code: def load_pretrained(model, num_classes, settings):
      assert (
          num_classes == settings["num_classes"]
      ), "num_classes should be {}, but is {}".format(
          settings["num_classes"], num_classes
      )
      state_dict = model_zoo.load_url(settings["url"])
      state_dict = update_state_dict(state_dict)
      model.load_state_dict(state_dict)
      model.input_space = settings["input_space"]
      model.input_size = settings["input_size"]
      model.input_range = settings["input_range"]
      model.mean = settings["mean"]
      model.std = settings["std"]
      return model
  
imports: from __future__ import print_function, division, absolute_import
  import torchvision.models
  import torch.utils.model_zoo
  import torch.nn.functional
  import types
  import re
label_desc: Use image node_id 2 for calling a global function with example usage: load_pretrained(model, num_classes, settings) and returns: model