code: def test_UnknownPartitionBook():
      node_map = {"_N": {0: 0, 1: 1, 2: 2}}
      edge_map = {"_N:_E:_N": {0: 0, 1: 1, 2: 2}}
  
      part_metadata = {
          "num_parts": 1,
          "num_nodes": len(node_map),
          "num_edges": len(edge_map),
          "node_map": node_map,
          "edge_map": edge_map,
          "graph_name": "test_graph",
      }
  
      with tempfile.TemporaryDirectory() as test_dir:
          part_config = os.path.join(test_dir, "test_graph.json")
          with open(part_config, "w") as file:
              json.dump(part_metadata, file, indent=4)
          try:
              load_partition_book(part_config, 0)
          except Exception as e:
              if not isinstance(e, TypeError):
                  raise e
  
imports: import json
  import os
  import tempfile
  import backend
  import dgl
  import numpy
  import pytest
  import torch
  from dgl import function
  from dgl.distributed import convert_dgl_partition_to_csc_sampling_graph, load_partition, load_partition_book, load_partition_feats, partition_graph
  from dgl.distributed.graph_partition_book import _etype_str_to_tuple, _etype_tuple_to_str, DEFAULT_ETYPE, DEFAULT_NTYPE, EdgePartitionPolicy, HeteroDataName, NodePartitionPolicy, RangePartitionBook
  from dgl.distributed.partition import _get_inner_edge_mask, _get_inner_node_mask, RESERVED_FIELD_DTYPE
  from scipy import sparse
  from utils import reset_envs
label_desc: Use image node_id 11 for calling a global function with example usage: test_UnknownPartitionBook() without return types