class_docstr: Partition dominated space into axis-aligned hyperrectangles.
  
  This uses the Algorithm 1 from [Lacour17]_.
  
  Example:
      >>> bd = DominatedPartitioning(ref_point, Y)
docstr: Get the bounds of each hypercell in the decomposition.
code: def _get_partitioning(self) -> None:
      r"""Get the bounds of each hypercell in the decomposition."""
      minimization_cell_bounds = get_partition_bounds(
          Z=self._Z, U=self._U, ref_point=self._neg_ref_point.view(-1)
      )
      cell_bounds = -minimization_cell_bounds.flip(0)
      self.hypercell_bounds = cell_bounds
  
file_path: botorch/botorch/utils/multi_objective/box_decompositions/dominated.py
imports: from __future__ import annotations
  from botorch.utils.multi_objective.box_decompositions.box_decomposition import FastPartitioning
  from botorch.utils.multi_objective.box_decompositions.utils import compute_dominated_hypercell_bounds_2d, get_partition_bounds
  from torch import Tensor
label_desc: Use image node_id 2 for calling the DominatedPartitioning obj's underlying member method code with example usage: obj._get_partitioning() without return types