code: def test_column_transformer_unk_chunksize():
      names = ["a", "b", "c"]
      x = dd.from_pandas(
          pd.DataFrame(np.arange(12).reshape(4, 3), columns=names), 2
      )
      features = sklearn.pipeline.Pipeline(
          [
              (
                  "features",
                  sklearn.pipeline.FeatureUnion(
                      [
                          (
                              "ratios",
                              dask_ml.compose.ColumnTransformer(
                                  [
                                      (
                                          "a_b",
                                          SumTransformer(one_d=False),
                                          ["a", "b"],
                                      ),
                                      (
                                          "b_c",
                                          SumTransformer(one_d=False),
                                          ["b", "c"],
                                      ),
                                  ]
                              ),
                          )
                      ]
                  ),
              )
          ]
      )
      out = features.fit_transform(x)
  
      exp = np.array([[1, 3], [7, 9], [13, 15], [19, 21]])
      np.testing.assert_array_equal(out, exp)
  
imports: import dask.dataframe
  import numpy
  import packaging.version
  import pandas
  import pytest
  import sklearn.compose
  import sklearn.pipeline
  import sklearn.preprocessing
  from sklearn.base import BaseEstimator, clone
  import dask_ml.compose
  import dask_ml.preprocessing
  from dask_ml._compat import SK_VERSION
label_desc: Use image node_id 2 for calling a global function with example usage: test_column_transformer_unk_chunksize() without return types