def METHOD_NAME(self):
    """Create normalized adjacency matrix.
    Returns:
        scipy.sparse.csr_matrix: Normalized adjacency matrix.
    """
    adj_mat = sp.dok_matrix(
        (self.n_users + self.n_items, self.n_users + self.n_items), dtype=np.float32
    )
    adj_mat = adj_mat.tolil()
    R = self.R.tolil()
    adj_mat[: self.n_users, self.n_users :] = R
    adj_mat[self.n_users :, : self.n_users] = R.T
    adj_mat = adj_mat.todok()
    print("Already create adjacency matrix.")
    rowsum = np.array(adj_mat.sum(1))
    d_inv = np.power(rowsum + 1e-9, -0.5).flatten()
    d_inv[np.isinf(d_inv)] = 0.0
    d_mat_inv = sp.diags(d_inv)
    norm_adj_mat = d_mat_inv.dot(adj_mat)
    norm_adj_mat = norm_adj_mat.dot(d_mat_inv)
    print("Already normalize adjacency matrix.")
    return norm_adj_mat.tocsr()