code: def forward(self, x):
      mu, log_var = self.encode(x)
      z = self.reparameterize(mu, log_var)
      x_reconst = self.decode(z)
      return x_reconst, mu, log_var
  
file_path: pytorch-tutorial/tutorials/03-advanced/variational_autoencoder/main.py
imports: import os
  import torch
  import torch.nn
  import torch.nn.functional
  import torchvision
  from torchvision import transforms
  from torchvision.utils import save_image
label_desc: Use image node_id 5 for calling the VAE obj's underlying member method code with example usage: obj.forward(x) and returns: x_reconst,  mu,  log_var