code: def _multi_period_targets(
      self, epochs, min_lr, max_lr, base_period, period_mult
  ):
      remaining_epochs = epochs
      current_period = base_period
      targets = list()
      while remaining_epochs > 0:
          period_epochs = min(remaining_epochs, current_period + 1)
          remaining_epochs -= period_epochs
          targets += self._single_period_targets(
              period_epochs, min_lr, max_lr, current_period
          )
          current_period = current_period * period_mult
      return targets
  
imports: from unittest.mock import Mock
  import numpy
  import pytest
  from sklearn.base import clone
  from torch.optim import SGD
  from torch.optim.lr_scheduler import CosineAnnealingLR
  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.lr_scheduler import CyclicLR
  from skorch import NeuralNetClassifier
  from skorch.callbacks.lr_scheduler import WarmRestartLR, LRScheduler
label_desc: Use image node_id 3 for calling the TestWarmRestartLR obj's underlying member method code with example usage: obj._multi_period_targets(epochs, min_lr, max_lr, base_period, period_mult) and returns: targets