'GridSearchCV' object has no attribute 'cv_results_' when fitting ExponentiatedGradient from fairlearn

Question

The GridSearchCV is passed to ExponentiatedGradient. But after fitting the ExponentiatedGradient, cv_results_ are not returned.

gs = GridSearchCV(
                estimator=model,
                param_grid=param,
                cv=RepeatedKFold(n_splits=5, n_repeats=2),
                scoring=scoring,
                return_train_score=True,
                refit='roc_auc_curve',
                n_jobs=-1)
mitigator = ExponentiatedGradient(gs, constraints=EqualizedOdds())
    
mitigator.fit(train_X, y_train, sensitive_features=x_train[set_sa])

print(mitigator.estimator)

GridSearchCV(cv=RepeatedKFold(n_repeats=2, n_splits=5, random_state=None),
             estimator=RandomForestClassifier(), n_jobs=-1,
             param_grid={'max_depth': [4, 7, 10],
                         'n_estimators': [100, 250, 500]},
             refit='roc_auc_curve', return_train_score=True,
             scoring={'acc': 'accuracy', 'bal_acc': 'balanced_accuracy',
                      'f1': 'f1', 'f1_weighted': 'f1_weighted',
                      'gmean': make_scorer(geometric_mean_score),
                      'roc_auc_curve': make_scorer(roc_auc_score, needs_proba=True, max_fpr=0.001)})

print(mitigator.estimator.cv_results_)

AttributeError: 'GridSearchCV' object has no attribute 'cv_results_'