def get_output_for(self, input, **kwargs):
        x = self.x if self.x is not None else input.pop(0)
        mu = self.mu if self.mu is not None else input.pop(0)
        logvar = self.var if self.var is not None else input.pop(0)

        c = - 0.5 * math.log(2 * math.pi)
        density = c - logvar / 2 - (x - mu) ** 2 / (2 * T.exp(logvar))
        return T.sum(density, axis=-1, keepdims=True)
dataset/ETHPy150Open ml-lab/auxiliary-deep-generative-models/lasagne_extensions/layers/variationallayer.py/GaussianLogDensityLayer.get_output_for/original