code: def int_dataset(request, random_seed):
      randint = create_rand_integers(random_seed)
      cp.random.seed(random_seed)
      random_loc = cp.random.choice(
          randint.size, int(randint.size * 0.3), replace=False
      )
  
      zero_filled = randint.copy().ravel()
      zero_filled[random_loc] = 0
      zero_filled = zero_filled.reshape(randint.shape)
      zero_filled = convert(zero_filled, request.param)
  
      one_filled = randint.copy().ravel()
      one_filled[random_loc] = 1
      one_filled = one_filled.reshape(randint.shape)
      one_filled = convert(one_filled, request.param)
  
      nan_filled = randint.copy().ravel()
      nan_filled[random_loc] = cp.nan
      nan_filled = nan_filled.reshape(randint.shape)
      nan_filled = convert(nan_filled, request.param)
  
      return zero_filled, one_filled, nan_filled
  
imports: from cuml.common import input_to_cuml_array
  from scipy.sparse import coo_matrix
  from scipy.sparse import csc_matrix
  from cupyx.scipy.sparse import coo_matrix
  from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.internals.safe_imports import gpu_only_import
  from cuml.internals.safe_imports import cpu_only_import
  import pytest
  from cuml.datasets import make_classification, make_blobs
  from cuml.internals.safe_imports import cpu_only_import_from
label_desc: Use image node_id 10 for calling a global function with example usage: int_dataset(request, random_seed) and returns: zero_filled,  one_filled,  nan_filled