code: def test_backends_with_filters():
      train = np.array(
          [
              [1, 1, 2],
              [1, 1, 3],
              [1, 1, 4],
              [5, 1, 3],
              [5, 1, 4],
              [6, 1, 3],
              [6, 1, 2],
              [6, 1, 4],
              [6, 1, 7],
          ]
      )
      test = np.array(
          [[3, 1, 2], [4, 1, 3], [5, 1, 4], [5, 1, 2], [1, 1, 5]]
      )
      val = np.array([[3, 1, 6], [2, 1, 2], [1, 1, 6]])
      use_filter = {"train": train, "test": test, "val": val}
  
      # complementary objects to 1,1,?: train: 2, 3, 4, test: 5, val: 6
      # complementary subjects to ?,1,2: train: 1, 6, test: 3, 5, val: 2
  
      data_dummy = GraphDataLoader(
          train,
          batch_size=1,
          dataset_type="train",
          use_filter=use_filter,
      )
      triple = np.array([[0, 0, 1]])
      data_db = GraphDataLoader(
          train,
          batch_size=1,
          dataset_type="train",
          backend=SQLiteAdapter,
          use_filter=use_filter,
      )
      data_db.add_dataset(test, dataset_type="test")
      data_db.add_dataset(val, dataset_type="val")
  
      dummy = data_dummy.backend.mapper.get_indexes(
          data_dummy.get_complementary_objects(
              triple, use_filter=use_filter
          )[0],
          type_of="e",
          order="ind2raw",
      )
      db = data_db.backend.mapper.get_indexes(
          data_db.get_complementary_objects(
              triple, use_filter=use_filter
          )[0],
          type_of="e",
          order="ind2raw",
      )
      assert np.array_equal(
          dummy, db
      ), "Backends differ: dummy: {}, db: {}".format(dummy, db)
  
file_path: AmpliGraph/tests/ampligraph/datasets/test_graph_data_loader.py
imports: from ampligraph.datasets import GraphDataLoader, NoBackend
  from ampligraph.datasets.sqlite_adapter import SQLiteAdapter
  import pytest
  import numpy
  import pandas
label_desc: Use image node_id 9 for calling a global function with example usage: test_backends_with_filters() without return types