code: def get_data_consistency_test():
      cluster_std = 1.0
      nrows = 1000
      ncols = 50
      nclusters = 8
  
      X, y = make_blobs(
          nrows,
          ncols,
          nclusters,
          cluster_std=cluster_std,
          shuffle=False,
          random_state=0,
      )
      return X, y
  
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 1 for calling a global function with example usage: get_data_consistency_test() and returns: X,  y