python function as cvxpy parameter for dynamic optimization (optimal control)

Question

import numpy as np
def af(a,b):
    return np.array([[a,b],[b**2, b]])
np.random.seed(1)
n = 2
m = 2
T = 50
alpha = 0.2
beta = 3
# A = np.eye(n) - alpha * np.random.rand(n, n)
B = np.random.randn(n, m)
x_0 = beta * np.random.randn(n)
import cvxpy as cp
x = cp.Variable((n, T + 1))
u = cp.Variable((m, T))
A = cp.Parameter((2,2))
cost = 0
constr = []
for t in range(T):
    cost += cp.sum_squares(x[:, t + 1]) + cp.sum_squares(u[:, t])
    A = af(*x[:,t])
    constr += [x[:, t + 1] == A @ x[:, t] + B @ u[:, t], cp.norm(u[:, t], "inf") <= 1]
# sums problem objectives and concatenates constraints.
constr += [x[:, T] == 0, x[:, 0] == x_0]
problem = cp.Problem(cp.Minimize(cost), constr)
problem.solve()

I want to use python function (lambdify function) as cvxpy parameter. I tried this method, please let me know if cvxpy support python function as parameter. thank you.