code: def senet154(num_classes=1000, pretrained="imagenet"):
      model = SENet(
          SEBottleneck,
          [3, 8, 36, 3],
          groups=64,
          reduction=16,
          dropout_p=0.2,
          num_classes=num_classes,
      )
      if pretrained is not None:
          settings = pretrained_settings["senet154"][pretrained]
          initialize_pretrained_model(model, num_classes, settings)
      return model
  
imports: from __future__ import print_function, division, absolute_import
  import math
  from collections import OrderedDict
  import torch.nn
  from torch.utils import model_zoo
label_desc: Use image node_id 2 for calling a global function with example usage: senet154(num_classes, pretrained) and returns: model