class_docstr: Mixin to test a bunch of common functionality in models
  deriving from RecommenderBase
code: def test_similar_items_batch(self):
      model = self._get_model()
      user_items = get_checker_board(256)
      model.fit(user_items, show_progress=False)
      itemids = np.arange(50)
  
      def check_results(ids):
          self.assertEqual(ids.shape, (50, 10))
          for itemid in itemids:
              # first item returned should be itself
              self.assertEqual(ids[itemid][0], itemid)
  
              # the rest of the items should be even or odd depending on the itemid
              for r in ids[itemid]:
                  self.assertEqual(r % 2, itemid % 2)
  
      ids, _ = model.similar_items(itemids, N=10)
      check_results(ids)
      try:
          ids, _ = model.similar_items(
              itemids,
              N=10,
              recalculate_item=True,
              item_users=user_items.T.tocsr()[itemids],
          )
          check_results(ids)
      except NotImplementedError:
          # some models don't support recalculating user on the fly, and that's ok
          pass
  
imports: import os
  import pickle
  import random
  import tempfile
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from scipy.sparse import coo_matrix, csr_matrix
  from implicit.evaluation import precision_at_k
  from implicit.nearest_neighbours import ItemItemRecommender
  from implicit.utils import ParameterWarning
label_desc: Use image node_id 10 for calling the RecommenderBaseTestMixin obj's underlying member method code with example usage: obj.test_similar_items_batch() without return types