Using PyGAD for feature selection

I'm trying to create a Python script for feature selection using PyGAD

The code below shows my previous attempt, but I haven’t achieved the desired result. Can you please help me with the correct implementation? Im taking the primary example shown on the package's documentation page.The error Im receiving is:

AttributeError: 'tuple' object has no attribute 'tb_frame'

My attempt so far:

import pygad
import numpy

from sklearn.model_selection import train_test_split, cross_val_score
from src.learner_params import target_column, model_features

from sklearn.datasets import load_breast_cancer
from lightgbm import LGBMClassifier as lgbm

bc = load_breast_cancer()
bst = lgbm(random_state = 42)

function_inputs = bc.feature_names

X, y = bc.data,bc.target
X = pd.DataFrame(X, columns=bc.feature_names)
X_train, X_test, y_train, y_test = train_test_split(X,
                                                    y,
                                                    random_state=42)



def fitness_func(ga_instance, solution, solution_idx):
    # output = numpy.sum(solution*function_inputs)
    score = cross_val_score(bst, X_train.loc[:,solution], y_train, scoring="roc_auc", cv = 2).mean()
    fitness = score
    return fitness



fitness_function = fitness_func

num_generations = 50
num_parents_mating = 4

sol_per_pop = 8
num_genes = len(X_train)

init_range_low = -2
init_range_high = 5

parent_selection_type = "sss"
keep_parents = 1

crossover_type = "single_point"

mutation_type = "random"
mutation_percent_genes = 10



ga_instance = pygad.GA(num_generations=num_generations,
                       num_parents_mating=num_parents_mating,
                       fitness_func=fitness_function,
                       sol_per_pop=sol_per_pop,
                       num_genes=num_genes,
                       init_range_low=init_range_low,
                       init_range_high=init_range_high,
                       parent_selection_type=parent_selection_type,
                       keep_parents=keep_parents,
                       crossover_type=crossover_type,
                       mutation_type=mutation_type,
                       mutation_percent_genes=mutation_percent_genes)


ga_instance.run()

source https://stackoverflow.com/questions/76715689/using-pygad-for-feature-selection