diff --git a/Zam347_scripts/generate_era5.sh b/Zam347_scripts/generate_era5.sh
index 3ee897b0cf9cc6232575d370e85624496684e66e..97a07d280248d09a754aa69450c883dc11375387 100755
--- a/Zam347_scripts/generate_era5.sh
+++ b/Zam347_scripts/generate_era5.sh
@@ -2,9 +2,9 @@
 
 
 python -u ../scripts/generate_transfer_learning_finetune.py \
---input_dir /home/${USER}/preprocessedData/era5-Y2015toY2017M01to12-128x160-74d00N71d00E-T_MSL_gph500/tfrecords/  \
+--input_dir /home/${USER}/preprocessedData/era5-Y2015toY2017M01to12-128x160-74d00N71d00E-T_MSL_gph500/tfrecords  \
 --dataset_hparams sequence_length=20 --checkpoint  /home/${USER}/models/era5-Y2015toY2017M01to12-128x160-74d00N71d00E-T_MSL_gph500/ours_savp \
---mode test --results_dir /home/${USER}/results/era5-Y2017M01to12-64x64-50d00N11d50E-T_T_T \
---batch_size 4 --dataset era5   > generate_era5-out.out
+--mode test --results_dir /home/${USER}/results/era5-Y2015toY2017M01to12-128x160-74d00N71d00E-T_MSL_gph500 \
+--batch_size 2 --dataset era5   > generate_era5-out.out
 
 #srun  python scripts/train.py --input_dir data/era5 --dataset era5  --model savp --model_hparams_dict hparams/kth/ours_savp/model_hparams.json --output_dir logs/era5/ours_savp
diff --git a/scripts/generate_transfer_learning_finetune.py b/scripts/generate_transfer_learning_finetune.py
index c3388d0983060db7ac2d382a79b1f86d72c34894..662a415d69ca5f8cf8cdd5e9c800a1403976a551 100644
--- a/scripts/generate_transfer_learning_finetune.py
+++ b/scripts/generate_transfer_learning_finetune.py
@@ -91,7 +91,10 @@ def main():
         tf.set_random_seed(args.seed)
         np.random.seed(args.seed)
         random.seed(args.seed)
-
+    #Bing:20200518 
+    input_dir = args.input_dir
+    temporal_dir = os.path.split(input_dir)[0] + "/hickle/splits/"
+    print ("temporal_dir:",temporal_dir)
     args.results_gif_dir = args.results_gif_dir or args.results_dir
     args.results_png_dir = args.results_png_dir or args.results_dir
     dataset_hparams_dict = {}
@@ -197,12 +200,13 @@ def main():
     persistent_images_all = []
     input_images_all = []
     #Bing:20201417
-    test_temporal_pkl = pickle.load(open("/p/scratch/deepacf/video_prediction_shared_folder/preprocessedData/era5-Y2017M01to12-64x64-50d00N11d50E-T_T_T/hickle/splits/T_test.pkl","rb"))
+    print ("temporal_dir:",temporal_dir)
+    test_temporal_pkl = pickle.load(open(os.path.join(temporal_dir,"T_test.pkl"),"rb"))
     #val_temporal_pkl = pickle.load(open("/p/scratch/deepacf/video_prediction_shared_folder/preprocessedData/era5-Y2017M01to12-64x64-50d00N11d50E-T_T_T/hickle/splits/T_val.pkl","rb"))
     print("test temporal_pkl file looks like folowing", test_temporal_pkl)
 
     #X_val = hickle.load("/p/scratch/deepacf/video_prediction_shared_folder/preprocessedData/era5-Y2017M01to12-64x64-50d00N11d50E-T_T_T/hickle/splits/X_val.hkl")
-    X_test = hickle.load("/p/scratch/deepacf/video_prediction_shared_folder/preprocessedData/era5-Y2017M01to12-64x64-50d00N11d50E-T_T_T/hickle/splits/X_test.hkl")
+    X_test = hickle.load(os.path.join(temporal_dir,"X_test.hkl"))
     is_first=True