code: def make_layers(cfg, batch_norm=False):
      layers = []
      in_channels = 3
      for v in cfg:
          if v == "M":
              layers += [
                  nn.MaxPool2d(kernel_size=2, stride=2, ceil_mode=True)
              ]
          else:
              conv2d = nn.Conv2d(
                  in_channels, v, kernel_size=3, padding=1
              )
              if batch_norm:
                  layers += [
                      conv2d,
                      BatchNorm(v),
                      nn.ReLU(inplace=True),
                  ]
              else:
                  layers += [conv2d, nn.ReLU(inplace=True)]
              in_channels = v
      return nn.Sequential(*layers)
  
file_path: pfe-net/model/vgg.py
imports: import torch
  import torch.nn
  import torch.utils.model_zoo
label_desc: Use image node_id 1 for calling a global function with example usage: make_layers(cfg, batch_norm) and returns: nn