How TPOT specify categorical feature by lgbm?

Hi all,

As we know, lgbm is capable of specifying the categorical features through the **categorical_feature** parameter of the **fit** function. As follows：
`model = lgb.LGBMRegressor()
model .fit(X_train, y_train,feature_name=list(X_train.columns),
categorical_feature=list(['col_1', 'col_2']))`

I know TPOT added **OneHotEncoder** to handle Categorical features. However, the idea of ​​lgbm processing categories is not just based on one-hot. So, how can i use TPOT_CONFIG to specify the categorical feature of lgbm?

Thank you very much and best regards!