code: def test_basic_fetching_movielens():
      data = fetch_movielens()
  
      assert isinstance(data["train"], sp.coo_matrix)
      assert isinstance(data["test"], sp.coo_matrix)
  
      assert data["train"].shape == data["test"].shape
      assert data["train"].shape == (943, 1682)
      assert (data["train"].getnnz() + data["test"].getnnz()) == 100000
  
      assert data["item_features"].shape == (1682, 1682)
      assert len(data["item_feature_labels"]) == 1682
      assert data["item_feature_labels"] is data["item_labels"]
  
      data = fetch_movielens(genre_features=True)
  
      assert data["item_features"].shape == (
          1682,
          len(data["item_feature_labels"]),
      )
      assert data["item_feature_labels"] is not data["item_labels"]
  
      with pytest.raises(ValueError):
          data = fetch_movielens(
              indicator_features=False, genre_features=False
          )
  
imports: import pytest
  import numpy
  import scipy.sparse
  from lightfm.datasets import fetch_movielens, fetch_stackexchange
label_desc: Use image node_id 1 for calling a global function with example usage: test_basic_fetching_movielens() without return types