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ConstantLR

class mmengine.optim.ConstantLR(optimizer, *args, **kwargs)[source]

Decays the learning rate value of each parameter group by a small constant factor until the number of epoch reaches a pre-defined milestone: end. Notice that such decay can happen simultaneously with other changes to the learning rate value from outside this scheduler.

Parameters
  • optimizer (Optimizer or OptimWrapper) – Wrapped optimizer.

  • factor (float) – The number we multiply learning rate until the milestone. Defaults to 1./3.

  • begin (int) – Step at which to start updating the learning rate. Defaults to 0.

  • end (int) – Step at which to stop updating the learning rate. Defaults to INF.

  • last_step (int) – The index of last step. Used for resume without state dict. Defaults to -1.

  • by_epoch (bool) – Whether the scheduled learning rate is updated by epochs. Defaults to True.

  • verbose (bool) – Whether to print the learning rate for each update. Defaults to False.

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