update printer

src/main_portrait.py

@@ -47,7 +47,6 @@ def main():
 
     device_dict = get_device_dict_from_redis()
     diary_dict = get_diary_dict_from_redis()
-    print(list(diary_dict.keys())[:20])
     print("redis data: " + str(len(device_dict)) + " " + str(len(diary_dict)))
 
     save_path = "/home/gmuser/data/models/1595501144"

src/models/esmm/model.py

@@ -97,10 +97,7 @@ def _bytes_feature(value):
 def model_predict_diary(device_id, diary_ids, device_dict, diary_dict, predict_fn):
     time_1 = timeit.default_timer()
     device_info, diary_lst, diary_ids_res = device_diary_fe(device_id, diary_ids, device_dict, diary_dict)
-    print("device_info: ")
-    print(device_info)
-    print(diary_lst)
-    print(diary_ids_res)
+    print("predict check: " + str(len(diary_lst)) + " " + str(len(diary_ids_res)))
     int_columns = [
         "active_type", "active_days", "card_id", "is_pure_author", "is_have_reply", "is_have_pure_reply", "content_level",
         "topic_num", "favor_num", "vote_num"
@@ -117,8 +114,6 @@ def model_predict_diary(device_id, diary_ids, device_dict, diary_dict, predict_f
         tmp = {}
         tmp.update(device_info)
         tmp.update(diary_info)
-        # TODO
-        print(tmp)
         features = {}
         for col in int_columns:
             features[col] = _int64_feature(int(tmp[col]))
@@ -129,15 +124,11 @@ def model_predict_diary(device_id, diary_ids, device_dict, diary_dict, predict_f
         example = tf.train.Example(features=tf.train.Features(feature=features))
         examples.append(example.SerializeToString())
 
-    # TODO
-    print(examples)
     total_1 = (timeit.default_timer() - time_1)
     print("make example cost {:.5f}s".format(total_1))
 
     time_1 = timeit.default_timer()
     predictions = predict_fn({"examples": examples})
-    # TODO
-    print(predictions)
     res_tuple = sorted(zip(diary_ids_res, predictions["output"].tolist()), key=lambda x: x[1], reverse=True)
     res = []
     for (id, _) in res_tuple: