update kpi ratio and chmod 775

fluid/PaddleNLP/text_matching_on_quora/.run_ce.sh

@@ -6,9 +6,9 @@ export OMP_NUM_THREADS=1
 cudaid=${text_matching_on_quora:=0} # use 0-th card as default
 export CUDA_VISIBLE_DEVICES=$cudaid
 
-FLAGS_benchmark=true  python train_and_evaluate.py --model_name=cdssmNet --config=cdssm_base --enable_ce | python _ce.py
+FLAGS_benchmark=true  python train_and_evaluate.py --model_name=cdssmNet --config=cdssm_base --enable_ce --epoch_num=5 | python _ce.py
 
 cudaid=${text_matching_on_quora_m:=0,1,2,3} # use 0,1,2,3 card as default
 export CUDA_VISIBLE_DEVICES=$cudaid
 
-FLAGS_benchmark=true  python train_and_evaluate.py --model_name=cdssmNet --config=cdssm_base --enable_ce | python _ce.py
+FLAGS_benchmark=true  python train_and_evaluate.py --model_name=cdssmNet --config=cdssm_base --enable_ce --epoch_num=5 | python _ce.py

fluid/PaddleNLP/text_matching_on_quora/train_and_evaluate.py

@@ -34,7 +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')
+parser.add_argument('--epoch_num', type=int, help='Number of epoch')
 
 DATA_DIR = os.path.join(os.path.expanduser('~'), '.cache/paddle/dataset')
 
@@ -242,8 +242,7 @@ def main():
     args = parser.parse_args()
     global_config = configs.__dict__[args.config]()
 
-    # only for ce
-    if args.enable_ce:
+    if args.epoch_num != None:
         global_config.epoch_num = args.epoch_num
 
     print("net_name: ", args.model_name)