code: def convert_conv_fc(
      blobs, state_dict, caffe_name, torch_name, converted_names
  ):
      state_dict[torch_name + ".weight"] = torch.from_numpy(
          blobs[caffe_name + "_w"]
      )
      converted_names.add(caffe_name + "_w")
      if caffe_name + "_b" in blobs:
          state_dict[torch_name + ".bias"] = torch.from_numpy(
              blobs[caffe_name + "_b"]
          )
          converted_names.add(caffe_name + "_b")
  
imports: import argparse
  from collections import OrderedDict
  import torch
  from mmengine.fileio import load
label_desc: Use image node_id 2 for calling a global function with example usage: convert_conv_fc(blobs, state_dict, caffe_name, torch_name, converted_names) without return types