class_docstr: Stochastic Gradient Descent with Warm Restarts (SGDR) scheduler.
  
  This scheduler sets the learning rate of each parameter group
  according to stochastic gradient descent with warm restarts (SGDR)
  policy. This policy simulates periodic warm restarts of SGD, where
  in each restart the learning rate is initialize to some value and is
  scheduled to decrease.
  
  Parameters
  ----------
  optimizer : torch.optimizer.Optimizer instance.
    Optimizer algorithm.
  
  min_lr : float or list of float (default=1e-6)
    Minimum allowed learning rate during each period for all
    param groups (float) or each group (list).
  
  max_lr : float or list of float (default=0.05)
    Maximum allowed learning rate during each period for all
    param groups (float) or each group (list).
  
  base_period : int (default=10)
    Initial restart period to be multiplied at each restart.
  
  period_mult : int (default=2)
    Multiplicative factor to increase the period between restarts.
  
  last_epoch : int (default=-1)
    The index of the last valid epoch.
  
  References
  ----------
  .. [1] Ilya Loshchilov and Frank Hutter, 2017, "Stochastic Gradient
      Descent with Warm Restarts,". "ICLR"
      `<https://arxiv.org/pdf/1608.03983.pdf>`_
code: def get_lr(self):
      epoch_idx = float(self.last_epoch)
      current_period = float(self.base_period)
      while epoch_idx / current_period > 1.0:
          epoch_idx -= current_period + 1
          current_period *= self.period_mult
  
      current_lrs = self._get_current_lr(
          self.min_lr, self.max_lr, current_period, epoch_idx
      )
      return current_lrs.tolist()
  
imports: import sys
  import warnings
  import numpy
  import torch
  from torch.optim.lr_scheduler import _LRScheduler
  from torch.optim.lr_scheduler import CosineAnnealingLR
  from torch.optim.lr_scheduler import CyclicLR
  from torch.optim.lr_scheduler import ExponentialLR
  from torch.optim.lr_scheduler import LambdaLR
  from torch.optim.lr_scheduler import MultiStepLR
  from torch.optim.lr_scheduler import ReduceLROnPlateau
  from torch.optim.lr_scheduler import StepLR
  from torch.optim.optimizer import Optimizer
  from skorch.callbacks import Callback
label_desc: Use image node_id 3 for calling the WarmRestartLR obj's underlying member method code with example usage: obj.get_lr() and returns: current_lrs