code: def test_fit_almost_empty_matrix():
      raw = [[0, 0, 0], [0, 1, 0], [0, 0, 0]]
      return BayesianPersonalizedRanking(use_gpu=False).fit(
          csr_matrix(raw), show_progress=False
      )
  
file_path: implicit/tests/bpr_test.py
imports: import unittest
  from recommender_base_test import RecommenderBaseTestMixin
  from scipy.sparse import csr_matrix
  from implicit.bpr import BayesianPersonalizedRanking
  from implicit.gpu import HAS_CUDA
label_desc: Use image node_id 2 for calling a global function with example usage: test_fit_almost_empty_matrix() and returns: BayesianPersonalizedRanking