Merge pull request #7 from erayon/master

encode_pickle_error

code/predict.py

@@ -93,7 +93,8 @@ def predict(files, model_path, output_dir, format, use_lstm=True):
     # Load model
     #if use_lstm==False: 
     with open(model_path, 'rb') as f:
-        model = pickle.load(f)
+    	model = pickle.load(f,encoding = 'latin1')
+
 
     if model._use_lstm:
         import helper_dataset as hd
@@ -114,7 +115,7 @@ def predict(files, model_path, output_dir, format, use_lstm=True):
            note=Document(txt)
            tokenized_sents  = note.getTokenizedSentences()
            updating_notes+=tokenized_sents
-        #print (updating_notes)
+        print (updating_notes)
         
         
         fictional_labels= copy.deepcopy(tokenized_sents)
@@ -135,18 +136,19 @@ def predict(files, model_path, output_dir, format, use_lstm=True):
         parameters['Feature_vector_length']=dataset.feature_vector_size
         parameters['use_features_before_final_lstm']=False       
         dataset.update_dataset("", ['deploy'],Datasets_tokens,Datasets_labels)
-        '''
         
-       # model._pretrained_dataset=dataset
         
-       # model_LSTM=entity_model.EntityLSTM(dataset,parameters)
-       # model._current_model=model_LSTM
-        #._current_model
+        model._pretrained_dataset=dataset
+        
+        model_LSTM=entity_model.EntityLSTM(dataset,parameters)
+        model._current_model=model_LSTM
+        ._current_model
         
+        '''
 
         print ("END TEST")
         #exit()
-       # model.parameters=None
+        #model.parameters=None
 
     # Tell user if not predicting
     if not files: