def get_checker_board(self, X):
ret = np.zeros((X, X))<EOL>for i in range(X):<EOL><INDENT>for j in range(i % <NUM_LIT:2>, X, <NUM_LIT:2>):<EOL><INDENT>ret[i, j] = <NUM_LIT:1.0><EOL><DEDENT><DEDENT>return csr_matrix(ret - np.eye(X))<EOL>
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