请帮我生成一段基于知识蒸馏的人脸识别系统的代码

好的，以下是基于知识蒸馏的人脸识别系统的部分代码示例：

import tensorflow as tf
from keras.models import Sequential
from keras.layers import Dense, Dropout
from keras.applications.inception_v3 import InceptionV3
from keras.optimizers import Adam
from keras.preprocessing.image import ImageDataGenerator

# 载入 InceptionV3 模型的权重
inc_model = InceptionV3(weights='imagenet', include_top=False, input_shape=(224, 224, 3))

# 新建一个顺序模型
model = Sequential()

# 往顺序模型中添加 InceptionV3 的组成部分
for layer in inc_model.layers:
model.add(layer)

# 接在顺序模型尾部的全连接层
model.add(Dense(1024, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(1024, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(2, activation='softmax'))

# 冻结 InceptionV3 组成部分的参数
for layer in model.layers[:-3]:
layer.trainable = False

# 编译模型
model.compile(optimizer=Adam(learning_rate=1e-3), loss='categorical_crossentropy', metrics=['accuracy'])

# 定义训练和验证数据的数据生成器
train_datagen = ImageDataGenerator(rescale=1. / 255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True)
val_datagen = ImageDataGenerator(rescale=1. / 255)

train_generator = train_datagen.flow_from_directory('/train', target_size=(224, 224), batch_size=32, class_mode='categorical')
val_generator = val_datagen.flow_from_directory('/val', target_size=(224, 224), batch_size=32, class_mode='categorical')

# 训练模型
model.fit_generator(train_generator, epochs=30, validation_data=val_generator)

# 评估模型性能
scores = model.evaluate_generator(val_generator)
print("准确率: %.2f%%" % (scores[1] * 100))