code: def _register_cudf():
      import dask_cudf
  
imports: from __future__ import annotations
  import warnings
  from collections.abc import Iterable
  import numpy
  import pandas
  from pandas.api.types import is_scalar, union_categoricals
  from dask.array.core import Array
  from dask.array.dispatch import percentile_lookup
  from dask.array.percentile import _percentile
  from dask.backends import CreationDispatch, DaskBackendEntrypoint
  from dask.dataframe._compat import is_any_real_numeric_dtype
  from dask.dataframe.core import DataFrame, Index, Scalar, Series, _Frame
  from dask.dataframe.dispatch import categorical_dtype_dispatch, concat, concat_dispatch, from_pyarrow_table_dispatch, get_parallel_type, group_split_dispatch, grouper_dispatch, hash_object_dispatch, is_categorical_dtype_dispatch, make_meta_dispatch, make_meta_obj, meta_lib_from_array, meta_nonempty, partd_encode_dispatch, pyarrow_schema_dispatch, to_pandas_dispatch, to_pyarrow_table_dispatch, tolist_dispatch, union_categoricals_dispatch
  from dask.dataframe.extensions import make_array_nonempty, make_scalar
  from dask.dataframe.utils import _empty_series, _nonempty_scalar, _scalar_from_dtype, is_float_na_dtype, is_integer_na_dtype
  from dask.sizeof import SimpleSizeof, sizeof
  from dask.utils import is_arraylike, is_series_like, typename
label_desc: Use image node_id 32 for calling a global function with example usage: _register_cudf() without return types