我有以下代码可以在分布式tensorflow中做一些简单的算术计算。一个最小的可重现示例是:-
import tensorflow as tf
global_step_tensor = tf.Variable(10, trainable=False, name='global_step')
cluster = tf.train.ClusterSpec({"local": ["localhost:2222", "localhost:2223","localhost:2224", "localhost:2225"]})
x = tf.constant(2)
with tf.device("/job:local/task:0"):
y = x + 300
model = tf.global_variables_initializer()
saver = tf.train.Saver([y])
ChiefSessionCreator = tf.train.ChiefSessionCreator(scaffold=None, master='grpc://localhost:2222', config=None, checkpoint_dir='/home/chaitanya/tensorflow/codes/checkpoints')
saver_hook = tf.train.CheckpointSaverHook(checkpoint_dir='/home/chaitanya/tensorflow/codes/checkpoints', save_secs=10, save_steps=None, saver=y, checkpoint_basename='model.ckpt', scaffold=None)
summary_hook = tf.train.SummarySaverHook(save_steps=None, save_secs=10, output_dir='/home/chaitanya/tensorflow/codes/savepoints', summary_writer=None, scaffold=None, summary_op=y)
with tf.train.MonitoredTrainingSession(master='grpc://localhost:2222', is_chief=True, checkpoint_dir='/home/chaitanya/tensorflow/codes/checkpoints',
scaffold=None, hooks=[saver_hook, summary_hook], chief_only_hooks=None, save_checkpoint_secs=10, save_summaries_steps=None, config=None) as sess:
while not sess.should_stop():
sess.run(model)
while not sess.should_stop():
result = sess.run(y)
print(result)
错误如下:-
Traceback (most recent call last):
File "add_1.py", line 13, in <module>
saver = tf.train.Saver([y])
raise TypeError("Variable to save is not a Variable: %s" % var)
TypeError: Variable to save is not a Variable: Tensor("add_3:0", shape=(), dtype=int32, device=/job:local/task:3)
请帮我想出正确的方法来使用这个函数。
最佳答案
当您简单地编写 x + 300
时,您并没有创建 tf.Variable
。您需要显式使用 tf.get_variable()
或 tf.Variable()
来创建可以保存的变量。
y = tf.Variable(x + 300)
关于python - 类型错误 : Variable to save is not a Variable,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/41498883/