code: def test_make_meta_backends(index):
      dtypes = ["int8", "int32", "int64", "float64"]
      df = cudf.DataFrame(
          {dt: np.arange(start=0, stop=3, dtype=dt) for dt in dtypes}
      )
      df["strings"] = ["cat", "dog", "fish"]
      df["cats"] = df["strings"].astype("category")
      df["time_s"] = np.array(
          ["2018-10-07", "2018-10-08", "2018-10-09"],
          dtype="datetime64[s]",
      )
      df["time_ms"] = df["time_s"].astype("datetime64[ms]")
      df["time_ns"] = df["time_s"].astype("datetime64[ns]")
      df = df.set_index(index)
  
      # Check "empty" metadata types
      chk_meta = dask_make_meta(df)
      dd.assert_eq(chk_meta.dtypes, df.dtypes)
  
      # Check "non-empty" metadata types
      chk_meta_nonempty = meta_nonempty(df)
      dd.assert_eq(chk_meta.dtypes, chk_meta_nonempty.dtypes)
  
      # Check dask code path if not MultiIndex
      if not isinstance(df.index, cudf.MultiIndex):
          ddf = dgd.from_cudf(df, npartitions=1)
  
          # Check "empty" metadata types
          dd.assert_eq(ddf._meta.dtypes, df.dtypes)
  
          # Check "non-empty" metadata types
          dd.assert_eq(ddf._meta.dtypes, ddf._meta_nonempty.dtypes)
  
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 39 for calling a global function with example usage: test_make_meta_backends(index) without return types