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.
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.
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