code: def _get_closed_form_lr(self) -> List[float]:
      denom = 1.0 + self.decay * self._step_count
      return [base_lr / denom for base_lr in self.base_lrs]
  
imports: import math
  import numpy
  from abc import abstractmethod
  from typing import Any
  from typing import Dict
  from typing import List
  from typing import Type
  from typing import Callable
  from typing import Optional
  from torch.optim import Optimizer
  from torch.optim.lr_scheduler import _LRScheduler
  from torch.optim.lr_scheduler import StepLR
  from torch.optim.lr_scheduler import CyclicLR
  from torch.optim.lr_scheduler import LambdaLR
  from torch.optim.lr_scheduler import ExponentialLR
  from torch.optim.lr_scheduler import CosineAnnealingLR
  from torch.optim.lr_scheduler import ReduceLROnPlateau
  from torch.optim.lr_scheduler import CosineAnnealingWarmRestarts
  from ..misc.toolkit import scheduler_requires_metric
label_desc: Use image node_id 3 for calling the LinearInverseScheduler obj's underlying member method code with example usage: obj._get_closed_form_lr() and returns: unknown