code: def resnet50(num_classes=1000, pretrained="imagenet"):
      """Constructs a ResNet-50 model."""
      model = models.resnet50(pretrained=False)
      if pretrained is not None:
          settings = pretrained_settings["resnet50"][pretrained]
          model = load_pretrained(model, num_classes, settings)
      model = modify_resnets(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 14 for calling a global function with example usage: resnet50(num_classes, pretrained) and returns: model