code: def convert_reslayer(
      model_key, model_weight, state_dict, converted_names
  ):
      split_keys = model_key.split(".")
      layer, block, module = split_keys[:3]
      block_id = int(block[1:])
      layer_name = f"layer{int(layer[1:])}"
      block_name = f"{block_id - 1}"
  
      if block_id == 1 and module == "bn":
          new_key = (
              f"{layer_name}.{block_name}.downsample.1.{split_keys[-1]}"
          )
      elif block_id == 1 and module == "proj":
          new_key = (
              f"{layer_name}.{block_name}.downsample.0.{split_keys[-1]}"
          )
      elif module == "f":
          if split_keys[3] == "a_bn":
              module_name = "bn1"
          elif split_keys[3] == "b_bn":
              module_name = "bn2"
          elif split_keys[3] == "c_bn":
              module_name = "bn3"
          elif split_keys[3] == "a":
              module_name = "conv1"
          elif split_keys[3] == "b":
              module_name = "conv2"
          elif split_keys[3] == "c":
              module_name = "conv3"
          new_key = f"{layer_name}.{block_name}.{module_name}.{split_keys[-1]}"
      else:
          raise ValueError(f"Unsupported conversion of key {model_key}")
      print(f"Convert {model_key} to {new_key}")
      state_dict[new_key] = model_weight
      converted_names.add(model_key)
  
imports: import argparse
  from collections import OrderedDict
  import torch
label_desc: Use image node_id 3 for calling a global function with example usage: convert_reslayer(model_key, model_weight, state_dict, converted_names) without return types