ValueError:传递的 save_path 不是有效的检查点:C:\Users\User\model.tflearn [英] ValueError: The passed save_path is not a valid checkpoint: C:\Users\User\model.tflearn

问题描述

我一直在尝试创建一个聊天机器人，但我一直收到以下错误.我是 TensorFlow 的初学者.

I have been trying to create a chatbot but I keep getting the following error. I am a beginner in TensorFlow.

Traceback (most recent call last):
  File "main.py", line 78, in <module>
    model.load("model.tflearn")
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tflearn\models\dnn.py", line 308, in load
    self.trainer.restore(model_file, weights_only, **optargs)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tflearn\helpers\trainer.py", line 490, in restore
    self.restorer.restore(self.session, model_file)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tensorflow\python\training\saver.py", line 1278, in restore
    compat.as_text(save_path))
ValueError: The passed save_path is not a valid checkpoint: C:\Users\User\model.tflearn

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "main.py", line 80, in <module>
    model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tflearn\models\dnn.py", line 216, in fit
    callbacks=callbacks)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tflearn\helpers\trainer.py", line 339, in fit
    show_metric)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tflearn\helpers\trainer.py", line 816, in _train
    tflearn.is_training(True, session=self.session)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tflearn\config.py", line 95, in is_training
    tf.get_collection('is_training_ops')[0].eval(session=session)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tensorflow\python\framework\ops.py", line 731, in eval
    return _eval_using_default_session(self, feed_dict, self.graph, session)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tensorflow\python\framework\ops.py", line 5579, in _eval_using_default_session
    return session.run(tensors, feed_dict)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
    run_metadata_ptr)
  File "C:\Users\User\Anaconda3\envs\newbot\lib\site-packages\tensorflow\python\client\session.py", line 1096, in _run
    raise RuntimeError('Attempted to use a closed Session.')
RuntimeError: Attempted to use a closed Session.

这是我的 TensorFlow 代码:

This is my TensorFlow code:

tensorflow.reset_default_graph()

net = tflearn.input_data(shape=[None, len(training[0])])
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, len(output[0]), activation="softmax")
net = tflearn.regression(net)

model = tflearn.DNN(net)

try: 
    model.load("model.tflearn")
except:
    model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
    model.save("model.tflearn")

我正在使用:

• Python 3.6.9
• TensorFlow 1.14.0
• TFLearn 0.3.2

先谢谢你！

推荐答案

将您的 Tensorflow 代码更改为:

Change your Tensorflow code to:

try:
    model.load('model.tflearn')
except:
    tensorflow.reset_default_graph()

    net = tflearn.input_data(shape=[None, len(training[0])])
    net = tflearn.fully_connected(net, 8)
    net = tflearn.fully_connected(net, 8)
    net = tflearn.fully_connected(net, len(output[0]), activation='softmax')
    net = tflearn.regression(net)

    model = tflearn.DNN(net)

    model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
    model.save("model.tflearn")

我认为问题的发生是因为您正在创建和重置模型，然后请求加载它，然后框架丢失了.

I think the problem happens because you are creating and reseting a model and then requesting to load it, and then the framework gets lost.

这篇关于ValueError:传递的 save_path 不是有效的检查点:C:\Users\User\model.tflearn的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！