code: def __init__(self, optimizer: Optimizer, max_epoch, gamma=0.9):
      def poly_lr(epoch):
          return (1.0 - float(epoch) / max_epoch) ** gamma
  
      super().__init__(optimizer, poly_lr)
  
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 1 to create a new PolyLR object from inherited base classes: LambdaLR with example: obj = PolyLR(optimizer, max_epoch, gamma)