Merge pull request #1220 from kuke/act_ner_ce

Activate ce of sequence_tagging_for_ner

fluid/sequence_tagging_for_ner/_ce.py

@@ -7,9 +7,9 @@ from kpi import CostKpi, DurationKpi, AccKpi
 
 #### NOTE kpi.py should shared in models in some way!!!!
 
-train_acc_kpi = AccKpi('train_precision', 0.005, actived=False)
-test_acc_kpi = CostKpi('test_precision', 0.005, actived=False)
-train_duration_kpi = DurationKpi('train_duration', 0.05, actived=True)
+train_acc_kpi = AccKpi('train_precision', 0.005, 0, actived=True)
+test_acc_kpi = CostKpi('test_precision', 0.005, 0, actived=True)
+train_duration_kpi = DurationKpi('train_duration', 0.05, 0, actived=True)
 
 tracking_kpis = [
     train_acc_kpi,

fluid/sequence_tagging_for_ner/train.py

@@ -55,6 +55,9 @@ def main(train_data_file,
     word_dict_len = len(word_dict)
     label_dict_len = len(label_dict)
 
+    if "CE_MODE_X" in os.environ:
+        fluid.default_startup_program().random_seed = 110
+
     avg_cost, feature_out, word, mark, target = ner_net(
         word_dict_len, label_dict_len, parallel)
 
@@ -98,8 +101,6 @@ def main(train_data_file,
     feeder = fluid.DataFeeder(feed_list=[word, mark, target], place=place)
     exe = fluid.Executor(place)
 
-    if "CE_MODE_X" in os.environ:
-        fluid.default_startup_program().random_seed = 110
     exe.run(fluid.default_startup_program())
 
     embedding_name = 'emb'