code: def test_fit_constant(data):
      a = sklearn.impute.SimpleImputer(
          strategy="constant", fill_value=-999.0
      )
      b = dask_ml.impute.SimpleImputer(
          strategy="constant", fill_value=-999.0
      )
  
      expected = a.fit_transform(X)
      result = b.fit_transform(data)
  
      assert_estimator_equal(a, b, exclude=["statistics_"])
      np.testing.assert_array_almost_equal(
          a.statistics_, np.asarray(b.statistics_)
      )
      assert isinstance(result, type(data))
      if isinstance(data, (pd.DataFrame, dd.DataFrame)):
          result = result.values
  
      da.utils.assert_eq(result, expected)
  
file_path: dask-ml/tests/test_impute.py
imports: import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import pandas.testing
  import pytest
  import sklearn.impute
  import dask_ml.datasets
  import dask_ml.impute
  from dask_ml._compat import DASK_2_26_0, PANDAS_1_2_0
  from dask_ml.utils import assert_estimator_equal
label_desc: Use image node_id 2 for calling a global function with example usage: test_fit_constant(data) without return types