code: def densenet161(num_classes=1000, pretrained="imagenet"):
      r"""Densenet-161 model from
      `"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`
      """
      model = models.densenet161(pretrained=False)
      if pretrained is not None:
          settings = pretrained_settings["densenet161"][pretrained]
          model = load_pretrained(model, num_classes, settings)
      model = modify_densenets(model)
      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 9 for calling a global function with example usage: densenet161(num_classes, pretrained) and returns: model