code: def test_split_mixed():
      y_series = dd.from_dask_array(dy)
  
      with pytest.raises(TypeError, match="convert_mixed_types"):
          dask_ml.model_selection.train_test_split(dX, y_series)
  
      expected = dask_ml.model_selection.train_test_split(
          dX, dy, random_state=0
      )
      results = dask_ml.model_selection.train_test_split(
          dX, y_series, random_state=0, convert_mixed_types=True
      )
  
      assert len(expected) == len(results)
      for a, b in zip(expected, results):
          da.utils.assert_eq(a, b)
  
imports: import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import pytest
  from sklearn.datasets import fetch_20newsgroups, make_regression
  import dask_ml.model_selection
  from dask_ml._compat import DASK_2130
label_desc: Use image node_id 15 for calling a global function with example usage: test_split_mixed() without return types