code: def __init__(self, features, num_classes=1000, init_weights=True):
      super(VGG, self).__init__()
      self.features = features
      self.avgpool = nn.AdaptiveAvgPool2d((7, 7))
      self.classifier = nn.Sequential(
          nn.Linear(512 * 7 * 7, 4096),
          nn.ReLU(True),
          nn.Dropout(),
          nn.Linear(4096, 4096),
          nn.ReLU(True),
          nn.Dropout(),
          nn.Linear(4096, num_classes),
      )
      if init_weights:
          self._initialize_weights()
  
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 to create a new VGG object from inherited base classes: nn with example: obj = VGG(features, num_classes, init_weights)