问题：Cannot assign a device for operation Variable

报错代码：

import tensorflow as tf
import numpy as np
import os
os.environ["CUDA_DEVICES_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1"with tf.device("/gpu:0"): ## 与下面注释的命令等价
# with tf.device("/job:localhost/replica:0/task:0/device:GPU:0"):a = tf.Variable(0,dtype=tf.float32)with tf.device("/gpu:1"):b = tf.constant(0, shape=[1], dtype=tf.float32)config = tf.ConfigProto()
config.gpu_options.allow_growth = True
config.log_device_placement = True
with tf.Session(config=config) as sess:sess.run(tf.global_variables_initializer())c = sess.run(a)b_ = sess.run(b)print(b_,c)

报错：

tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot assign a device for operation Variable: node Variable (defined at /wzg_code/×××/multi_gpu_test.py:19) was explicitly assigned to /device:GPU:1 but available devices are [ /job:localhost/replica:0/task:0/device:CPU:0, /job:localhost/replica:0/task:0/device:XLA_CPU:0, /job:localhost/replica:0/task:0/device:XLA_GPU:0, /job:localhost/replica:0/task:0/device:XLA_GPU:1 ]. Make sure the device specification refers to a valid device.[[Variable]]

当时考虑了将 tf.device("gpu:0") 的位置改成： tf.device(“/job:localhost/replica:0/task:0/device:XLA_GPU:0”），仍然报错，最后发现需要在sess的配置上进行修改，增加 config.allow_soft_placement=True,虽然不知道为什么，但是work了。更正后的代码如下：

import tensorflow as tf
import numpy as np
import os
os.environ["CUDA_DEVICES_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1"with tf.device("/gpu:0"):
# with tf.device("/job:localhost/replica:0/task:0/device:GPU:0"):a = tf.Variable(0,dtype=tf.float32)with tf.device("/gpu:1"):b = tf.constant(0, shape=[1], dtype=tf.float32)#config = tf.ConfigProto()
config = tf.ConfigProto(allow_soft_placement=True)
config.gpu_options.allow_growth = True
config.log_device_placement = True
with tf.Session(config=config) as sess:sess.run(tf.global_variables_initializer())c = sess.run(a)b_ = sess.run(b)print(b_,c)

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