Keras:如何在keras中实现层的o/p的重新排序？

import tensorflow as tf
from tensorflow import keras

model = keras.Sequential()
model.add(keras.layers.Dense(64, activation='relu', input_shape=(input_dim,)))
model.add(keras.layers.Dense(32, activation='relu'))
model.add(keras.layers.Dense(10, activation='softmax'))

layer_output = model.layers[layer_index].output

reordered_output = tf.gather(layer_output, indices, axis=1)

new_model = keras.Model(inputs=model.input, outputs=reordered_output)

import tensorflow as tf
from tensorflow import keras

# 创建模型并添加层
model = keras.Sequential()
model.add(keras.layers.Dense(64, activation='relu', input_shape=(input_dim,)))
model.add(keras.layers.Dense(32, activation='relu'))
model.add(keras.layers.Dense(10, activation='softmax'))

# 获取某一层的输出
layer_output = model.layers[layer_index].output

# 重新排序输出
indices = [2, 0, 1]  # 示例重新排序为第3列、第1列、第2列
reordered_output = tf.gather(layer_output, indices, axis=1)

# 创建新模型
new_model = keras.Model(inputs=model.input, outputs=reordered_output)