code: def forward(self, x, c):
      c = c.view(c.shape[0], 1)
      c = torch.tensor(c).float()
      res = {}
      mc_samples = 50
      em, ev = self.encoder(torch.cat((x, c), 1))
      res["em"] = em
      res["ev"] = ev
      res["z"] = []
      res["x_pred"] = []
      res["mc_samples"] = mc_samples
      for _ in range(mc_samples):
          z = self.sample_latent_code(em, ev)
          x_pred = self.decoder(torch.cat((z, c), 1))
          res["z"].append(z)
          res["x_pred"].append(x_pred)
  
      return res
  
imports: import torch
  import torch.utils.data
  from torch import nn
label_desc: Use image node_id 6 for calling the CF_VAE obj's underlying member method code with example usage: obj.forward(x, c) and returns: res