code: def correctness_sparse(a, b, atol=0.1, rtol=0.2, threshold=0.95):
      n_ref_zeros = (a == 0).sum()
      n_ref_non_zero_elms = a.size - n_ref_zeros
      n_correct = (cp.abs(a - b) <= (atol + rtol * cp.abs(b))).sum()
      correctness = (n_correct - n_ref_zeros) / n_ref_non_zero_elms
      return correctness >= threshold
  
imports: import platform
  import pytest
  import copy
  import joblib
  from sklearn.metrics import adjusted_rand_score
  from sklearn.manifold import trustworthiness
  from sklearn.datasets import make_blobs
  from sklearn.cluster import KMeans
  from sklearn.neighbors import NearestNeighbors
  from sklearn import datasets
  from cuml.internals import logger
  from cuml.metrics import pairwise_distances
  from cuml.testing.utils import array_equal, unit_param, quality_param, stress_param
  from cuml.manifold.umap import UMAP
  from cuml.internals.safe_imports import cpu_only_import
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 20 for calling a global function with example usage: correctness_sparse(a, b, atol, rtol, threshold) and returns: unknown