code: def resnet50(pretrained=False, progress=True, **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(
          "resnet50",
          Bottleneck,
          [3, 4, 6, 3],
          pretrained,
          progress,
          **kwargs,
      )
  
imports: from collections import OrderedDict
  import torch
  from torch import nn
  from torch.jit.annotations import Dict
  from torch.nn import functional
label_desc: Use image node_id 5 for calling a global function with example usage: resnet50(pretrained, progress) and returns: _resnet