code: def test_fit(self):
      a = dpp.RobustScaler()
      b = spp.RobustScaler()
  
      # bigger data to make percentile more reliable
      # and not centered around 0 to make rtol work
      X, y = make_classification(
          n_samples=1000, chunks=200, random_state=0
      )
      X = X + 3
  
      a.fit(X)
      b.fit(X.compute())
      assert_estimator_equal(a, b, rtol=0.2)
  
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 1 for calling the TestRobustScaler obj's underlying member method code with example usage: obj.test_fit() without return types