Error in Handling of Mixed-Variable-Type Problem in Pymoo Package

Question

I have an optimization problem that I want to solve via tools in pymoo package of version 0.6.1 in Python. I defined my problem as follows,

class Problem(ElementwiseProblem):

  def __init__(self):

    vol_frac_vars = {'vol_frac_' + str(i): Real(bounds=(0, 1)) for i in range(LAM_NUM)}
    theta_vars = {'theta_' + str(i): Choice(options=[-45, 0, 45, 90]) for i in range(LAM_NUM)}
    vars = {**vol_frac_vars, **theta_vars}

    super().__init__(vars=vars,
                     n_obj=1,
                     n_eq_constr=0,
                     n_ieq_constr=1)

  def _evaluate(self, X, out, *args, **kwargs):
    
    v = [X['vol_frac_' + str(i)] for i in range(LAM_NUM)]
    t = [X['theta_' + str(i)] for i in range(LAM_NUM)]

    f1 = # Objective function here

    g1 = # Constraint function here

    out['F'] = [f1]
    out['G'] = [g1]


problem = Problem()

algorithm = MixedVariableGA(pop_size=100, 
                            n_offsprings=10, 
                            sampling=FloatRandomSampling(), 
                            crossover=SBX(prob=0.9, eta=15), 
                            mutation=PM(eta=20), 
                            eliminate_duplicates=True)

termination = get_termination('n_gen', 1000)

result = minimize(problem,
                  algorithm,
                  termination,
                  save_history=True,
                  return_least_infeasible=True,
                  seed=SEED)

It is a mixed-variable-type problem so I used MixedVariableGA as stipulated in the documentation of the package. Also variables in capitals are pre-defined constants specific for my problem. My goal is to find the minimum value of f1 subjected to constraint g1 for n number of vol_frac_vars and n number of theta_vars variables, which in total adds up to 2n number of variables. However, when I run the code, I encounter the following error,

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-18-57a92730b50b> in <cell line: 10>()
      8 termination = get_termination('n_gen', 1000)
      9 
---> 10 result = minimize(problem,
     11                   algorithm,
     12                   termination,

8 frames
/usr/local/lib/python3.10/dist-packages/pymoo/operators/sampling/rnd.py in _do(self, problem, n_samples, **kwargs)
     22         if problem.has_bounds():
     23             xl, xu = problem.bounds()
---> 24             assert np.all(xu >= xl)
     25             X = xl + (xu - xl) * X
     26 

TypeError: '>=' not supported between instances of 'dict' and 'dict'

How can I solve this error?