code: def learning_rate_decay(
      optimizer, epoch, decay_rate=0.1, decay_steps=10
  ):
      for param_group in optimizer.param_groups:
          param_group["lr"] = param_group["lr"] * (
              decay_rate ** (epoch // decay_steps)
          )
  
imports: import torch.nn.functional
  from .utils import *
  from .backbone import *
label_desc: Use image node_id 6 for calling a global function with example usage: learning_rate_decay(optimizer, epoch, decay_rate, decay_steps) without return types