code: def test_zero_iterations_with_loss(use_gpu):
      model = AlternatingLeastSquares(
          factors=128,
          use_gpu=use_gpu,
          iterations=0,
          calculate_training_loss=True,
      )
      model.fit(csr_matrix(np.ones((10, 10))), show_progress=False)
  
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 1 for calling a global function with example usage: test_zero_iterations_with_loss(use_gpu) without return types