如何使用Keras冻结某些图层中的权重？

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

input_layer = Input(shape=(input_shape,))
hidden_layer_1 = Dense(units=64, activation='relu')(input_layer)
hidden_layer_2 = Dense(units=32, activation='relu')(hidden_layer_1)
output_layer = Dense(units=num_classes, activation='softmax')(hidden_layer_2)

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

for layer in model.layers[:freeze_layers]:
    layer.trainable = False

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))