code: def test_incremental_mean_and_var(
      failure_logger, random_seed, random_dataset
  ):
      X_np, X = random_dataset
      cp.random.seed(random_seed)
      last_mean = cp.random.rand(10)
      last_variance = cp.random.rand(10)
      last_sample_count = cp.random.rand(10)
  
      (
          cu_mean,
          cu_variance,
          cu_sample_count,
      ) = cu_incremental_mean_and_var(
          X, last_mean, last_variance, last_sample_count
      )
      (
          sk_mean,
          sk_variance,
          sk_sample_count,
      ) = sk_incremental_mean_and_var(
          X_np,
          last_mean.get(),
          last_variance.get(),
          last_sample_count.get(),
      )
      assert_allclose(cu_mean, sk_mean)
      assert_allclose(cu_variance, sk_variance)
      assert_allclose(cu_sample_count, sk_sample_count)
  
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 5 for calling a global function with example usage: test_incremental_mean_and_var(failure_logger, random_seed, random_dataset) without return types