code: def input_expected_output(input_combo):
      """
      This fixture returns the expected results from the pagerank algorithm.
      """
      import networkx
  
      M = utils.read_csv_for_nx(input_combo["graph_file"])
  
      Gnx = networkx.from_pandas_edgelist(
          M,
          source="0",
          target="1",
          edge_attr="weight",
          create_using=networkx.DiGraph(),
      )
      nnz_vtx = np.unique(M[["0", "1"]])
      personalization = get_personalization(
          input_combo["pers_percent"], nnz_vtx
      )
      input_combo["nstart"] = None
      nstart = None
      if input_combo["has_guess"] == 1:
          z = {k: 1.0 / Gnx.number_of_nodes() for k in Gnx.nodes()}
          input_combo["nstart"] = z
          nstart = z
  
      pr = networkx.pagerank(
          Gnx,
          max_iter=input_combo["max_iter"],
          tol=input_combo["tol"],
          personalization=personalization,
          nstart=nstart,
      )
      input_combo["personalization"] = personalization
      input_combo["nx_pr_rankings"] = pr
      return input_combo
  
file_path: cugraph/python/cugraph/cugraph/tests/nx/test_compat_pr.py
imports: import gc
  import importlib
  import pytest
  import numpy
  from cugraph.testing import utils
  from cugraph.datasets import karate
  from pylibcugraph.testing.utils 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