code: def input_combo(request):
      """
      Simply return the current combination of params as a dictionary for use in
      tests or other parameterized fixtures.
      """
      parameters = dict(
          zip(
              (
                  "graph_file",
                  "directed",
                  "with_replacement",
                  "indices_type",
              ),
              request.param,
          )
      )
  
      indices_type = parameters["indices_type"]
  
      input_data_path = parameters["graph_file"].get_path()
      directed = parameters["directed"]
  
      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", indices_type],
      )
  
      dg = cugraph.Graph(directed=directed)
      dg.from_dask_cudf_edgelist(
          ddf,
          source="src",
          destination="dst",
          edge_attr="value",
          store_transposed=False,
      )
  
      parameters["MGGraph"] = dg
  
      # sample k vertices from the cuGraph graph
      k = random.randint(1, 3)
      srcs = dg.input_df["src"]
      dsts = dg.input_df["dst"]
  
      vertices = (
          dask_cudf.concat([srcs, dsts]).drop_duplicates().compute()
      )
      start_list = vertices.sample(k).astype("int32")
  
      # Generate a random fanout_vals list of length random(1, k)
      fanout_vals = [
          random.randint(1, k) for _ in range(random.randint(1, k))
      ]
  
      # These prints are for debugging purposes since the vertices and the
      # fanout_vals are randomly sampled/chosen
      print("\nstart_list: \n", start_list)
      print("fanout_vals: ", fanout_vals)
  
      parameters["start_list"] = start_list
      parameters["fanout_vals"] = fanout_vals
  
      return parameters
  
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 2 for calling a global function with example usage: input_combo(request) and returns: parameters