code: def __init__(self, hidden_dim, latent_dim, input_dim):
      super(VAE, self).__init__()
  
      self.encoder = Encoder(hidden_dim, latent_dim, input_dim)
      self.prior = CompositePrior(hidden_dim, latent_dim, input_dim)
      self.decoder = nn.Linear(latent_dim, input_dim)
  
imports: import numpy
  from copy import deepcopy
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new VAE object from inherited base classes: nn with example: obj = VAE(hidden_dim, latent_dim, input_dim)