code: def input_expected_output(input_combo):
      """
      This fixture returns the inputs and expected results from the induced_subgraph algo.
      (based on cuGraph subgraph) which can be used for validation.
      """
  
      input_data_path = input_combo["graph_file"]
      directed = input_combo["directed"]
      num_seeds = input_combo["seeds"]
  
      # FIXME: This parameter is not tested
      # offsets= input_combo["offsets"]
      G = utils.generate_cugraph_graph_from_file(
          input_data_path, directed=directed, edgevals=True
      )
  
      # Sample k vertices from the cuGraph graph
      # FIXME: Leverage the method 'select_random_vertices' instead
      srcs = G.view_edge_list()["0"]
      dsts = G.view_edge_list()["1"]
      vertices = cudf.concat([srcs, dsts]).drop_duplicates()
      vertices = vertices.sample(num_seeds, replace=True).astype(
          "int32"
      )
  
      # print randomly sample n seeds from the graph
      print("\nvertices: \n", vertices)
  
      input_combo["vertices"] = vertices
  
      sg_induced_subgraph, _ = cugraph.induced_subgraph(
          G, vertices=vertices
      )
  
      # Save the results back to the input_combo dictionary to prevent redundant
      # cuGraph runs. Other tests using the input_combo fixture will look for
      # them, and if not present they will have to re-run the same cuGraph call.
  
      input_combo["sg_cugraph_results"] = sg_induced_subgraph
      chunksize = dcg.get_chunksize(input_data_path)
      ddf = dask_cudf.read_csv(
          input_data_path,
          chunksize=chunksize,
          delimiter=" ",
          names=["src", "dst", "value"],
          dtype=["int32", "int32", "float32"],
      )
  
      dg = cugraph.Graph(directed=directed)
      dg.from_dask_cudf_edgelist(
          ddf,
          source="src",
          destination="dst",
          edge_attr="value",
          renumber=True,
          store_transposed=True,
      )
  
      input_combo["MGGraph"] = dg
  
      return input_combo
  
file_path: cugraph/python/cugraph/cugraph/tests/community/test_induced_subgraph_mg.py
imports: import gc
  import pytest
  import cudf
  from cudf.testing.testing import assert_frame_equal
  import dask_cudf
  import cugraph
  import cugraph.dask
  from cugraph.testing import utils
  from cugraph.dask.common.mg_utils import is_single_gpu
  from pylibcugraph.testing import gen_fixture_params_product
label_desc: Use image node_id 3 for calling a global function with example usage: input_expected_output(input_combo) and returns: input_combo