我可以将提前停止合并到keras网格搜索中吗？

from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import GridSearchCV
from keras.callbacks import EarlyStopping

# 定义创建模型的函数
def create_model():
    model = Sequential()
    model.add(Dense(10, input_dim=10, activation='relu'))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    return model

# 创建KerasClassifier对象
model = KerasClassifier(build_fn=create_model, verbose=0)

# 定义参数网格
param_grid = {'batch_size': [16, 32, 64],
              'epochs': [10, 20, 30],
              'optimizer': ['adam', 'sgd']}

# 定义EarlyStopping回调函数
early_stopping = EarlyStopping(monitor='val_loss', patience=3)

# 创建GridSearchCV对象
grid = GridSearchCV(estimator=model, param_grid=param_grid, cv=3, verbose=2)

# 在网格搜索中使用提前停止
grid_result = grid.fit(X, y, callbacks=[early_stopping])

# 输出最佳参数和得分
print("Best: %f using %s" % (grid_result.best_score_, grid_result.best_params_))