如何使用Tensorflow Keras api从预先训练的模型中复制特定的层权重？

import tensorflow as tf
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Dense

pretrained_model = tf.keras.applications.<ModelName>(weights='imagenet', include_top=False)

input_tensor = pretrained_model.input
output_tensor = pretrained_model.get_layer('<LayerName>').output

new_model = Model(inputs=input_tensor, outputs=output_tensor)
new_model.load_weights('<Path_to_Weights>')

x = new_model.output
x = Dense(<Number_of_Neurons>, activation='relu')(x)
# 添加更多自定义层...

new_output = Dense(<Number_of_Classes>, activation='softmax')(x)

new_model = Model(inputs=new_model.input, outputs=new_output)

new_model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])

# 训练新模型...