mlpclassifier check weights

GRID = [
    {'scaler': [StandardScaler()],
     'estimator': [MLPClassifier(random_state=RANDOM_SEED)],
     'estimator__solver': ['adam'],
     'estimator__learning_rate_init': [0.0001],
     'estimator__max_iter': [300],
     'estimator__hidden_layer_sizes': [(500, 400, 300, 200, 100), (400, 400, 400, 400, 400), (300, 300, 300, 300, 300), (200, 200, 200, 200, 200)],
     'estimator__activation': ['logistic', 'tanh', 'relu'],
     'estimator__alpha': [0.0001, 0.001, 0.005],
     'estimator__early_stopping': [True, False]
     }
]

PIPELINE = Pipeline([('scaler', None), ('estimator', MLPClassifier())])

grid_search = GridSearchCV(estimator=PIPELINE, param_grid=GRID, 
                            scoring=make_scorer(accuracy_score),# average='macro'), 
                            n_jobs=-1, cv=split, refit=True, verbose=1, 
                            return_train_score=False)

grid_search.fit(X, y)