code: def _nonempty_index(idx):
      if isinstance(idx, cudf.core.index.RangeIndex):
          return cudf.core.index.RangeIndex(2, name=idx.name)
      elif isinstance(idx, cudf.core.index.DatetimeIndex):
          start = "1970-01-01"
          data = np.array([start, "1970-01-02"], dtype=idx.dtype)
          values = cudf.core.column.as_column(data)
          return cudf.core.index.DatetimeIndex(values, name=idx.name)
      elif isinstance(idx, cudf.StringIndex):
          return cudf.StringIndex(["cat", "dog"], name=idx.name)
      elif isinstance(idx, cudf.core.index.CategoricalIndex):
          key = tuple(idx._data.keys())
          assert len(key) == 1
          categories = idx._data[key[0]].categories
          codes = [0, 0]
          ordered = idx._data[key[0]].ordered
          values = cudf.core.column.build_categorical_column(
              categories=categories, codes=codes, ordered=ordered
          )
          return cudf.core.index.CategoricalIndex(values, name=idx.name)
      elif isinstance(idx, cudf.core.index.GenericIndex):
          return cudf.core.index.GenericIndex(
              np.arange(2, dtype=idx.dtype), name=idx.name
          )
      elif isinstance(idx, cudf.core.multiindex.MultiIndex):
          levels = [meta_nonempty(lev) for lev in idx.levels]
          codes = [[0, 0] for i in idx.levels]
          return cudf.core.multiindex.MultiIndex(
              levels=levels, codes=codes, names=idx.names
          )
  
      raise TypeError(
          f"Don't know how to handle index of type {type(idx)}"
      )
  
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 1 for calling a global function with example usage: _nonempty_index(idx) and returns: cudf, cudf, cudf, cudf, cudf, cudf