code: def _compute_hssp_truth_and_approx(
      test_case: np.ndarray, subset_size: int
  ) -> Tuple[float, float]:
      r = 1.1 * np.max(test_case, axis=0)
      truth = 0.0
      for subset in itertools.permutations(test_case, subset_size):
          truth = max(
              truth,
              optuna._hypervolume.WFG().compute(np.asarray(subset), r),
          )
      indices = optuna._hypervolume.hssp._solve_hssp(
          test_case, np.arange(len(test_case)), subset_size, r
      )
      approx = optuna._hypervolume.WFG().compute(test_case[indices], r)
      return truth, approx
  
file_path: optuna/tests/hypervolume_tests/test_hssp.py
imports: import itertools
  from typing import Tuple
  import numpy
  import pytest
  import optuna
label_desc: Use image node_id 1 for calling a global function with example usage: _compute_hssp_truth_and_approx(test_case, subset_size) and returns: truth,  approx