def METHOD_NAME(self) -> float:
    if self._num_examples == 0:
        raise NotComputableError("InceptionScore must have at least one example before it can be computed.")
    mean_probs = self._prob_total / self._num_examples
    log_mean_probs = torch.log(mean_probs + self._eps)
    if log_mean_probs.dtype != self._prob_total.dtype:
        log_mean_probs = log_mean_probs.to(self._prob_total)
    excess_entropy = self._prob_total * log_mean_probs
    avg_kl_d = torch.sum(self._total_kl_d - excess_entropy) / self._num_examples
    return torch.exp(avg_kl_d).item()