06-02 17:11:09 +08:00
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# for batch_size 512, use lr = 0.4
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optim_wrapper = dict(optimizer=dict(lr=0.4))
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2022-07-14 19:15:49 +08:00
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2022-07-15 15:20:17 +08:00
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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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2022-07-14 19:15:49 +08:00
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# base_batch_size = (8 GPUs) x (64 samples per GPU)
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auto_scale_lr = dict(base_batch_size=512)
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