code: def _cudf_to_table(obj, preserve_index=None, **kwargs):
      if kwargs:
          warnings.warn(
              "Ignoring the following arguments to "
              f"`to_pyarrow_table_dispatch`: {list(kwargs)}"
          )
  
      # TODO: Remove this logic when cudf#14159 is resolved
      # (see: https://github.com/rapidsai/cudf/issues/14159)
      if preserve_index and isinstance(obj.index, cudf.RangeIndex):
          obj = obj.copy()
          obj.index.name = (
              obj.index.name
              if obj.index.name is not None
              else "__index_level_0__"
          )
          obj.index = obj.index._as_int_index()
  
      return obj.to_arrow(preserve_index=preserve_index)
  
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 17 for calling a global function with example usage: _cudf_to_table(obj, preserve_index) and returns: obj