How to use the blueqat.vqe.Vqe function in blueqat

p = 1
        m = 1
        for b in bits[:n1_bits]:
            if b:
                p += 2**m
            m += 1
        q = 1
        m = 1
        for b in bits[n1_bits:]:
            if b:
                q += 2**m
            m += 1
        return p, q

    hamiltonian = (num - mk_expr(0, n1_bits) * mk_expr(n1_bits, n2_bits))**2
    return vqe.Vqe(vqe.QaoaAnsatz(hamiltonian, n_step), minimizer, sampler), bitseparator

def qaoa(self,shots=1,step=2,verbose=False):
		from blueqat import vqe
		return vqe.Vqe(vqe.QaoaAnsatz(pauli(self.qubo),step)).run()

:param n_sample: The number of sampling time of each measurement in VQE.
                     If None, use calculated ideal value.
    :param edges: The edges list of the graph.
    :returns Vqe object
    """
    sampler = sampler or vqe.non_sampling_sampler
    minimizer = minimizer or vqe.get_scipy_minimizer(
        method="Powell",
        options={"ftol": 5.0e-2, "xtol": 5.0e-2, "maxiter": 1000, "disp": True}
    )
    hamiltonian = pauli.I() * 0

    for i, j in edges:
        hamiltonian += pauli.Z(i) * pauli.Z(j)

    return vqe.Vqe(vqe.QaoaAnsatz(hamiltonian, n_step), minimizer, sampler)

:param n_sample: The number of sampling time of each measurement in VQE.
                     If None, use calculated ideal value.
    :param edges: The edges list of the graph.
    :returns Vqe object
    """
    sampler = sampler or vqe.non_sampling_sampler
    minimizer = minimizer or vqe.get_scipy_minimizer(
        method="Powell",
        options={"ftol": 5.0e-2, "xtol": 5.0e-2, "maxiter": 1000, "disp": True}
    )
    hamiltonian = pauli.I() * 0

    for i, j in edges:
        hamiltonian += pauli.Z(i) * pauli.Z(j)

    return vqe.Vqe(vqe.QaoaAnsatz(hamiltonian, n_step), minimizer, sampler)

def numpartition_qaoa(n_step, nums, minimizer=None, sampler=None):
    """Do the Number partition QAOA.

    :param n_step: The number of step of QAOA
    :param nums: The edges list of the graph.
    :returns Vqe object
    """
    hamiltonian = pauli.Expr.zero()
    for i, x in enumerate(nums):
        hamiltonian += pauli.Z[i] * x
    hamiltonian = (hamiltonian ** 2).simplify()

    return vqe.Vqe(vqe.QaoaAnsatz(hamiltonian, n_step), minimizer, sampler)