code: def _weighted_mean_absolute_percentage_error_compute(
      sum_abs_error: Tensor,
      sum_scale: Tensor,
      epsilon: float = 1.17e-06,
  ) -> Tensor:
      """Compute Weighted Absolute Percentage Error.
  
      Args:
          sum_abs_error: scalar with sum of absolute errors
          sum_scale: scalar with sum of target values
          epsilon: small float to prevent division by zero
  
      """
      return sum_abs_error / torch.clamp(sum_scale, min=epsilon)
  
imports: from typing import Tuple
  import torch
  from torch import Tensor
  from torchmetrics.utilities.checks import _check_same_shape
label_desc: Use image node_id 2 for calling a global function with example usage: _weighted_mean_absolute_percentage_error_compute(sum_abs_error, sum_scale, epsilon) and returns: unknown