code: def _tweedie_deviance_score_compute(
      sum_deviance_score: Tensor, num_observations: Tensor
  ) -> Tensor:
      """Compute Deviance Score.
  
      Args:
          sum_deviance_score: Sum of deviance scores accumulated until now.
          num_observations: Number of observations encountered until now.
  
      Example:
          >>> targets = torch.tensor([1.0, 2.0, 3.0, 4.0])
          >>> preds = torch.tensor([4.0, 3.0, 2.0, 1.0])
          >>> sum_deviance_score, num_observations = _tweedie_deviance_score_update(preds, targets, power=2)
          >>> _tweedie_deviance_score_compute(sum_deviance_score, num_observations)
          tensor(1.2083)
  
      """
      return sum_deviance_score / num_observations
  
imports: from typing import Tuple
  import torch
  from torch import Tensor
  from torchmetrics.utilities.checks import _check_same_shape
  from torchmetrics.utilities.compute import _safe_xlogy
label_desc: Use image node_id 2 for calling a global function with example usage: _tweedie_deviance_score_compute(sum_deviance_score, num_observations) and returns: unknown