update function name

src/models/esmm/fe/tractate_fe.py

@@ -30,7 +30,7 @@ def read_csv_data(dataset_path):
     return tractate_df, click_df, conversion_df
 
 
-def get_tractate_from_redis():
+def get_tractate_dict_from_redis():
     """
     return: {tractate_id: {first_demands: [], is_pure_author: 1}}
     """

src/train_tractate.py

@@ -65,18 +65,18 @@ def main():
     predict_fn = tf.contrib.predictor.from_saved_model(save_path)
 
     device_dict = device_fe.get_device_dict_from_redis()
-    diary_dict = tractate_fe.get_tractate_dict_from_redis()
+    tractate_dict = tractate_fe.get_tractate_dict_from_redis()
 
     device_ids = list(device_dict.keys())[:20]
-    diary_ids = list(diary_dict.keys())
+    tractate_ids = list(tractate_dict.keys())
 
     print(device_dict(device_ids[0]), "\n")
-    print(diary_dict(diary_ids[0]), "\n")
+    print(tractate_dict(tractate_ids[0]), "\n")
 
     for i in range(5):
         time_1 = timeit.default_timer()
         res = model_predict_tractate(
-            random.sample(device_ids, 1)[0], random.sample(diary_ids, 200), device_dict, diary_dict, predict_fn)
+            random.sample(device_ids, 1)[0], random.sample(tractate_ids, 200), device_dict, tractate_dict, predict_fn)
         print(res[:10])
         total_1 = (timeit.default_timer() - time_1)
         print("total prediction cost {:.5f}s".format(total_1), "\n")