code: def sparse_extremes(request, random_seed):
      X = cp.array(
          [
              [-0.9933658, 0.871748, 0.44418066],
              [0.87808335, cp.nan, 0.18183318],
              [cp.nan, 0.25030251, -0.7269053],
              [cp.nan, 0.17725405, cp.nan],
              [cp.nan, cp.nan, cp.nan],
              [0.0, 0.0, 0.44418066],
              [0.0, 0.0, 0.0],
              [0.0, 0.0, cp.nan],
              [0.0, cp.nan, cp.nan],
          ]
      )
      if request.param == "cupy-csr":
          X_sparse = cpx.scipy.sparse.csr_matrix(X)
      elif request.param == "cupy-csc":
          X_sparse = cpx.scipy.sparse.csc_matrix(X)
      return X_sparse.get(), X_sparse
  
imports: from cuml.testing.test_preproc_utils import assert_allclose
  from sklearn.utils.sparsefuncs import inplace_csr_column_scale, inplace_csr_row_scale, inplace_column_scale, mean_variance_axis, min_max_axis
  from cuml._thirdparty.sklearn.utils.sparsefuncs import inplace_csr_column_scale, inplace_csr_row_scale, inplace_column_scale, mean_variance_axis, min_max_axis
  from sklearn.utils.extmath import row_norms, _incremental_mean_and_var
  from cuml._thirdparty.sklearn.utils.extmath import row_norms, _incremental_mean_and_var
  from cuml._thirdparty.sklearn.utils.validation import check_X_y
  from cuml.internals.safe_imports import gpu_only_import
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 11 for calling a global function with example usage: sparse_extremes(request, random_seed) and returns: X_sparse,  X_sparse