code: def test_get_dummies_sparse_mix():
      df = pd.DataFrame(
          {
              "A": pd.Categorical(
                  ["a", "b", "a"], categories=["a", "b", "c"]
              ),
              "B": [0, 0, 1],
          }
      )
      ddf = dd.from_pandas(df, 2)
  
      exp = pd.get_dummies(df, sparse=True)
      res = dd.get_dummies(ddf, sparse=True)
      with ignore_numpy_bool8_deprecation():
          assert_eq(exp, res)
  
      dtype = res.compute().A_a.dtype
      assert dtype.fill_value == _get_dummies_dtype_default(0)
      assert dtype.subtype == _get_dummies_dtype_default
      assert isinstance(res.A_a.compute().dtype, pd.SparseDtype)
  
imports: from __future__ import annotations
  import contextlib
  import warnings
  import numpy
  import pandas
  import pytest
  from packaging.version import parse
  import dask.dataframe
  from dask.dataframe._compat import PANDAS_VERSION, tm
  from dask.dataframe.reshape import _get_dummies_dtype_default
  from dask.dataframe.utils import assert_eq, make_meta
label_desc: Use image node_id 8 for calling a global function with example usage: test_get_dummies_sparse_mix() without return types