update

recommend.py

@@ -582,7 +582,7 @@ def video_old_recommend(request_id, mid, uid, size, top_K, flow_pool_P, app_type
     #print(rank_result)
 
     result['rankResult'] = rank_result
-    result['flow_recall_num'] = flow_result
+    result['flow_num'] = flow_result
     result['rankTime'] = (time.time() - start_rank) * 1000
 
 

video_rank.py

@@ -657,8 +657,8 @@ def video_new_rank2(data, size, top_K, flow_pool_P, ab_code, flowConfig=None):
     if flowConfig == "1" and len(rov_recall_rank)>0:
         for recall_item in rank_result:
             flow_recall_name  = recall_item.get("flowPool", '')
-            print("recall_item:", recall_item)
-            print("flow_recall_name:", flow_recall_name)
+            #print("recall_item:", recall_item)
+            #print("flow_recall_name:", flow_recall_name)
             if flow_recall_name is not None and flow_recall_name.find("#") > -1:
                 flow_result = flow_result + 1
         if flow_result > 0:
@@ -666,7 +666,7 @@ def video_new_rank2(data, size, top_K, flow_pool_P, ab_code, flowConfig=None):
                 rank_result.append(rov_recall_rank[0])
             elif len(flow_recall_rank) > 0:
                 rank_result.append(flow_recall_rank[0])
-        print("flow_result:", flow_result)
+        #print("flow_result:", flow_result)
     else:
         # 按概率 p 及score排序获取 size - k 个视频
         i = 0
@@ -806,7 +806,7 @@ def video_sanke_rank(data, size, top_K, flow_pool_P, ab_Code='', exp_config=None
                 rank_result.append(rov_recall_rank[0])
             elif len(flow_recall_rank)>0:
                 rank_result.append(flow_recall_rank[0])
-        print("flow_result:", flow_result)
+        #print("flow_result:", flow_result)
     else:
         # 按概率 p 及score排序获取 size - k 个视频
         i = 0