code: def test_solve_hssp_infinite_loss() -> None:
      rng = np.random.RandomState(128)
  
      subset_size = 4
      test_case = rng.rand(9, 2)
      test_case[-1].fill(float("inf"))
      truth, approx = _compute_hssp_truth_and_approx(
          test_case, subset_size
      )
      assert np.isinf(truth)
      assert np.isinf(approx)
  
      test_case = rng.rand(9, 3)
      test_case[-1].fill(float("inf"))
      truth, approx = _compute_hssp_truth_and_approx(
          test_case, subset_size
      )
      assert truth == 0
      assert np.isnan(approx)
  
      for dim in range(2, 4):
          test_case = rng.rand(9, dim)
          test_case[-1].fill(-float("inf"))
          truth, approx = _compute_hssp_truth_and_approx(
              test_case, subset_size
          )
          assert np.isinf(truth)
          assert np.isinf(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 3 for calling a global function with example usage: test_solve_hssp_infinite_loss() without return types