code: def get_params(self, base_lr):
      group1 = [
          self.encoder1,
          self.encoder2,
          self.encoder3,
          self.encoder4,
          self.encoder5,
      ]
      group2 = [
          self.decoder1,
          self.decoder2,
          self.decoder3,
          self.decoder4,
          self.decoder5,
          self.center,
          self.logit,
      ]
  
      params1 = []
      for x in group1:
          for p in x.parameters():
              params1.append(p)
  
      param_group1 = {"params": params1, "lr": base_lr / 5}
  
      params2 = []
      for x in group2:
          for p in x.parameters():
              params2.append(p)
      param_group2 = {"params": params2, "lr": base_lr}
  
      return [param_group1, param_group2]
  
imports: from torch import nn
  from torch.nn import functional
  import torch
  from torchvision import models
  from torchvision.models import resnet34, resnet101, resnet50, resnet152
  import torchvision
label_desc: Use image node_id 4 for calling the UNetResNetV4 obj's underlying member method code with example usage: obj.get_params(base_lr) and returns: list