code: def test_imputer(
      failure_logger,
      random_seed,
      int_dataset,  # noqa: F811
      strategy,
      missing_values,
      add_indicator,
  ):
      zero_filled, one_filled, nan_filled = int_dataset
      if missing_values == 0:
          X_np, X = zero_filled
      elif missing_values == 1:
          X_np, X = one_filled
      else:
          X_np, X = nan_filled
      np.random.seed(random_seed)
      fill_value = np.random.randint(10, size=1)[0]
  
      imputer = cuSimpleImputer(
          copy=True,
          missing_values=missing_values,
          strategy=strategy,
          fill_value=fill_value,
          add_indicator=add_indicator,
      )
      t_X = imputer.fit_transform(X)
      assert type(t_X) == type(X)
  
      imputer = skSimpleImputer(
          copy=True,
          missing_values=missing_values,
          strategy=strategy,
          fill_value=fill_value,
          add_indicator=add_indicator,
      )
      sk_t_X = imputer.fit_transform(X_np)
  
      assert_allclose(t_X, sk_t_X)
  
imports: from cuml.internals.safe_imports import gpu_only_import
  import pytest
  import sklearn
  from cuml.preprocessing import Binarizer, FunctionTransformer, KBinsDiscretizer, KernelCenterer, MaxAbsScaler, MinMaxScaler, MissingIndicator, Normalizer, PolynomialFeatures, PowerTransformer, QuantileTransformer, RobustScaler, SimpleImputer, StandardScaler
  from cuml.preprocessing import add_dummy_feature, binarize, maxabs_scale, minmax_scale, normalize, power_transform, quantile_transform, robust_scale, scale
  from sklearn.preprocessing import Binarizer, FunctionTransformer, KBinsDiscretizer, KernelCenterer, MaxAbsScaler, MinMaxScaler, Normalizer, PolynomialFeatures, PowerTransformer, QuantileTransformer, RobustScaler, StandardScaler
  from sklearn.preprocessing import add_dummy_feature, binarize, maxabs_scale, minmax_scale, normalize, power_transform, quantile_transform, robust_scale, scale
  from sklearn.impute import MissingIndicator, SimpleImputer
  from cuml.testing.test_preproc_utils import clf_dataset, int_dataset, blobs_dataset, nan_filled_positive, sparse_nan_filled_positive, sparse_clf_dataset, sparse_blobs_dataset, sparse_int_dataset, sparse_imputer_dataset, sparse_dataset_with_coo
  from cuml.testing.test_preproc_utils import assert_allclose
  from cuml.metrics import pairwise_kernels
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 14 for calling a global function with example usage: test_imputer(failure_logger, random_seed, int_dataset, strategy, missing_values, add_indicator) without return types