code: def __init__(self, image_size=784, h_dim=400, z_dim=20):
      super(VAE, self).__init__()
      self.fc1 = nn.Linear(image_size, h_dim)
      self.fc2 = nn.Linear(h_dim, z_dim)
      self.fc3 = nn.Linear(h_dim, z_dim)
      self.fc4 = nn.Linear(z_dim, h_dim)
      self.fc5 = nn.Linear(h_dim, image_size)
  
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 1 to create a new VAE object from inherited base classes: nn with example: obj = VAE(image_size, h_dim, z_dim)