19 lines
573 B
Python
19 lines
573 B
Python
# optimizer
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optim_wrapper = dict(
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optimizer=dict(type='SGD', lr=0.8, momentum=0.9, weight_decay=5e-5))
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# learning policy
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param_scheduler = [
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dict(type='LinearLR', start_factor=0.1, by_epoch=True, begin=0, end=5),
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dict(type='CosineAnnealingLR', T_max=95, by_epoch=True, begin=5, end=100)
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]
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# train, val, test setting
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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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test_cfg = dict()
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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=1024)
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