code: def test_groupby_agg_empty_partition(tmpdir, split_out):
      # Write random and empty cudf DataFrames
      # to two distinct files.
      df = cudf.datasets.randomdata()
      df.to_parquet(str(tmpdir.join("f0.parquet")))
      cudf.DataFrame(
          columns=["id", "x", "y"],
          dtype={"id": "int64", "x": "float64", "y": "float64"},
      ).to_parquet(str(tmpdir.join("f1.parquet")))
  
      # Read back our two partitions as a single
      # dask_cudf DataFrame (one partition is now empty)
      ddf = dask_cudf.read_parquet(str(tmpdir))
      gb = ddf.groupby(["id"]).agg({"x": ["sum"]}, split_out=split_out)
  
      expect = df.groupby(["id"]).agg({"x": ["sum"]}).sort_index()
      dd.assert_eq(gb.compute().sort_index(), expect)
  
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 6 for calling a global function with example usage: test_groupby_agg_empty_partition(tmpdir, split_out) without return types