test tractate

src/main_portrait.py

@@ -10,8 +10,8 @@ from models.esmm.fe import device_fe, diary_fe, tractate_fe
 from models.esmm.tractate_model import model_predict_tractate
 from utils.cache import redis_client2
 from utils.grey import recommed_service_category_device_id_by_tail
-from utils.portrait import (user_portrait_tag3_get_candidate_dict, user_portrait_tag3_get_candidate_unread_list,
-                            user_portrait_tag3_write_ctcvr_data)
+from utils.portrait import (get_user_portrait_tag3_read_v2, user_portrait_tag3_get_candidate_dict,
+                            user_portrait_tag3_get_candidate_unread_list, user_portrait_tag3_write_ctcvr_data)
 
 
 def user_portrait_scan_info(device_dict, diary_dict, predict_fn, tail_number):
@@ -64,6 +64,9 @@ def main():
     diary_save_path = "/home/gmuser/data/models/diary/1596083349"
     diary_predict_fn = tf.contrib.predictor.from_saved_model(diary_save_path)
 
+    tractate_save_path = "/home/gmuser/data/models/tractate/1596092061"
+    tractate_predict_fn = tf.contrib.predictor.from_saved_model(tractate_save_path)
+
     # device_id = "androidid_a25a1129c0b38f7b"
     # offline_predict_diary(device_id, device_dict, diary_dict, diary_predict_fn)
 
@@ -71,8 +74,7 @@ def main():
     # print(len(res))
     # print(res[:10])
 
-    tail_number = sys.argv[1]
-    # "c", "d", "e", "f"
+    tail_number = sys.argv[1]  # "c", "d", "e", "f"
     user_portrait_scan_info(device_dict, diary_dict, diary_predict_fn, tail_number)
 
 

src/test.py

+import datetime
+import time
+
+import tensorflow as tf
+
+from models.esmm.fe import device_fe, diary_fe, tractate_fe
+from models.esmm.tractate_model import model_predict_tractate
+from utils.cache import redis_client2
+from utils.grey import recommed_service_category_device_id_by_tail
+from utils.portrait import (get_user_portrait_tag3_read_v2, user_portrait_tag3_get_candidate_dict,
+                            user_portrait_tag3_get_candidate_unread_list, user_portrait_tag3_write_ctcvr_data)
+
+if __name__ == "__main__":
+    time_begin = time.time()
+
+    device_id = "androidid_a25a1129c0b38f7b"
+
+    tractate_save_path = "/home/gmuser/data/models/tractate/1596092061"
+    tractate_predict_fn = tf.contrib.predictor.from_saved_model(tractate_save_path)
+
+    read_list, _ = get_user_portrait_tag3_read_v2(device_id, "tractate")
+    print(len(read_list))
+    print(read_list[:10])
+
+    res = user_portrait_tag3_get_candidate_unread_list(device_id, "tractate")
+    print(len(res))
+    print(res[:10])
+
+    res2 = user_portrait_tag3_get_candidate_dict(device_id, "tractate")
+    print(res2.keys())
+
+    total_time = (time.time() - time_begin) / 60
+    print("total cost {:.2f} mins at {}".format(total_time, datetime.datetime.now()))