code: def test_pickle_homo_graph(
      total_num_nodes, total_num_edges, has_node_attrs, has_edge_attrs
  ):
      csc_indptr, indices = gbt.random_homo_graph(
          total_num_nodes, total_num_edges
      )
      node_attributes = None
      if has_node_attrs:
          node_attributes = {
              "A": torch.arange(total_num_nodes),
              "B": torch.arange(total_num_nodes),
          }
      edge_attributes = None
      if has_edge_attrs:
          edge_attributes = {
              "A": torch.arange(total_num_edges),
              "B": torch.arange(total_num_edges),
          }
      graph = gb.fused_csc_sampling_graph(
          csc_indptr,
          indices,
          node_attributes=node_attributes,
          edge_attributes=edge_attributes,
      )
  
      serialized = pickle.dumps(graph)
      graph2 = pickle.loads(serialized)
  
      assert graph.total_num_nodes == graph2.total_num_nodes
      assert graph.total_num_edges == graph2.total_num_edges
  
      assert torch.equal(graph.csc_indptr, graph2.csc_indptr)
      assert torch.equal(graph.indices, graph2.indices)
  
      assert (
          graph.node_type_offset is None
          and graph2.node_type_offset is None
      )
      assert (
          graph.type_per_edge is None and graph2.type_per_edge is None
      )
      assert (
          graph.node_type_to_id is None
          and graph2.node_type_to_id is None
      )
      assert (
          graph.edge_type_to_id is None
          and graph2.edge_type_to_id is None
      )
      if has_node_attrs:
          assert (
              graph.node_attributes.keys()
              == graph2.node_attributes.keys()
          )
          for key in graph.node_attributes.keys():
              assert torch.equal(
                  graph.node_attributes[key],
                  graph2.node_attributes[key],
              )
      else:
          assert (
              graph.node_attributes is None
              and graph2.node_attributes is None
          )
      if has_edge_attrs:
          assert (
              graph.edge_attributes.keys()
              == graph2.edge_attributes.keys()
          )
          for key in graph.edge_attributes.keys():
              assert torch.equal(
                  graph.edge_attributes[key],
                  graph2.edge_attributes[key],
              )
      else:
          assert (
              graph.edge_attributes is None
              and graph2.edge_attributes is None
          )
  
imports: import os
  import pickle
  import re
  import tempfile
  import unittest
  import backend
  import dgl
  import dgl.graphbolt
  import pytest
  import torch
  import torch.multiprocessing
  from dgl.graphbolt.base import etype_str_to_tuple
  from scipy import sparse
  from ..None import gb_test_utils
label_desc: Use image node_id 12 for calling a global function with example usage: test_pickle_homo_graph(total_num_nodes, total_num_edges, has_node_attrs, has_edge_attrs) without return types