如何保存/加载具有多个分支的keras模型

from keras.models import Model
from keras.layers import Input, Dense

input_layer = Input(shape=(input_shape,))
branch1_output = Dense(units=64, activation='relu')(input_layer)
branch2_output = Dense(units=128, activation='relu')(input_layer)

output_layer = Dense(units=num_classes, activation='softmax')([branch1_output, branch2_output])

model = Model(inputs=input_layer, outputs=output_layer)

model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, validation_data=(x_val, y_val))

model.save('model.h5')

from keras.models import load_model

model = load_model('model.h5')

predictions = model.predict(x_test)