code: def test_get_type_vector(self):
      worlds, num_entities = self.get_fake_worlds()
      tensor = torch.LongTensor([])
      type_vector, _ = self.model._get_type_vector(
          worlds, num_entities, tensor
      )
      # Verify that both types are present and padding used for non existent entities.
      assert_almost_equal(
          type_vector.data.numpy(),
          [
              [
                  [1, 0, 0, 0],
                  [0, 1, 0, 0],
                  [0, 1, 0, 0],
                  [0, 0, 0, 1],
                  [0, 0, 0, 1],
              ],
              [
                  [1, 0, 0, 0],
                  [0, 1, 0, 0],
                  [0, 0, 0, 1],
                  [0, 0, 0, 0],
                  [0, 0, 0, 0],
              ],
          ],
      )
  
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 7 for calling the WikiTablesMmlSemanticParserTest obj's underlying member method code with example usage: obj.test_get_type_vector() without return types