code: def resnext101(pretrained=True, **kwargs):
      """Constructs a ResNet-101 model.
  
      Args:
          pretrained (bool): If True, returns a model pre-trained on Places
      """
      model = ResNeXt(GroupBottleneck, [3, 4, 23, 3], **kwargs)
      if pretrained:
          model.load_state_dict(
              load_url(model_urls["resnext101"], **kwargs), strict=False
          )
      return model
  
file_path: pywick/pywick/models/segmentation/testnets/lg_kernel_exfuse/seg_resnext.py
imports: import os
  import sys
  import torch
  import torch.nn
  import math
label_desc: Use image node_id 2 for calling a global function with example usage: resnext101(pretrained) and returns: model