在多个tf.device情况下，CPU代码可以存在于"with GPU (Gpu_id) :“下吗？

import tensorflow as tf

# 定义一个CPU操作
with tf.device('CPU'):
    a = tf.constant([1, 2, 3])
    b = tf.constant([4, 5, 6])
    c = tf.add(a, b)

# 定义一个GPU操作
with tf.device('GPU:0'):
    d = tf.constant([7, 8, 9])
    e = tf.constant([10, 11, 12])
    f = tf.add(d, e)

# 定义一个CPU操作
with tf.device('CPU'):
    g = tf.constant([13, 14, 15])
    h = tf.constant([16, 17, 18])
    i = tf.add(g, h)

# 执行计算图
with tf.Session() as sess:
    result_c, result_f, result_i = sess.run([c, f, i])
    print("Result c:", result_c)
    print("Result f:", result_f)
    print("Result i:", result_i)