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Complete this python program:
def _smw_solver(s, A, AtA, BI, di):
assistant
#Here is the Python code you requested.

    """Solves the system (s*I + A*B*A\) * x = rhs for an arbitrary rhs.
    The inverse matrix of B is block diagonal.  The upper left block
    is BI and the lower right block is a diagonal matrix containing
    di.
    Parameters
    s : scalar
    See above for usage
    A : ndarray
    See above for usage
    AtA : square ndarray
    A.T * A
    BI : square symmetric ndarray
    The inverse of `B`.
    di : array-like
    Returns
    A function that takes `rhs` as an input argument and returns a
    solution to the linear system defined above.
    """
    qmat = (AtA / s)
    m = BI.shape[0]
    qmat[0:m, 0:m] += BI
    ix = np.arange(m, A.shape[1])
    qmat[(ix, ix)] += di
    if sparse.issparse(A):
        qi = sparse.linalg.inv(qmat)
        qmati = A.dot(qi.T).T
    else:
        qmati = np.linalg.solve(qmat, A.T)
    def solver(rhs):
        if sparse.issparse(A):
            ql = qmati.dot(rhs)
            ql = A.dot(ql)
        else:
            ql = np.dot(qmati, rhs)
            ql = np.dot(A, ql)
        rslt = ((rhs / s) - (ql / (s ** 2)))
        if sparse.issparse(rslt):
            rslt = np.asarray(rslt.todense())
        return rslt
    return solver