diff --git a/README.md b/README.md index a91680a084ba696cbde84a73c1a20b003c495976..84c1664c21164a8130e77990d5f947bdbb5cdda7 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ This project aims to adopt the GAN-based architectures, which original proposed - Python 3 - CPU or NVIDIA GPU + CUDA CuDNN -### Installation +### Installation - Clone this repo: ```bash git clone -b master https://gitlab.version.fz-juelich.de/gong1/video_prediction_savp.git @@ -21,6 +21,17 @@ cd Video_Prediction_SAVP pip install -r requirements.txt ``` +###Set-up on JUWELS + +- Set up env and install packages + +```bash +cd env_setup +./create_env.sh <USER_FOLDER> +``` + + + ### Miscellaneous installation considerations - In python >= 3.6, make sure to add the root directory to the PYTHONPATH`, e.g. `export PYTHONPATH=path/to/video_prediction_savp`. - 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. @@ -38,7 +49,6 @@ bash data/download_and_preprocess_dataset_era5.sh --data era5 --input_dir /split python scripts/train_v2.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 ``` - ### Model Evaluation 