PolyLR

class mmengine.optim.PolyLR(optimizer, *args, **kwargs)

Decays the learning rate of each parameter group in a polynomial decay scheme.

Notice that such decay can happen simultaneously with other changes to the parameter value from outside this scheduler.

Parameters

• optimizer (Optimizer or OptimWrapper) – Wrapped optimizer.

• eta_min (float) – Minimum learning rate at the end of scheduling. Defaults to 0.

• power (float) – The power of the polynomial. Defaults to 1.0.

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

• end (int) – Step at which to stop updating the parameters. 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 parameters are updated by epochs. Defaults to True.

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