code: def forward(self, x):
      # N x 3 x 224 x 224
      x = self.features(x)
      # N x 512 x 7 x 7
      x = torch.flatten(x, start_dim=1)
      # N x 512*7*7
      x = self.classifier(x)
      return x
  
file_path: deep-learning-for-image-processing/pytorch_object_detection/train_coco_dataset/backbone/vgg_model.py
imports: import torch.nn
  import torch
label_desc: Use image node_id 2 for calling the VGG obj's underlying member method code with example usage: obj.forward(x) and returns: x