如何在TensorFlow 2.0中使用Keras API仅恢复模型的零件层的权重？

import tensorflow as tf
from tensorflow.keras.layers import Dense, Flatten

model = tf.keras.Sequential([
    Dense(64, activation='relu', input_shape=(32,)),
    Dense(64, activation='relu'),
    Dense(10, activation='softmax')
])

model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

model.fit(x_train, y_train, epochs=10)

model.save_weights('model_weights.h5')

new_model = tf.keras.Sequential([
    Dense(64, activation='relu', input_shape=(32,)),
    Dense(64, activation='relu')
])

new_model.load_weights('model_weights.h5', by_name=True)