code: def _squeezenet(version, pretrained, progress, **kwargs):
      model = SqueezeNet(version, **kwargs)
      if pretrained:
          arch = "squeezenet" + version
          state_dict = load_state_dict_from_url(
              model_urls[arch], progress=progress
          )
          model.load_state_dict(state_dict)
      return model
  
file_path: robustness/robustness/imagenet_models/squeezenet.py
imports: import torch
  import torch.nn
  import torch.nn.init
  from torch.hub import load_state_dict_from_url
  from ..tools.custom_modules import FakeReLUM
label_desc: Use image node_id 1 for calling a global function with example usage: _squeezenet(version, pretrained, progress) and returns: model