Update app.py

app.py

@@ -34,10 +34,10 @@ def f1(y_true, y_pred):
 def accuracy(y_true, y_pred):
     return K.mean(K.equal(y_true, K.round(y_pred)), axis=1)
 
-with open('tokenizer.json', 'r', encoding='utf-8') as f:
-    tokenizer_config = f.read()
+# with open('tokenizer.json', 'r', encoding='utf-8') as f:
+#     tokenizer_config = f.read()
 
-tokenizer = tokenizer_from_json(tokenizer_config)
+# tokenizer = tokenizer_from_json(tokenizer_config)
 
 model = tf.keras.models.load_model("sentimentality.h5", custom_objects={'f1':f1, 'recall': recall, 'precision': precision, 'accuracy':accuracy})
 
@@ -50,7 +50,7 @@ def get_sentiment(text):
     text = text.split()
     text = [stemmer.lemmatize(word) for word in text]
     text = ' '.join(text)
-    text = tokenizer.texts_to_sequences([text])[0]
+    # text = tokenizer.texts_to_sequences([text])[0]
     text += [0] * (30 - len(text))
     text = np.array(text).reshape(-1, 30)
     x = model.predict(text).tolist()[0][0]