Pipeline+GridSearchCV

from sklearn.datasets import load_iris
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.preprocessing import StandardScaler, MinMaxScaler
from sklearn.pipeline import Pipeline
iris = load_iris()
X_train, X_test, y_train, y_test = train_test_split(____)
pipe = Pipeline([('____', StandardScaler()), ('____', MLPClassifier(____))])
param_grid = {'____': [StandardScaler(), MinMaxScaler()], '____': [(____,), (____,)]}
grid = GridSearchCV(____)
grid.fit(____)
print(____)