code: def test_calculate_loss_segfault():
      # this code used to segfault, because of a bug in calculate_loss
      factors = 1
      regularization = 0
      n_users, n_items = 4, 4
  
      item_factors = np.random.random((n_items, factors)).astype(
          "float32"
      )
      user_factors = np.random.random((n_users, factors)).astype(
          "float32"
      )
      c_ui = coo_matrix(
          ([1.0, 1.0], ([0, 1], [0, 1])), shape=(n_users, n_items)
      ).tocsr()
  
      loss = implicit.cpu.als.calculate_loss(
          c_ui, user_factors, item_factors, regularization
      )
      assert loss > 0
  
imports: import pickle
  import unittest
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from recommender_base_test import RecommenderBaseTestMixin, get_checker_board
  from scipy.sparse import coo_matrix, csr_matrix, random
  import implicit
  from implicit.als import AlternatingLeastSquares
  from implicit.gpu import HAS_CUDA
label_desc: Use image node_id 12 for calling a global function with example usage: test_calculate_loss_segfault() without return types