如何在TensorFlow 2中保存/加载模型的一部分？

import tensorflow as tf

# 定义并训练模型
model = tf.keras.Sequential([
    tf.keras.layers.Dense(64, activation='relu'),
    tf.keras.layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])
model.fit(x_train, y_train, epochs=10)

# 保存整个模型
tf.saved_model.save(model, 'saved_model/')

import tensorflow as tf

# 定义并训练模型
model = tf.keras.Sequential([
    tf.keras.layers.Dense(64, activation='relu'),
    tf.keras.layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])
model.fit(x_train, y_train, epochs=10)

# 保存模型的某个层
layer_to_save = model.layers[0]
tf.saved_model.save(layer_to_save, 'saved_model/')