sklearn_tuner change Bool to Int

[Q-strong]

I got the error "The 'bootstrap' parameter of cross_val_predict must be an instance of 'bool' or an instance of 'numpy.bool_'. Got 0 instead." when running

from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import r2_score, mean_squared_error
from hebo.sklearn_tuner import sklearn_tuner
from sklearn.datasets import fetch_california_housing

data = fetch_california_housing()
X, y = data.data, data.target

space_cfg = [
        {'name' : 'max_depth',        'type' : 'int', 'lb' : 1, 'ub' : 20},
        {'name' : 'min_samples_leaf', 'type' : 'num', 'lb' : 1e-4, 'ub' : 0.5},
        {'name' : 'max_features',     'type' : 'cat', 'categories' : ['auto', 'sqrt', 'log2']},
        {'name' : 'bootstrap',        'type' : 'bool'},
        {'name' : 'min_impurity_decrease', 'type' : 'pow', 'lb' : 1e-4, 'ub' : 1.0},
        ]

result = sklearn_tuner(RandomForestRegressor, space_cfg, X, y, metric = r2_score, max_iter = 16)

The sklearn version is 1.6.1. I believe it may be because in line 35 of bool_param.py, the bool variable is treated as numeric, and then in line 79 of sklearn_tuner.py it changes the bool to int.