class_docstr: An abstract class for box decompositions.
  
  Note: Internally, we store the negative reference point (minimization).
  
  :meta private:
docstr: Partition the non-dominated space into disjoint hypercells.
  
  This method supports an arbitrary number of outcomes, but is
  less efficient than `partition_space_2d` for the 2-outcome case.
code: def _partition_space(self) -> None:
      r"""Partition the non-dominated space into disjoint hypercells.
  
      This method supports an arbitrary number of outcomes, but is
      less efficient than `partition_space_2d` for the 2-outcome case.
      """
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import Optional
  import torch
  from botorch.exceptions.errors import BotorchError
  from botorch.utils.multi_objective.box_decompositions.utils import _expand_ref_point, _pad_batch_pareto_frontier, update_local_upper_bounds_incremental
  from botorch.utils.multi_objective.pareto import is_non_dominated
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 9 for calling the BoxDecomposition obj's underlying member method code with example usage: obj._partition_space() without return types