Method kl

lvdm/distributions.py:42–54

(self, other=None)

        return x

    def kl(self, other=None):
        if self.deterministic:
            return torch.Tensor([0.])
        else:
            if other is None:
                return 0.5 * torch.sum(torch.pow(self.mean, 2)
                                       + self.var - 1.0 - self.logvar,
                                       dim=[1, 2, 3])
            else:
                return 0.5 * torch.sum(
                    torch.pow(self.mean - other.mean, 2) / other.var
                    + self.var / other.var - 1.0 - self.logvar + other.logvar,
                    dim=[1, 2, 3])

    def nll(self, sample, dims=[1,2,3]):
        if self.deterministic: