code: def get_fake_worlds(self):
      # Generate a toy WikitablesWorld.
      FakeTable = namedtuple("FakeTable", ["entities", "neighbors"])
      FakeWorld = namedtuple("FakeWorld", ["table_graph"])
      entities = [
          [
              "0",
              "fb:cell.2010",
              "fb:cell.2011",
              "fb:row.row.year",
              "fb:row.row.year2",
          ],
          ["1", "fb:cell.2012", "fb:row.row.year"],
      ]
      neighbors = [
          {
              "fb:cell.2010": ["fb:row.row.year", "fb:row.row.year2"],
              "fb:cell.2011": ["fb:row.row.year", "fb:row.row.year2"],
              "fb:row.row.year": ["fb:cell.2010", "fb:cell.2011"],
              "fb:row.row.year2": ["fb:cell.2010", "fb:cell.2011"],
              "0": [],
          },
          {
              "fb:cell.2012": ["fb:row.row.year"],
              "fb:row.row.year": ["fb:cell.2012"],
              "1": [],
          },
      ]
  
      worlds = [
          FakeWorld(FakeTable(entity_list, entity2neighbors))
          for entity_list, entity2neighbors in izip(entities, neighbors)
      ]
      num_entities = max([len(entity_list) for entity_list in entities])
      return worlds, num_entities
  
imports: from __future__ import division
  from __future__ import absolute_import
  from collections import namedtuple
  import os
  import pytest
  from flaky import flaky
  from numpy.testing import assert_almost_equal
  import torch
  from allennlp.common import Params
  from allennlp.common.testing import ModelTestCase
  from allennlp.models import Model, WikiTablesMmlSemanticParser
  from allennlp.training.metrics.wikitables_accuracy import SEMPRE_ABBREVIATIONS_PATH, SEMPRE_GRAMMAR_PATH
label_desc: Use image node_id 9 for calling the WikiTablesMmlSemanticParserTest obj's underlying member method code with example usage: obj.get_fake_worlds() and returns: worlds,  num_entities