try predict

src/models/esmm/tractate_model.py

@@ -46,15 +46,14 @@ def model_predict_tractate(device_id, tractate_ids, device_dict, tractate_dict,
 
         time_1 = timeit.default_timer()
         predictions = predict_fn({"examples": examples})
-        print(predictions)
-        # res_tuple = sorted(zip(tractate_ids_res, predictions["output"].tolist()), key=lambda x: x[1], reverse=True)
-        # res = []
-        # for (id, _) in res_tuple:
-        #     res.append(int(id))
-        # # print(res)
+        res_tuple = sorted(zip(tractate_ids_res, predictions["output"].tolist()), key=lambda x: x[1], reverse=True)
+        res = []
+        for (id, _) in res_tuple:
+            res.append(int(id))
+        # print(res)
         total_1 = (timeit.default_timer() - time_1)
         print("prediction cost {:.5f}s".format(total_1))
-        # return res
+        return res
     except Exception as e:
         print(e)
         # device_info, _, _ = device_tractate_fe(device_id, tractate_ids, device_dict, tractate_dict)