code: def test_groupby_multiindex_reset_index(npartitions):
      df = cudf.DataFrame(
          {
              "a": [1, 1, 2, 3, 4],
              "b": [5, 2, 1, 2, 5],
              "c": [1, 2, 2, 3, 5],
          }
      )
      ddf = dask_cudf.from_cudf(df, npartitions=npartitions)
      pddf = dd.from_pandas(df.to_pandas(), npartitions=npartitions)
      gr = ddf.groupby(["a", "c"]).agg({"b": ["count"]}).reset_index()
      pr = pddf.groupby(["a", "c"]).agg({"b": ["count"]}).reset_index()
  
      # CuDF uses "int32" for count. Pandas uses "int64"
      gr_out = (
          gr.compute().sort_values(by=["a", "c"]).reset_index(drop=True)
      )
      gr_out[("b", "count")] = gr_out[("b", "count")].astype("int64")
  
      dd.assert_eq(
          gr_out,
          pr.compute()
          .sort_values(by=["a", "c"])
          .reset_index(drop=True),
      )
  
imports: import numpy
  import pandas
  import pytest
  import dask
  from dask import dataframe
  from dask.utils_test import hlg_layer
  import cudf
  import dask_cudf
  from dask_cudf.groupby import OPTIMIZED_AGGS, _aggs_optimized
label_desc: Use image node_id 14 for calling a global function with example usage: test_groupby_multiindex_reset_index(npartitions) without return types