code: def reconstruct(self, data):
      self.eval()
      with torch.no_grad():
          qz_x = self.qz_x(*self.enc(data))
          latents = qz_x.rsample()  # no dim expansion
          px_z = self.px_z(*self.dec(latents))
          recon = get_mean(px_z)
      return recon
  
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 7 for calling the VAE obj's underlying member method code with example usage: obj.reconstruct(data) and returns: recon