code: def __init__(self, prior_dist, params, *vaes):
      super(MMVAE, self).__init__()
      self.pz = prior_dist
      self.vaes = nn.ModuleList([vae(params) for vae in vaes])
      self.modelName = None  # filled-in per sub-class
      self.params = params
      self._pz_params = None
  
file_path: mmvae/src/models/mmvae.py
imports: from itertools import combinations
  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 MMVAE object from inherited base classes: nn with example: obj = MMVAE(prior_dist, params)