code: def _supervised_evaluation_error_checking(targets, predictions):
      
      _raise_error_if_not_sarray(targets, "targets")
      _raise_error_if_not_sarray(predictions, "predictions")
      if (len(targets) != len(predictions)):
          raise _ToolkitError(
           "Input SArrays 'targets' and 'predictions' must be of the same length.")
docs: Perform basic error checking for the evaluation metrics. Check
      types and sizes of the inputs.