code: def test_cora_load(
      is_directed, largest_cc_only, subject_as_feature
  ) -> None:
      g, subjects = Cora().load(
          is_directed, largest_cc_only, subject_as_feature
      )
  
      if largest_cc_only:
          expected_nodes = 2485
          expected_edges = 5209
      else:
          expected_nodes = 2708
          expected_edges = 5429
  
      base_feature_size = 1433
      if subject_as_feature:
          feature_size = base_feature_size + 7
      else:
          feature_size = base_feature_size
  
      assert g.nodes().dtype == np.int64
      assert g.is_directed() == is_directed
  
      assert g.number_of_nodes() == expected_nodes
      assert g.number_of_edges() == expected_edges
      assert g.node_feature_sizes() == {"paper": feature_size}
  
      assert len(subjects) == g.number_of_nodes()
      assert set(subjects.index) == set(g.nodes())
      assert set(subjects) == {
          "Case_Based",
          "Genetic_Algorithms",
          "Neural_Networks",
          "Probabilistic_Methods",
          "Reinforcement_Learning",
          "Rule_Learning",
          "Theory",
      }
  
imports: import pytest
  import tempfile
  import os
  import sys
  import numpy
  from stellargraph.datasets import *
  from urllib.error import URLError
  from stellargraph.datasets.dataset_loader import DatasetLoader
  from urllib.request import urlretrieve
  from unittest.mock import patch
label_desc: Use image node_id 11 for calling a global function with example usage: test_cora_load(is_directed, largest_cc_only, subject_as_feature) without return types