code: def assert_membership_vectors(cu_vecs, sk_vecs):
      """
      Assert the membership vectors by taking the adjusted rand score
      of the argsorted membership vectors.
      """
      if sk_vecs.shape == cu_vecs.shape:
          cu_labels_sorted = np.argsort(cu_vecs)[::-1]
          sk_labels_sorted = np.argsort(sk_vecs)[::-1]
  
          k = min(sk_vecs.shape[1], 10)
          for i in range(k):
              assert (
                  adjusted_rand_score(
                      cu_labels_sorted[:, i], sk_labels_sorted[:, i]
                  )
                  >= 0.90
              )
  
imports: from cuml.internals.safe_imports import gpu_only_import
  from sklearn.model_selection import train_test_split
  from sklearn import datasets
  from hdbscan.plots import CondensedTree
  import hdbscan
  from cuml.internals import logger
  import pytest
  from cuml.cluster.hdbscan import HDBSCAN, condense_hierarchy
  from cuml.cluster.hdbscan.prediction import all_points_membership_vectors, approximate_predict, membership_vector
  from sklearn.datasets import make_blobs
  from cuml.metrics import adjusted_rand_score
  from cuml.testing.utils import get_pattern, array_equal
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 5 for calling a global function with example usage: assert_membership_vectors(cu_vecs, sk_vecs) without return types