code: def test_to_backend_kwargs():
      data = {"x": [0, 2, np.nan, 3, 4, 5]}
      with dask.config.set({"dataframe.backend": "pandas"}):
          dser = dd.from_dict(data, npartitions=2)["x"]
          assert isinstance(dser._meta, pd.Series)
  
          # Using `nan_as_null=False` will result in a cudf-backed
          # Series with a NaN element (ranther than <NA>)
          gser_nan = dser.to_backend("cudf", nan_as_null=False)
          assert isinstance(gser_nan, dgd.Series)
          assert np.isnan(gser_nan.compute()).sum() == 1
  
          # Using `nan_as_null=True` will result in a cudf-backed
          # Series with a <NA> element (ranther than NaN)
          gser_null = dser.to_backend("cudf", nan_as_null=True)
          assert isinstance(gser_null, dgd.Series)
          assert np.isnan(gser_null.compute()).sum() == 0
  
          # Check `nullable` argument for `cudf.Series.to_pandas`
          dser_null = gser_null.to_backend("pandas", nullable=False)
          assert dser_null.compute().dtype == "float"
          dser_null = gser_null.to_backend("pandas", nullable=True)
          assert isinstance(dser_null.compute().dtype, pd.Float64Dtype)
  
          # Check unsupported arguments
          with pytest.raises(ValueError, match="pandas-to-cudf"):
              dser.to_backend("cudf", bad_arg=True)
  
          with pytest.raises(ValueError, match="cudf-to-cudf"):
              gser_null.to_backend("cudf", bad_arg=True)
  
          with pytest.raises(ValueError, match="cudf-to-pandas"):
              gser_null.to_backend("pandas", bad_arg=True)
  
imports: import random
  import cupy
  import numpy
  import pandas
  import pytest
  from packaging import version
  import dask
  from dask import dataframe
  from dask.dataframe.core import make_meta, meta_nonempty
  from dask.utils import M
  import cudf
  import dask_cudf
label_desc: Use image node_id 3 for calling a global function with example usage: test_to_backend_kwargs() without return types