code: def get_checker_board(X):
      """Returns a 'checkerboard' matrix: where every even userid has liked
      every even itemid and every odd userid has liked every odd itemid.
      The diagonal is withheld for testing recommend methods"""
      ret = np.zeros((X, X))
      for i in range(X):
          for j in range(i % 2, X, 2):
              ret[i, j] = 1.0
      return csr_matrix(ret - np.eye(X))
  
imports: import os
  import pickle
  import random
  import tempfile
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from scipy.sparse import coo_matrix, csr_matrix
  from implicit.evaluation import precision_at_k
  from implicit.nearest_neighbours import ItemItemRecommender
  from implicit.utils import ParameterWarning
label_desc: Use image node_id 1 for calling a global function with example usage: get_checker_board(X) and returns: csr_matrix