code: def assert_cluster_counts(sk_agg, cuml_agg, digits=25):
      sk_unique, sk_counts = np.unique(
          sk_agg.labels_, return_counts=True
      )
      sk_counts = np.sort(sk_counts)
  
      cu_unique, cu_counts = cp.unique(
          cuml_agg.labels_, return_counts=True
      )
      cu_counts = cp.sort(cu_counts).get()
  
      np.testing.assert_almost_equal(
          sk_counts, cu_counts, decimal=-1 * digits
      )
  
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 1 for calling a global function with example usage: assert_cluster_counts(sk_agg, cuml_agg, digits) without return types