code: def test_transform(self):
      a = dpp.RobustScaler()
      b = spp.RobustScaler()
  
      a.fit(X)
      b.fit(X.compute())
  
      # overwriting dask-ml's fitted attributes to have them exactly equal
      # (the approximate equality is tested above)
      a.scale_ = b.scale_
      a.center_ = b.center_
  
      assert dask.is_dask_collection(a.transform(X))
      assert_eq_ar(a.transform(X), b.transform(X.compute()))
  
imports: from copy import copy
  import dask
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import pandas.testing
  import pytest
  import sklearn.preprocessing
  from dask import compute
  from dask.array.utils import assert_eq
  from dask.dataframe.utils import assert_eq
  from pandas.api.types import is_categorical_dtype, is_object_dtype
  from sklearn.exceptions import NotFittedError
  import dask_ml.preprocessing
  from dask_ml.datasets import make_classification
  from dask_ml.utils import assert_estimator_equal
label_desc: Use image node_id 2 for calling the TestRobustScaler obj's underlying member method code with example usage: obj.test_transform() without return types