Module Contents



Decays the learning rate of each parameter group by linearly changing

class mmedit.engine.schedulers.reduce_lr_scheduler.ReduceLR(optimizer, mode: str = 'min', factor: float = 0.1, patience: int = 10, threshold: float = 0.0001, threshold_mode: str = 'rel', cooldown: int = 0, min_lr: float = 0.0, eps: float = 1e-08, **kwargs)[源代码]

Bases: mmengine.optim._ParamScheduler

Decays the learning rate of each parameter group by linearly changing small multiplicative 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 from outside this scheduler.


The learning rate of each parameter group will be update at regular


  • optimizer (Optimizer or OptimWrapper) – Wrapped optimizer.

  • mode (str, optional) – One of min, max. In min mode, lr will be reduced when the quantity monitored has stopped decreasing; in max mode it will be reduced when the quantity monitored has stopped increasing. Default: ‘min’.

  • factor (float, optional) – Factor by which the learning rate will be reduced. new_lr = lr * factor. Default: 0.1.

  • patience (int, optional) – Number of epochs with no improvement after which learning rate will be reduced. For example, if patience = 2, then we will ignore the first 2 epochs with no improvement, and will only decrease the LR after the 3rd epoch if the loss still hasn’t improved then. Default: 10.

  • threshold (float, optional) – Threshold for measuring the new optimum, to only focus on significant changes. Default: 1e-4.

  • threshold_mode (str, optional) – One of rel, abs. In rel mode, dynamic_threshold = best * ( 1 + threshold ) in ‘max’ mode or best * ( 1 - threshold ) in min mode. In abs mode, dynamic_threshold = best + threshold in max mode or best - threshold in min mode. Default: ‘rel’.

  • cooldown (int, optional) – Number of epochs to wait before resuming normal operation after lr has been reduced. Default: 0.

  • min_lr (float, optional) – Minimum LR value to keep. If LR after decay is lower than min_lr, it will be clipped to this value. Default: 0.

  • eps (float, optional) – Minimal decay applied to lr. If the difference between new and old lr is smaller than eps, the update is ignored. Default: 1e-8.

  • 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.

  • 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.

property in_cooldown[源代码]

Compute value using chainable form of the scheduler.

is_better(a, best)[源代码]
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