Update trainer.py

sdfvae/trainer.py

@@ -59,9 +59,10 @@ class Trainer(object):
         # See https://arxiv.org/pdf/1606.05908.pdf, Page 9, Section 2.2 for details.
         # The constant items in the loss function (not the coefficients) can be any number here, or even omitted        
         # due to they have no any impact on gradientis propagation during training. So do in testing.
-        # 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}
+        # log(N(x|mu,sigma^2))
+        # = log{1/(sqrt(2*pi)*sigma)exp{-(x-mu)^2/(2*sigma^2)}} 
+        # = -0.5*{log(2*pi)+2*log(sigma)+[(x-mu)/exp{log(sigma)}]^2}
+        # Note that var = sigma^2, so “recon_seq_logvar” is more appropriate to be called “recon_seq_logsigma”, but the name does not the matter
         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))