TensorFlow: Cant Belastung trainiert Modell

Question

ich zu trainieren bin versucht, speichern und ein tensorflow Modell laden tflearn

 # Building convolutional network 

     network = input_data(shape=[None, imageSize, imageSize, 1], name='input') 
     network = conv_2d(network, imageSize, self.windowSize, activation='relu', regularizer="L2") 
     network = max_pool_2d(network, 2) 
     network = local_response_normalization(network) 
     network = conv_2d(network, imageSize * 2, self.windowSize, activation='relu', regularizer="L2") 
     network = max_pool_2d(network, 2) 
     network = local_response_normalization(network) 
     network = fully_connected(network, (dim4 * dim4) * (imageSize * 2), activation='tanh') 
     network = dropout(network, keep) 
     network = fully_connected(network, (dim4 * dim4) * (imageSize * 2), activation='tanh') 
     network = dropout(network, keep) 
     network = fully_connected(network, n_classes, activation='softmax') 
     network = regression(network, optimizer='adam', learning_rate=self.learningRate, 
           loss='categorical_crossentropy', name='target') 

     model = tflearn.DNN(network, tensorboard_verbose=0, tensorboard_dir='some/dir') 
     model.fit(

      {'input': np.array(myData.train_x).reshape(-1, self.imageSize, self.imageSize, 1)}, {'target': myData.train_y}, n_epoch=self.epochs, 

      validation_set=(
       {'input': np.array(myData.test_x).reshape(-1, self.imageSize, self.imageSize, 1)}, 
      {'target': myData.test_y}), 
     snapshot_step=100, show_metric=True, run_id='convnet') 
     model.save("some/path/model") 

Dieses Teil funktioniert mit. nächste, ich tue

 model_path = "some/path/model.meta" 

     if os.path.exists(model_path): 
      model.load(model_path) 
     else : 
      return "need to train the model" 

     prediction = self.model.predict([<some_input>]) 
     print(str(prediction)) 
     return prediction 

dies nicht gelingt bei model.load(model_path). Ich erhalte die folgenden Fehler

DataLossError (see above for traceback): Unable to open table file some/path/model.meta: Data loss: not an sstable (bad magic number): perhaps your file is in a different file format and you need to use a different restore operator? 
    [[Node: save_5/RestoreV2_4 = RestoreV2[dtypes=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_save_5/Const_0_0, save_5/RestoreV2_4/tensor_names, save_5/RestoreV2_4/shape_and_slices)]] 
Caused by op 'save_5/RestoreV2_4', defined at: 

verfolgen, was von

Data loss: not an sstable (bad magic number): perhaps your file is in a different file format and you need to use a different restore operator? 

gemeint ist, kann ich sehen, dass das Modell in die Tat richtig gespeichert und ist nicht eine leere Datei. Warum kann ich es nicht laden?

Versionsinformationen

tensorflow==1.4.0 
tensorflow-tensorboard==0.4.0rc2 
tflearn==0.3.2 
Python 3.6.3 :: Anaconda, Inc. 

Answer 1

ANTWORT:

Wie in den Kommentaren diskutiert, Der Weg Sie die Variablen speichern zu müssen „.ckpt“ Dateinamen enthalten.

ähnlich Wiederherstellung sollte