code: def resultset_call(graph_file, source, load_results, edgevals=True):
      dataset_path = graph_file.get_path()
      dataset_name = graph_file.metadata["name"]
  
      if edgevals is False:
          # FIXME: no test coverage if edgevals is False, this assertion is never reached
          assert False
          golden_paths = get_resultset(
              resultset_name="traversal",
              algo="single_source_shortest_path_length",
              graph_dataset=dataset_name,
              graph_directed=str(True),
              source=str(source),
          )
      else:
          # FIXME: The golden results (nx) below doesn't return accurate results as it
          # seems to not support 'weights'. It matches cuGraph result only if the weight
          # column is 1s.
          golden_paths = get_resultset(
              resultset_name="traversal",
              algo="single_source_dijkstra_path_length",
              graph_dataset=dataset_name,
              graph_directed=str(True),
              source=str(source),
          )
      golden_paths = cudf.Series(
          golden_paths.distance.values, index=golden_paths.vertex
      ).to_dict()
  
      G = graph_file.get_graph(
          create_using=cugraph.Graph(directed=True),
          ignore_weights=not edgevals,
      )
  
      return (G, dataset_path, graph_file, source, golden_paths)
  
imports: import gc
  import pytest
  import numpy
  import pandas
  import cudf
  import cupyx
  import cugraph
  import cupy
  from cupyx.scipy.sparse import coo_matrix
  from cupyx.scipy.sparse import csr_matrix
  from cupyx.scipy.sparse import csc_matrix
  from scipy.sparse import coo_matrix
  from scipy.sparse import csr_matrix
  from scipy.sparse import csc_matrix
  from pylibcugraph.testing.utils import gen_fixture_params_product
  from cugraph.testing import utils, get_resultset, load_resultset, UNDIRECTED_DATASETS, SMALL_DATASETS
label_desc: Use image node_id 3 for calling a global function with example usage: resultset_call(graph_file, source, load_results, edgevals) and returns: G,  dataset_path,  graph_file,  source,  golden_paths