code: def forward(
      self, x, with_latent=False, fake_relu=False, no_relu=False
  ):
      assert (not fake_relu) and (
          not no_relu
      ), "fake_relu and no_relu not yet supported for this architecture"
      out = self.features(x)
      latent = out.view(out.size(0), -1)
      out = self.classifier(latent)
      if with_latent:
          return out, latent
      return out
  
file_path: robustness/robustness/cifar_models/vgg.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the VGG obj's underlying member method code with example usage: obj.forward(x, with_latent, fake_relu, no_relu) and returns: out, out,  latent