code: def is_categorical_dtype_cudf(obj):
      return cudf.api.types.is_categorical_dtype(obj)
  
imports: import warnings
  from collections.abc import Iterator
  import cupy
  import numpy
  import pandas
  import pyarrow
  from pandas.api.types import is_scalar
  from pandas.core.tools.datetimes import is_datetime64tz_dtype
  import dask.dataframe
  from dask import config
  from dask.array.dispatch import percentile_lookup
  from dask.dataframe.backends import DataFrameBackendEntrypoint, PandasBackendEntrypoint
  from dask.dataframe.core import get_parallel_type, meta_nonempty
  from dask.dataframe.dispatch import categorical_dtype_dispatch, concat_dispatch, from_pyarrow_table_dispatch, group_split_dispatch, grouper_dispatch, hash_object_dispatch, is_categorical_dtype_dispatch, make_meta_dispatch, pyarrow_schema_dispatch, to_pyarrow_table_dispatch, tolist_dispatch, union_categoricals_dispatch
  from dask.dataframe.utils import UNKNOWN_CATEGORIES, _nonempty_scalar, _scalar_from_dtype, make_meta_obj
  from dask.sizeof import sizeof
  from dask.utils import Dispatch, is_arraylike
  import cudf
  from cudf.api.types import is_string_dtype
  from cudf.utils.nvtx_annotation import _dask_cudf_nvtx_annotate
  from .core import DataFrame, Index, Series
label_desc: Use image node_id 13 for calling a global function with example usage: is_categorical_dtype_cudf(obj) and returns: cudf