code: def search_sparse_flat_tree(
      point_inds,
      point_data,
      hyperplanes,
      offsets,
      children,
      indices,
      rng_state,
  ):
      node = 0
      while children[node, 0] > 0:
          side = sparse_select_side(
              hyperplanes[node],
              offsets[node],
              point_inds,
              point_data,
              rng_state,
          )
          if side == 0:
              node = children[node, 0]
          else:
              node = children[node, 1]
  
      return indices[-children[node, 0] : -children[node, 1]]
  
imports: from warnings import warn
  import locale
  import numpy
  import numba
  import scipy.sparse
  from pynndescent.sparse import sparse_mul, sparse_diff, sparse_sum, arr_intersect, sparse_dot_product
  from pynndescent.utils import tau_rand_int, norm
  import joblib
  from collections import namedtuple
label_desc: Use image node_id 14 for calling a global function with example usage: search_sparse_flat_tree(point_inds, point_data, hyperplanes, offsets, children, indices, rng_state) and returns: indices