upate readme

README.md

@@ -14,7 +14,7 @@ This project need to work with [Workflow_parallel_frame_prediction project](http
 ```bash
 git clone -b master https://gitlab.version.fz-juelich.de/gong1/video_prediction_savp.git
 git clone -b master https://gitlab.version.fz-juelich.de/gong1/workflow_parallel_frame_prediction.git
-cd video_prediction_savp
+
 ```
 - Install TensorFlow >= 1.9 and dependencies from http://tensorflow.org/
 - Install other dependencies
@@ -28,14 +28,13 @@ pip install -r requirements.txt
 - For the best speed and experimental results, we recommend using cudnn version 7.3.0.29 and any tensorflow version >= 1.9 and <= 1.12. The final training loss is worse when using cudnn versions 7.3.1.20 or 7.4.1.5, compared to when using versions 7.3.0.29 and below.
 - Add the directories lpips-tensorflow and hickle (get from [Workflow project](https://gitlab.version.fz-juelich.de/gong1/workflow_parallel_frame_prediction) to the  `PATHONPATH `, e.g export PYTHONPATH=path/to/lpips-tensorflow
 
-
 ### Set-up on JUWELS
 
 - Set up env and install packages
 
 ```bash
-./env_setup/create_env.sh <user> <env_name>
-source <env_name>/bin/activate
+cd video_prediction_savp
+source env_setup/create_env.sh <dir_name> <env_name>
 ```
 
 ## Workflow by steps
@@ -73,7 +72,7 @@ python3 scripts/train_v2.py --input_dir <./data/exp_name> --dataset era5  --mode
 
 Example
 ```python
-python3 scripts/train_v2.py --input_dir ./data/era5_64_64_3_3t_norm --dataset era5  --model savp --model_hparams_dict hparams/kth/ours_savp/model_hparams.json --output_dir logs/era5_64_64_3_3t_norm/end_to_end
+python3 scripts/train_v2.py --input_dir ./data/era5_size_64_64_3_3t_norm --dataset era5  --model savp --model_hparams_dict hparams/kth/ours_savp/model_hparams.json --output_dir logs/era5_64_64_3_3t_norm/end_to_end
 ```
 ### Postprocessing