code: def test_mg_uniform_neighbor_sample_unweighted(dask_client):
      df = cudf.DataFrame(
          {
              "src": cudf.Series(
                  [0, 1, 2, 2, 0, 1, 4, 4], dtype="int32"
              ),
              "dst": cudf.Series(
                  [3, 2, 1, 4, 1, 3, 1, 2], dtype="int32"
              ),
          }
      )
  
      df = dask_cudf.from_cudf(df, npartitions=2)
  
      G = cugraph.Graph()
      G.from_dask_cudf_edgelist(df, source="src", destination="dst")
  
      start_list = cudf.Series([0], dtype="int32")
      fanout_vals = [-1]
      with_replacement = True
  
      sampling_results = uniform_neighbor_sample(
          G, start_list, fanout_vals, with_replacement=with_replacement
      )
  
      expected_src = [0, 0]
      actual_src = sampling_results.sources
      actual_src = actual_src.compute().to_arrow().to_pylist()
      assert sorted(actual_src) == sorted(expected_src)
  
      expected_dst = [3, 1]
      actual_dst = sampling_results.destinations
      actual_dst = actual_dst.compute().to_arrow().to_pylist()
      assert sorted(actual_dst) == sorted(expected_dst)
  
imports: import gc
  import random
  import os
  import pytest
  import pandas
  import cupy
  import cudf
  import cugraph
  import dask_cudf
  import cugraph.dask
  from cugraph.testing import UNDIRECTED_DATASETS
  from cugraph.dask import uniform_neighbor_sample
  from cugraph.dask.common.mg_utils import is_single_gpu
  from cugraph.datasets import email_Eu_core, small_tree
  from pylibcugraph.testing.utils import gen_fixture_params_product
label_desc: Use image node_id 5 for calling a global function with example usage: test_mg_uniform_neighbor_sample_unweighted(dask_client) without return types