code: def resnet101(pretrained=False, **kwargs):
      """Constructs a ResNet-101 model.
  
      Args:
          pretrained (bool): If True, returns a model pre-trained on ImageNet
      """
      model = ResNet(Bottleneck, [3, 4, 23, 3], **kwargs)
      if pretrained:
          # model.load_state_dict(model_zoo.load_url(model_urls['resnet101']))
          model_path = "./initmodel/resnet101_v2.pth"
          model.load_state_dict(torch.load(model_path), strict=False)
      return model
  
imports: import torch
  import torch.nn
  import math
  import torch.utils.model_zoo
label_desc: Use image node_id 5 for calling a global function with example usage: resnet101(pretrained) and returns: model