code: def resnet50(**kwargs):
      r"""ResNet-50 model from
      `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_
  
      Args:
          pretrained (bool): If True, returns a model pre-trained on ImageNet
          progress (bool): If True, displays a progress bar of the download to stderr
      """
      return _resnet(Bottleneck, [3, 4, 6, 3], **kwargs)
  
file_path: deep-learning-for-image-processing/pytorch_segmentation/deeplab_v3/src/resnet_backbone.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 4 for calling a global function with example usage: resnet50() and returns: _resnet