def forward()

in models/encoders/mvconv1.py [0:0]

• 14 lines of code
• 5 McCabe index (conditional complexity)

    def forward(self, x, losslist=[]):
        x = self.pad(x)
        x = [self.down1[0 if self.tied else i](x[:, i*3:(i+1)*3, :, :]).view(-1, 256 * 3 * 4) for i in range(self.ninputs)]
        x = torch.cat(x, dim=1)
        x = self.down2(x)

        mu, logstd = self.mu(x) * 0.1, self.logstd(x) * 0.01
        if self.training:
            z = mu + torch.exp(logstd) * torch.randn(*logstd.size(), device=logstd.device)
        else:
            z = mu

        losses = {}
        if "kldiv" in losslist:
            losses["kldiv"] = torch.mean(-0.5 - logstd + 0.5 * mu ** 2 + 0.5 * torch.exp(2 * logstd), dim=-1)

        return {"encoding": z, "losses": losses}