class_docstr: Test on the problem (with the simplying assumption on general position)
  from Table 1 in:
  https://www.sciencedirect.com/science/article/pii/S0305054816301538
class_docstr_tok: ["Test","on","the","problem","(","with","the","simplying","assumption","on","general","position",")","from","Table","1","in",":","https",":","\/\/www.sciencedirect.com\/science\/article\/pii\/S0305054816301538"]
code: def test_get_partition_bounds(self):
      expected_bounds_raw = torch.tensor(
          [
              [
                  [3.0, 5.0, 7.0],
                  [6.0, 2.0, 7.0],
                  [4.0, 7.0, 3.0],
                  [6.0, 2.0, 4.0],
              ],
              [
                  [10.0, 10.0, 10.0],
                  [10.0, 5.0, 10.0],
                  [10.0, 10.0, 7.0],
                  [10.0, 7.0, 7.0],
              ],
          ],
          device=self.device,
      )
      for dtype in (torch.float, torch.double):
          final_U = self.expected_U_after_update.to(dtype=dtype)
          final_Z = self.expected_Z_after_update.to(dtype=dtype)
          bounds = get_partition_bounds(
              Z=final_Z, U=final_U, ref_point=-self.ref_point
          )
          expected_bounds = expected_bounds_raw.to(dtype=dtype)
          self.assertTrue(torch.equal(bounds, expected_bounds))
  
file_path: botorch/test/utils/multi_objective/box_decompositions/test_utils.py
imports: from __future__ import annotations
  import torch
  from botorch.exceptions.errors import BotorchTensorDimensionError, UnsupportedError
  from botorch.utils.multi_objective.box_decompositions.utils import _expand_ref_point, _pad_batch_pareto_frontier, compute_dominated_hypercell_bounds_2d, compute_local_upper_bounds, compute_non_dominated_hypercell_bounds_2d, get_partition_bounds, update_local_upper_bounds_incremental
  from botorch.utils.testing import BotorchTestCase
label_desc: Use image node_id 3 for calling the TestFastPartitioningUtils obj's underlying member method code with example usage: obj.test_get_partition_bounds() without return types