code: def resnet101(pretrained=False, root="./pretrain_models", **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)
      # Remove the following lines of comments
      # if u want to train from a pretrained model
      if pretrained:
          print(
              "===>> pretrained==True, returns a model pre-trained on ImageNet"
          )
          from .model_store import get_model_file
  
          model.load_state_dict(
              torch.load(get_model_file("resnet101", root=root)),
              strict=False,
          )
      return model
  
imports: import math
  import torch
  import torch.utils.model_zoo
  import torch.nn
label_desc: Use image node_id 3 for calling a global function with example usage: resnet101(pretrained, root) and returns: model