如何在Keras中缓存图层激活？

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.callbacks import LambdaCallback

activations = []

def get_activations(model, layer_name):
    intermediate_layer_model = tf.keras.Model(inputs=model.input, outputs=model.get_layer(layer_name).output)
    intermediate_output = intermediate_layer_model.predict(x_train)  # 这里的x_train是你的训练数据
    activations.append(intermediate_output)

cache_activations = LambdaCallback(on_epoch_end=lambda epoch, logs: get_activations(model, layer_name))

model.fit(x_train, y_train, epochs=10, callbacks=[cache_activations])