code: def test_multi_column_ego_graph(graph_file, seed, radius):
      gc.collect()
  
      dataset_path = graph_file.get_path()
      df = utils.read_csv_file(dataset_path, read_weights_in_sp=True)
      df.rename(columns={"0": "src_0", "1": "dst_0"}, inplace=True)
      df["src_1"] = df["src_0"] + 1000
      df["dst_1"] = df["dst_0"] + 1000
  
      G1 = cugraph.Graph()
      G1.from_cudf_edgelist(
          df,
          source=["src_0", "src_1"],
          destination=["dst_0", "dst_1"],
          edge_attr="2",
      )
  
      seed_df = cudf.DataFrame()
      seed_df["v_0"] = [seed]
      seed_df["v_1"] = [seed + 1000]
  
      ego_cugraph_res = cugraph.ego_graph(G1, seed_df, radius=radius)
  
      G2 = cugraph.Graph()
      G2.from_cudf_edgelist(
          df, source="src_0", destination="dst_0", edge_attr="2"
      )
      ego_cugraph_exp = cugraph.ego_graph(G2, seed, radius=radius)
  
      # FIXME: Replace with multi-column view_edge_list()
      edgelist_df = ego_cugraph_res.edgelist.edgelist_df
      edgelist_df_res = ego_cugraph_res.unrenumber(edgelist_df, "src")
      edgelist_df_res = ego_cugraph_res.unrenumber(
          edgelist_df_res, "dst"
      )
      for i in range(len(edgelist_df_res)):
          assert ego_cugraph_exp.has_edge(
              edgelist_df_res["0_src"].iloc[i],
              edgelist_df_res["0_dst"].iloc[i],
          )
  
file_path: cugraph/python/cugraph/cugraph/tests/sampling/test_egonet.py
imports: import gc
  import pytest
  import networkx
  import cudf
  import cugraph
  from cugraph.testing import utils, DEFAULT_DATASETS
label_desc: Use image node_id 3 for calling a global function with example usage: test_multi_column_ego_graph(graph_file, seed, radius) without return types