未验证 提交 796e56e7 编辑于 作者: dlagul's avatar dlagul 提交者： GitHub
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Update tester.py

上级 20305675

sdfvae/tester.py

+6 −0
原始行号 差异行号 差异行
@@ -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))