code: def test_fitting(fitting):
      output, _ = fitting
      assert output.shape == (4, 4)
      target = np.array(
          [
              [0, 0.10000000894069672, "train", "Precision"],
              [0, 0.10000000149011612, "test", "Precision"],
              [0, 1.0, "train", "Recall"],
              [0, 1.0, "test", "Recall"],
          ],
          dtype="object",
      )
      np.testing.assert_array_equal(output, target)
  
file_path: recommenders/tests/unit/recommenders/models/test_lightfm_utils.py
imports: import pytest
  import itertools
  import numpy
  import pandas
  from lightfm.data import Dataset
  from lightfm import LightFM, cross_validation
  from recommenders.models.lightfm.lightfm_utils import track_model_metrics, similar_users, similar_items
label_desc: Use image node_id 8 for calling a global function with example usage: test_fitting(fitting) without return types