update offline predict number

src/main_portrait.py

 import datetime
-import random
 import sys
 import time
 
@@ -10,7 +9,7 @@ from models.esmm.fe import device_fe, diary_fe, tractate_fe
 from models.esmm.tractate_model import model_predict_tractate
 from utils.cache import get_essm_model_save_path, redis_client2
 from utils.grey import recommed_service_category_device_id_by_tail
-from utils.portrait import (get_unread_cpc_diary_list, get_user_portrait_tag3_read_v2, user_portrait_tag3_get_candidate_dict,
+from utils.portrait import (get_unread_cpc_diary_list, user_portrait_tag3_get_candidate_dict,
                             user_portrait_tag3_get_candidate_unread_list, user_portrait_tag3_get_ctcvr_queue,
                             user_portrait_tag3_write_cpc_ctcvr_data, user_portrait_tag3_write_ctcvr_data)
 
@@ -19,6 +18,7 @@ def user_portrait_scan_info(device_dict, diary_dict, tractate_dict, diary_predic
     try:
         round = 0
         all_count = 0
+        predict_size = 500
         keys = "doris:user_portrait:tag3:device_id:*"
         cur, results = redis_client2.scan(0, keys, 3000)
         while cur != 0:
@@ -33,9 +33,9 @@ def user_portrait_scan_info(device_dict, diary_dict, tractate_dict, diary_predic
                     if (user_portrait_tag3_get_candidate_dict(device_id, "diary")):
                         all_count += 1
                         print(str(all_count) + ": " + device_id)
-                        offline_predict_diary(device_id, device_dict, diary_dict, diary_predict_fn, size=200)
+                        offline_predict_diary(device_id, device_dict, diary_dict, diary_predict_fn, size=predict_size)
                         print("---------------------")
-                        offline_predict_tractate(device_id, device_dict, tractate_dict, tractate_predict_fn, size=200)
+                        offline_predict_tractate(device_id, device_dict, tractate_dict, tractate_predict_fn, size=predict_size)
                         print("=========================================\n")
 
         print("all count: " + str(all_count))

src/models/esmm/model.py

-import json
-import timeit
-
 import tensorflow as tf
 from tensorflow import feature_column as fc
 from tensorflow.python.estimator.canned import head as head_lib
 from tensorflow.python.ops.losses import losses
 
-from .fe.diary_fe import device_diary_fe
-from .utils import common_elements, nth_element
-
 
 def build_deep_layer(net, params):
     for num_hidden_units in params["hidden_units"]: