code: def create_regnet(model_name="RegNetX_200MF", num_classes=1000):
      model_name = model_name.lower().replace("-", "_")
      if model_name not in model_cfgs.keys():
          print(
              "support model name: \n{}".format(
                  "\n".join(model_cfgs.keys())
              )
          )
          raise KeyError(
              "not support model name: {}".format(model_name)
          )
  
      model = RegNet(
          cfg=model_cfgs[model_name], num_classes=num_classes
      )
      return model
  
imports: from typing import Optional
  import numpy
  import torch
  import torch.nn
  from torch import Tensor
label_desc: Use image node_id 5 for calling a global function with example usage: create_regnet(model_name, num_classes) and returns: model