2020-07-09 23:59:10 +08:00
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# optimizer
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2022-06-02 17:11:09 +08:00
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optim_wrapper = dict(
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optimizer=dict(type='SGD', lr=0.1, momentum=0.9, weight_decay=0.0001))
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2020-07-09 23:59:10 +08:00
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# learning policy
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2022-05-23 17:31:57 +08:00
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param_scheduler = dict(
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type='MultiStepLR', by_epoch=True, milestones=[30, 60, 90], gamma=0.1)
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# train, val, test setting
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2022-07-12 16:10:59 +08:00
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train_cfg = dict(by_epoch=True, max_epochs=100, val_interval=1)
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val_cfg = dict()
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2022-05-23 17:31:57 +08:00
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test_cfg = dict()
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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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auto_scale_lr = dict(base_batch_size=256)
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