在Keras Tuner搜索期间，如何让有状态的LSTM在两个时期之间重置其状态？

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from kerastuner.tuners import RandomSearch

# 定义有状态的LSTM模型
def build_model(hp):
    model = keras.Sequential()
    model.add(layers.LSTM(units=hp.Int('units', min_value=32, max_value=512, step=32), stateful=True))
    model.add(layers.Dense(1, activation='sigmoid'))
    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
    return model

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

# 创建Keras Tuner随机搜索实例
tuner = RandomSearch(
    build_model,
    objective='val_accuracy',
    max_trials=5,
    executions_per_trial=1,
    directory='my_dir',
    project_name='my_project')

# 开始搜索
tuner.search(x_train, y_train, epochs=10, validation_data=(x_val, y_val), callbacks=[early_stopping])

# 获取最佳模型
best_model = tuner.get_best_models(num_models=1)[0]