如何在TensorFlow中自动分配空闲GPU

import tensorflow as tf

gpu_devices = tf.config.experimental.list_physical_devices('GPU')
for device in gpu_devices:
    tf.config.experimental.set_memory_growth(device, True)

gpus = tf.config.experimental.list_physical_devices('GPU')
if gpus:
    strategy = tf.distribute.OneDeviceStrategy(device="/gpu:0")  # 指定使用第一个可用的GPU
    with strategy.scope():
        session = tf.compat.v1.Session(config=tf.compat.v1.ConfigProto(allow_soft_placement=True))
else:
    session = tf.compat.v1.Session(config=tf.compat.v1.ConfigProto(allow_soft_placement=True))

with tf.device('/gpu:0'):
    # 在这里编写需要在GPU上运行的代码