update kpi ratio and chmod 775

fluid/PaddleNLP/text_matching_on_quora/_ce.py

@@ -7,11 +7,11 @@ from kpi import CostKpi
 from kpi import DurationKpi
 
 
-each_pass_duration_card1_kpi = DurationKpi('each_pass_duration_card1', 0.2, 0, actived=True)
-train_avg_cost_card1_kpi = CostKpi('train_avg_cost_card1', 0.2, 0)
+each_pass_duration_card1_kpi = DurationKpi('each_pass_duration_card1', 0.08, 0, actived=True)
+train_avg_cost_card1_kpi = CostKpi('train_avg_cost_card1', 0.08, 0)
 train_avg_acc_card1_kpi = CostKpi('train_avg_acc_card1', 0.02, 0)
-each_pass_duration_card4_kpi = DurationKpi('each_pass_duration_card4', 0.2, 0, actived=True)
-train_avg_cost_card4_kpi = CostKpi('train_avg_cost_card4', 0.2, 0)
+each_pass_duration_card4_kpi = DurationKpi('each_pass_duration_card4', 0.08, 0, actived=True)
+train_avg_cost_card4_kpi = CostKpi('train_avg_cost_card4', 0.08, 0)
 train_avg_acc_card4_kpi = CostKpi('train_avg_acc_card4', 0.02, 0)
 
 tracking_kpis = [

fluid/PaddleNLP/text_matching_on_quora/train_and_evaluate.py

@@ -34,6 +34,7 @@ parser = argparse.ArgumentParser(description=__doc__)
 parser.add_argument('--model_name',       type=str,   default='cdssmNet',                  help="Which model to train")
 parser.add_argument('--config',           type=str,   default='cdssm_base',       help="The global config setting")
 parser.add_argument('--enable_ce', action='store_true', help='If set, run the task with continuous evaluation logs.')
+parser.add_argument('--epoch_num', type=int, default=5, help='Number of GPU devices for ce')
 
 DATA_DIR = os.path.join(os.path.expanduser('~'), '.cache/paddle/dataset')
 
@@ -241,6 +242,10 @@ def main():
     args = parser.parse_args()
     global_config = configs.__dict__[args.config]()
 
+    # only for ce
+    if args.enable_ce:
+        global_config.epoch_num = args.epoch_num
+
     print("net_name: ", args.model_name)
     net = models.__dict__[args.model_name](global_config)