TFLearn在加载训练过的模型时抛出错误

我是TFLearn和Tensorflow的新手，我尝试通过关于任何任务的神经网络来了解它们。我成功地训练了一个模型来对推文进行情绪分析。我用model.save(path)保存我的模型。TFLearn在加载训练过的模型时抛出错误

现在，当我运行model.load(path)时，它会引发错误。具体而言，从文件中装载了模型的代码是这样的：

def loadModel(model = None, max_size=40, path="model.save"): 
    # Load the saved model from the specified path 
    global VOCABULARY_SIZE 

    if model == None: 
     plh = tf.placeholder(tf.float32, shape = (None, max_size)) # Creates a Placeholder that is used in buildNetwork() to create the input layer. 
     model = buildNetwork(plh, dictionary_size=len(VOCABULARY_SIZE)) 

    # At this point, the model has the same architecture as the trained one. 

    model = model.load(path) 
    return model

而且我的错误是这样的：

NotFoundError: Tensor name "Embedding_1/W" not found in checkpoint files model.save 
    [[Node: save_11/restore_slice_1 = RestoreSlice[dt=DT_FLOAT, preferred_shard=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_save_11/Const_0, save_11/restore_slice_1/tensor_name, save_11/restore_slice_1/shape_and_slice)]] 
Caused by op u'save_11/restore_slice_1', defined at: 
    File "/opt/local/bin/ipython", line 5, in <module> 
    start_ipython() 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/__init__.py", line 119, in start_ipython 
    return launch_new_instance(argv=argv, **kwargs) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/traitlets/config/application.py", line 658, in launch_instance 
    app.start() 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/terminal/ipapp.py", line 348, in start 
    self.shell.mainloop() 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/terminal/interactiveshell.py", line 440, in mainloop 
    self.interact() 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/terminal/interactiveshell.py", line 431, in interact 
    self.run_cell(code, store_history=True) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell 
    interactivity=interactivity, compiler=compiler, result=result) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2827, in run_ast_nodes 
    if self.run_code(code, result): 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code 
    exec(code_obj, self.user_global_ns, self.user_ns) 
    File "<ipython-input-7-2cfc4af80f36>", line 1, in <module> 
    stm_a.loadModelandVocabulary() 
    File "stm_a.py", line 42, in loadModelandVocabulary 
    model = buildNetwork(plh, dictionary_size=len(vocabulary_object.vocabulary_)) 
    File "stm_a.py", line 98, in buildNetwork 
    return tflearn.DNN(g, checkpoint_path = checkpoint_path) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tflearn/models/dnn.py", line 63, in __init__ 
    best_val_accuracy=best_val_accuracy) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tflearn/helpers/trainer.py", line 142, in __init__ 
    keep_checkpoint_every_n_hours=keep_checkpoint_every_n_hours) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tensorflow/python/training/saver.py", line 861, in __init__ 
    restore_sequentially=restore_sequentially) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tensorflow/python/training/saver.py", line 519, in build 
    filename_tensor, vars_to_save, restore_sequentially, reshape) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tensorflow/python/training/saver.py", line 272, in _AddRestoreOps 
    values = self.restore_op(filename_tensor, vs, preferred_shard) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tensorflow/python/training/saver.py", line 187, in restore_op 
    preferred_shard=preferred_shard) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tensorflow/python/ops/io_ops.py", line 203, in _restore_slice 
    preferred_shard, name=name) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tensorflow/python/ops/gen_io_ops.py", line 359, in _restore_slice 
    preferred_shard=preferred_shard, name=name) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tensorflow/python/framework/op_def_library.py", line 703, in apply_op 
    op_def=op_def) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tensorflow/python/framework/ops.py", line 2317, in create_op 
    original_op=self._default_original_op, op_def=op_def) 
    File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/site-python/tensorflow/python/framework/ops.py", line 1239, in __init__ 
    self._traceback = _extract_stack()

我看到的东西是错误与我的如下输入层我埋层。我使用这些（默认）该层的参数：trainable=True, restore=True, reuse=False。

我对此很陌生，所以我不知道如何正确调试TFLearn和Tensorflow错误。

任何帮助表示赞赏！

来源

2016-12-10 ant0nisk

你能链接到你用来加载的代码和模式的代码本身吗？ –

当然我推在Github整个事情（与训练模型）：https://github.com/ant0nisk/Sentiment-Analysis-with-Deep-Learning – ant0nisk

您正在使用什么TensorFlow和Python的版本？ –

我不确定你的问题是什么，但model.load()不返回任何东西。下面是从tflearn用法示例：

model = DNN(network) 
model.load('model.tflearn') 
model.predict(X)

你分配到modelNone。

来源

2016-12-10 20:29:28

TFLearn在加载训练过的模型时抛出错误

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