code: def test_n_init_cluster_consistency(random_state):
      nclusters = 8
      X, y = get_data_consistency_test()
  
      cuml_kmeans = cuml.KMeans(
          init="k-means++",
          n_clusters=nclusters,
          n_init=10,
          random_state=random_state,
          output_type="numpy",
      )
  
      cuml_kmeans.fit(X)
      initial_clusters = cuml_kmeans.cluster_centers_
  
      cuml_kmeans = cuml.KMeans(
          init="k-means++",
          n_clusters=nclusters,
          n_init=10,
          random_state=random_state,
          output_type="numpy",
      )
  
      cuml_kmeans.fit(X)
  
      assert array_equal(initial_clusters, cuml_kmeans.cluster_centers_)
  
imports: from cuml.internals.safe_imports import gpu_only_import
  from sklearn.preprocessing import StandardScaler
  from sklearn.metrics import adjusted_rand_score
  from sklearn import cluster
  from cuml.testing.utils import get_pattern, unit_param, quality_param, stress_param, array_equal
  from cuml.datasets import make_blobs
  import pytest
  import random
  import cuml
  import cuml.internals.logger
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 3 for calling a global function with example usage: test_n_init_cluster_consistency(random_state) without return types