code: def get_lr(self):
      if not self._get_lr_called_within_step:
          warnings.warn(
              "To get the last learning rate computed by the scheduler, "
              "please use `get_last_lr()`.",
              DeprecationWarning,
          )
  
      return [
          self.eta_min
          + (base_lr * self.gamma**self.last_epoch - self.eta_min)
          * (1 + math.cos(math.pi * self.T_cur / self.T_i))
          / 2
          for base_lr in self.base_lrs
      ]
  
imports: import math
  import warnings
  import numpy
  from torch import nn
  from torch.optim.optimizer import Optimizer
  from torch.optim.lr_scheduler import _LRScheduler, LambdaLR, ExponentialLR, CyclicLR, MultiStepLR, ReduceLROnPlateau, CosineAnnealingLR, CosineAnnealingWarmRestarts
label_desc: Use image node_id 2 for calling the CosineAnnealingWarmRestartsWithDecay obj's underlying member method code with example usage: obj.get_lr() and returns: unknown