Update app.py

app.py

@@ -15,10 +15,10 @@ from underthesea import word_tokenize
 
 #from phoBERT import BERT_predict
 
-#Load tokenizer
-# fp = Path(__file__).with_name('tokenizer.pkl')
-# with open(fp,mode="rb") as f:
-#     tokenizer = pickle.load(f)
+Load tokenizer
+fp = Path(__file__).with_name('tokenizer.pkl')
+with open(fp,mode="rb") as f:
+    tokenizer = pickle.load(f)
 
 #Load LSTM
 fp = Path(__file__).with_name('lstm_model.h5')
@@ -40,7 +40,7 @@ def tokenizer_pad(tokenizer,comment_text,max_length=200):
     return padded_sequences
 
 def LSTM_predict(x):
-    #x = tokenizer_pad(tokenizer=tokenizer,comment_text=x)
+    x = tokenizer_pad(tokenizer=tokenizer,comment_text=x)
 
     pred_proba = LSTM_model.predict(x)[0]
 
@@ -51,7 +51,7 @@ def LSTM_predict(x):
     return pred_proba
 
 def GRU_predict(x):
-    #x = tokenizer_pad(tokenizer=tokenizer,comment_text=x)
+    x = tokenizer_pad(tokenizer=tokenizer,comment_text=x)
 
     
     pred_proba = GRU_model.predict(x)[0]
@@ -93,16 +93,3 @@ def judge(x):
     result.append((result_lstm[i]+result_gru[i])/2)
   
   return (result)
-
-
-# if __name__ == "__main__":
-#   #  print("Loading")
-#   #  while(True):
-#   #   string = input("\nMời nhập văn bản: ")
-#   #   os.system('cls')
-#   #   print(f"Văn bản đã nhập: {string}")
-#   #   judge(string)
-#   interface = gr.Interface(fn=judge,
-#                          inputs=gr.Textbox(lines=2, placeholder='Please write something', label="Input Text"),
-#                         outputs=['text','plot','text'])
-#   interface.launch()