code: def test_mean_variance_axis(
      failure_logger, sparse_random_dataset, axis
  ):
      _, _, X_sparse_np, X_sparse = sparse_random_dataset
      cu_mean, cu_variance = cu_mean_variance_axis(X_sparse, axis=axis)
      sk_mean, sk_variance = sk_mean_variance_axis(
          X_sparse_np, axis=axis
      )
      assert_allclose(cu_mean, sk_mean)
      assert_allclose(cu_variance, sk_variance)
  
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 9 for calling a global function with example usage: test_mean_variance_axis(failure_logger, sparse_random_dataset, axis) without return types