Update trainer.py

                s_logvar, d_post_mean, d_post_logvar, d_prior_mean, d_prior_logvar):

        batch_size = original_seq.size(0)

        # See https://arxiv.org/pdf/1606.05908.pdf, Page 9, Section 2.2 for details.

        # N(x|mu,var)

        # log(N(x|mu,var))

        # = log{1/(sqrt(2*pi)*var)exp{-(x-mu)^2/(2*var^2)}} 

        # = -0.5*{log(2*pi)+2*log(var)+[(x-mu)/exp{log(var)}]^2}

        loglikelihood = -0.5 * torch.sum(torch.pow(((original_seq.float()-recon_seq_mu.float())/torch.exp(recon_seq_logvar.float())), 2)