add printer

src/main.py

@@ -92,7 +92,7 @@ def main():
     device_ids = list(device_dict.keys())[:20]
     diary_ids = list(diary_dict.keys())
 
-    for i in range(5):
+    for i in range(2):
         time_1 = timeit.default_timer()
         model_predict2(random.sample(device_ids, 1)[0], random.sample(diary_ids, 200), device_dict, diary_dict, predict_fn)
         total_1 = (timeit.default_timer() - time_1)

src/models/esmm/model.py

@@ -129,39 +129,11 @@ def model_predict2(device_id, diary_ids, device_dict, diary_dict, predict_fn):
 
     time_1 = timeit.default_timer()
     predictions = predict_fn({"examples": examples})
+    diary_ids = []
+    for i in diary_lst:
+        diary_ids.append(i.get("card_id", "-1"))
+    print(predictions)
+    print(diary_ids)
     total_1 = (timeit.default_timer() - time_1)
     print("prediction cost {:.5f}s".format(total_1))
     return predictions
-
-
-# def model_predict(inputs, predict_fn):
-#     time_1 = timeit.default_timer()
-#     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"
-#     ]
-#     float_columns = ["one_ctr", "three_ctr", "seven_ctr", "fifteen_ctr"]
-#     examples = []
-#     for index, row in inputs.iterrows():
-#         features = {}
-#         for col, value in row.iteritems():
-#             if col in ["click_label", "conversion_label"]:
-#                 pass
-#             elif col in int_columns:
-#                 features[col] = _int64_feature(int(value))
-#             elif col in float_columns:
-#                 features[col] = _float_feature(float(value))
-#             else:
-#                 features[col] = _bytes_feature(str(value).encode(encoding="utf-8"))
-#         example = tf.train.Example(features=tf.train.Features(feature=features))
-#         examples.append(example.SerializeToString())
-#     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})
-#     total_1 = (timeit.default_timer() - time_1)
-#     print("prediction cost {:.5f}s".format(total_1))
-#     # print(predictions)
-#     # TODO get the diary ids
-#     return predictions