code: def resnext50_32x4d(num_classes=1000, include_top=True):
      # https://download.pytorch.org/models/resnext50_32x4d-7cdf4587.pth
      groups = 32
      width_per_group = 4
      return ResNet(
          Bottleneck,
          [3, 4, 6, 3],
          num_classes=num_classes,
          include_top=include_top,
          groups=groups,
          width_per_group=width_per_group,
      )
  
file_path: deep-learning-for-image-processing/pytorch_classification/Test5_resnet/model.py
imports: import torch.nn
  import torch
label_desc: Use image node_id 4 for calling a global function with example usage: resnext50_32x4d(num_classes, include_top) and returns: ResNet