code: def decons_obs_group_ids(
      comp_ids: npt.NDArray[np.intp],
      obs_ids: npt.NDArray[np.intp],
      shape: Shape,
      labels: Sequence[npt.NDArray[np.signedinteger]],
      xnull: bool,
  ) -> list[npt.NDArray[np.intp]]:
      """
      Reconstruct labels from observed group ids.
  
      Parameters
      ----------
      comp_ids : np.ndarray[np.intp]
      obs_ids: np.ndarray[np.intp]
      shape : tuple[int]
      labels : Sequence[np.ndarray[np.signedinteger]]
      xnull : bool
          If nulls are excluded; i.e. -1 labels are passed through.
      """
      if not xnull:
          lift = np.fromiter(
              ((a == -1).any() for a in labels), dtype=np.intp
          )
          arr_shape = np.asarray(shape, dtype=np.intp) + lift
          shape = tuple(arr_shape)
  
      if not is_int64_overflow_possible(shape):
          # obs ids are deconstructable! take the fast route!
          out = _decons_group_index(obs_ids, shape)
          return (
              out
              if xnull or not lift.any()
              else [x - y for x, y in zip(out, lift)]
          )
  
      indexer = unique_label_indices(comp_ids)
      return [
          lab[indexer].astype(np.intp, subok=False, copy=True)
          for lab in labels
      ]
  
imports: from __future__ import annotations
  from collections import defaultdict
  from typing import TYPE_CHECKING, Callable, DefaultDict, cast
  import numpy
  from pandas._libs import algos, hashtable, lib
  from pandas._libs.hashtable import unique_label_indices
  from pandas.core.dtypes.common import ensure_int64, ensure_platform_int
  from pandas.core.dtypes.generic import ABCMultiIndex, ABCRangeIndex
  from pandas.core.dtypes.missing import isna
  from pandas.core.construction import extract_array
label_desc: Use image node_id 6 for calling a global function with example usage: decons_obs_group_ids(comp_ids, obs_ids, shape, labels, xnull) and returns: unknown, unknown