def forward(self, x, t):
    (out1, out2) = (self.encoder(x), self.encoder(x))
    mu = self.fc11(out1.view(out1.size(0), (- 1)))
    logvar = self.fc12(out2.view(out2.size(0), (- 1)))
    pre = self.mlp(torch.cat((t, mu), dim=1))
    z = reparameterize(mu, logvar)
    out3 = self.fc2(z).view(z.size(0), 128, 20, 5)
    return (self.decoder(out3), mu, logvar, pre)
def forward(self, x, t):
    (out1, out2) = (self.encoder(x), self.encoder(x))
    mu = self.fc11(out1.view(out1.size(0), (- 1)))
    logvar = self.fc12(out2.view(out2.size(0), (- 1)))
    pre = self.mlp(torch.cat((t, mu), dim=1))
    z = reparameterize(mu, logvar)
    out3 = self.fc2(z).view(z.size(0), 128, 20, 5)
    return (self.decoder(out3), mu, logvar, pre)