tf.train.Saver（）和GPU問題 - TensorFlow

Question

我的代碼結構如下：

with tf.device('/gpu:1'):
...
model = get_model(input_pl)
...
    with tf.Session() as sess:
        saver = tf.train.Saver()
        sess.run(tf.global_variables_initializer())
        for epoch in range(num_epochs):
           ...
           for n in range(num_batches):
              ...
              sess.run(...)
           # eval epoch
        saver.save(sess, ...)

我想在訓練階段后保存模型。 當我運行它給我這個錯誤：

InvalidArgumentError (see above for traceback): Cannot assign a device for operation 'save/SaveV2': Could not satisfy explicit device specification '/device:GPU:1' because no supported kernel for GPU devices is available.

閱讀這個問題我用這種方式改變了代碼：

saver = tf.train.Saver()
with tf.device('/gpu:1'):
...
model = get_model(pointcloud_pl)
...
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch in range(num_epochs):
           ...
           for n in range(num_batches):
              ...
              sess.run(...)
           # eval epoch
        saver.save(sess, ...)

但是現在我收到了這個錯誤：

ValueError: No variables to save

我也嘗試過這樣做：

with tf.Session() as sess:
    saver = tf.train.Saver()
    ...
    with tf.device('/gpu:1'):
        sess.run(tf.global_variables_initializer())
        for epoch in range(num_epochs):
        ...
            for n in range(num_batches):
               ...
               sess.run()
            # eval epoch
        saver.save(sess, ...)

我仍然得到同樣的錯誤。 該錯誤始終在saver = tf.train.Saver()行中。

我怎么解決這個問題？

Answer 1

解決了這個問題：

1. tf.Session()
2. 模型
3. saver = tf.train.Saver()
4. with tf.device():

這是一個示例代碼

with tf.Session() as sess:
    ...
    model = get_model(input_pl)
    saver = tf.train.Saver()
    ...
    with tf.device('/gpu:1'):
        sess.run(tf.global_variables_initializer())
        for epoch in range(num_epochs):
        ...
            for n in range(num_batches):
               ...
               sess.run()
            # eval epoch
        saver.save(sess, ...)