code: def __init__(
      self, prior_dist, likelihood_dist, post_dist, enc, dec, params
  ):
      super(VAE, self).__init__()
      self.pz = prior_dist
      self.px_z = likelihood_dist
      self.qz_x = post_dist
      self.enc = enc
      self.dec = dec
      self.modelName = None
      self.params = params
      self._pz_params = None  # defined in subclass
      self._qz_x_params = None  # populated in `forward`
      self.llik_scaling = 1.0
  
file_path: mmvae/src/models/vae.py
imports: import torch
  import torch.nn
  from utils import get_mean, kl_divergence
  from vis import embed_umap, tensors_to_df
label_desc: Use image node_id 1 to create a new VAE object from inherited base classes: nn with example: obj = VAE(prior_dist, likelihood_dist, post_dist, enc, dec, params)