code: def get_compressed_ids(labels, sizes):
      """
  
      Group_index is offsets into cartesian product of all possible labels. This
      space can be huge, so this function compresses it, by computing offsets
      (comp_ids) into the list of unique labels (obs_group_ids).
  
      Parameters
      ----------
      labels : list of label arrays
      sizes : list of size of the levels
  
      Returns
      -------
      tuple of (comp_ids, obs_group_ids)
  
      """
      ids = get_group_index(labels, sizes, sort=True, xnull=False)
      return compress_group_index(ids, sort=True)
  
imports: import warnings
  import numpy
  from pandas._libs import algos, hashtable, lib
  from pandas._libs.hashtable import unique_label_indices
  from pandas.compat import PY3, long, string_types
  from pandas.core.dtypes.cast import infer_dtype_from_array
  from pandas.core.dtypes.common import ensure_int64, ensure_platform_int, is_categorical_dtype, is_list_like
  from pandas.core.dtypes.missing import isna
  import pandas.core.algorithms
label_desc: Use image node_id 2 for calling a global function with example usage: get_compressed_ids(labels, sizes) and returns: compress_group_index