code: def test_maxabs_scaler(failure_logger, clf_dataset):  # noqa: F811
      X_np, X = clf_dataset
  
      scaler = cuMaxAbsScaler(copy=True)
      t_X = scaler.fit_transform(X)
      r_X = scaler.inverse_transform(t_X)
      assert type(t_X) == type(X)
      assert type(r_X) == type(t_X)
  
      scaler = skMaxAbsScaler(copy=True)
      sk_t_X = scaler.fit_transform(X_np)
      sk_r_X = scaler.inverse_transform(sk_t_X)
  
      assert_allclose(t_X, sk_t_X)
      assert_allclose(r_X, sk_r_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 8 for calling a global function with example usage: test_maxabs_scaler(failure_logger, clf_dataset) without return types