def _get_loss_features(self):
    with torch.no_grad():
        loss_var = torch.log(torch.var(self.loss_batch))
        self.lossVarDiscountedAverage = ((self.discount_factor * self.lossVarDiscountedAverage) + ((1 - self.discount_factor) * loss_var))
        self.lossVarUncertainty = ((self.discount_factor * self.lossVarUncertainty) + ((1 - self.discount_factor) * ((loss_var - self.lossVarDiscountedAverage) ** 2)))
    return (self.lossVarDiscountedAverage, self.lossVarUncertainty)
def _get_loss_features(self):
    with torch.no_grad():
        loss_var = torch.log(torch.var(self.loss_batch))
        self.lossVarDiscountedAverage = ((self.discount_factor * self.lossVarDiscountedAverage) + ((1 - self.discount_factor) * loss_var))
        self.lossVarUncertainty = ((self.discount_factor * self.lossVarUncertainty) + ((1 - self.discount_factor) * ((loss_var - self.lossVarDiscountedAverage) ** 2)))
    return (self.lossVarDiscountedAverage, self.lossVarUncertainty)