code: def normal_mb_neg_loglik(self, beta, mini_batch):
               
  
          mu, Y = self._mb_model(beta, mini_batch)
          return -np.sum(ss.norm.logpdf(Y, loc=mu, scale=self.latent_variables.z_list[-1].prior.transform(beta[-1])))
docs: Calculates the negative log-likelihood of the Normal model for a minibatch
  
          Parameters
          ----------
          beta : np.ndarray
              Contains untransformed starting values for latent variables
  
          mini_batch : int
              Size of each mini batch of data
  
          Returns
          ----------
          The negative logliklihood of the model