update

demo.py

@@ -1,11 +1,14 @@
 # import the necessary packages
+import os
 import random
 
 import jieba
 import pandas as pd
+import torch
 
+from config import device, save_folder, test_a_folder, test_a_filename
 from data_gen import parse_user_reviews, batch2TrainData
-from utils import *
+from utils import Lang, encode_text
 
 if __name__ == '__main__':
     voc = Lang('data/WORDMAP.json')
@@ -24,6 +27,8 @@
     # Set dropout layers to eval mode
     encoder.eval()
 
+    filename = os.path.join(test_a_folder, test_a_filename)
+    user_reviews = pd.read_csv(filename)
     samples = parse_user_reviews('test_a')
 
     samples = random.sample(samples, 10)

train.py

@@ -1,10 +1,15 @@
+import time
+
 import numpy as np
+import torch
 from torch import nn
 from torch import optim
 
+from config import device, label_names, print_every, hidden_size, encoder_n_layers, dropout, learning_rate, start_epoch, \
+    epochs
 from data_gen import SaDataset
 from models import EncoderRNN
-from utils import *
+from utils import AverageMeter, ExpoAverageMeter, accuracy, Lang, timestamp, adjust_learning_rate, save_checkpoint
 
 
 def train(epoch, train_data, encoder, optimizer):