code: def __init__(self):
      super().__init__()
      self.features = nn.Sequential(
          nn.Conv2d(1, 64, 3, 1, 1),
          nn.ReLU(inplace=True),
          nn.MaxPool2d(2, 2),
          nn.Conv2d(64, 128, 3, 1, 1),
          nn.ReLU(inplace=True),
          nn.MaxPool2d(2, 2),
          nn.Conv2d(128, 256, 3, 1, 1),
          nn.ReLU(inplace=True),
          nn.Conv2d(256, 256, 3, 1, 1),
          nn.ReLU(inplace=True),
          nn.MaxPool2d(2, 2),
          nn.Conv2d(256, 512, 3, 1, 1),
          nn.ReLU(inplace=True),
          nn.Conv2d(512, 512, 3, 1, 1),
          nn.ReLU(inplace=True),
          nn.MaxPool2d(2, 2),
      )
      self.embeddings = nn.Sequential(
          nn.Linear(512 * 24, 4096),
          nn.ReLU(inplace=True),
          nn.Linear(4096, 4096),
          nn.ReLU(inplace=True),
          nn.Linear(4096, 128),
          # nn.ReLU(inplace=True)
      )
  
imports: from torch import nn
label_desc: Use image node_id 1 to create a new VGG object from inherited base classes: nn with example: obj = VGG()