Update tester.py

sdfvae/tester.py

@@ -82,6 +82,9 @@ class Tester(object):
     def loss_fn(self, original_seq, recon_seq_mu, recon_seq_logvar, s_mean, 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{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) 
                                          + 2 * recon_seq_logvar.float() 
                                          + np.log(np.pi*2))
@@ -98,6 +101,9 @@ class Tester(object):
     
     def loglikelihood_last_timestamp(self, x, recon_x_mu, recon_x_logvar):
         # See https://arxiv.org/pdf/1606.05908.pdf, Page 9, Section 2.2 for details.
+        # 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}
         llh = -0.5 * torch.sum(torch.pow(((x.float()-recon_x_mu.float())/torch.exp(recon_x_logvar.float())), 2) 
               + 2 * recon_x_logvar.float() 
               + np.log(np.pi*2))