code: def _log_cosh_error_compute(
      sum_log_cosh_error: Tensor, num_obs: Tensor
  ) -> Tensor:
      """Compute Mean Squared Error.
  
      Args:
          sum_log_cosh_error: Sum of LogCosh errors over all observations
          num_obs: Number of predictions or observations
  
      """
      return (sum_log_cosh_error / num_obs).squeeze()
  
file_path: torchmetrics/src/torchmetrics/functional/regression/log_cosh.py
imports: from typing import Tuple
  import torch
  from torch import Tensor
  from torchmetrics.functional.regression.utils import _check_data_shape_to_num_outputs
  from torchmetrics.utilities.checks import _check_same_shape
label_desc: Use image node_id 3 for calling a global function with example usage: _log_cosh_error_compute(sum_log_cosh_error, num_obs) and returns: unknown