如何在TensorFlow中计算类激活图？

import tensorflow as tf
import numpy as np

model = tf.keras.applications.VGG16(weights='imagenet', include_top=True)

input_image = tf.Variable(np.random.random((1, 224, 224, 3)).astype(np.float32))

target_class = 10  # 假设目标类别为第10类

loss_object = tf.keras.losses.CategoricalCrossentropy()

with tf.GradientTape() as tape:
    tape.watch(input_image)
    predictions = model(input_image)
    loss = loss_object(predictions[:, target_class])

gradient = tape.gradient(loss, input_image)

gradient /= tf.math.reduce_std(gradient) + 1e-8

class_activation_map = tf.reduce_mean(gradient, axis=-1)