code: def resnet_param_groups(model: nn.Module) -> List[nn.Parameter]:
      layers = []
      layers += [nn.Sequential(model.conv1, model.bn1)]
      layers += [
          l
          for name, l in model.named_children()
          if name.startswith("layer")
      ]
  
      param_groups = [list(layer.parameters()) for layer in layers]
      check_all_model_params_in_groups2(model, param_groups)
  
      return param_groups
  
file_path: icevision/icevision/models/fastai/unet/backbones/resnet_configs.py
imports: from collections import OrderedDict
  from types import MethodType
  from typing import List
  from torch import nn
  import torchvision
  from icevision.utils.torch_utils import check_all_model_params_in_groups2
  from icevision.models.fastai.unet.backbones.backbone_config import TorchvisionUNetBackboneConfig
label_desc: Use image node_id 2 for calling a global function with example usage: resnet_param_groups(model) and returns: param_groups