- In python >= 3.6, make sure to add the root directory to the PYTHONPATH`, e.g. `export PYTHONPATH=path/to/video_prediction_savp`.
- 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.
- 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
- 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
- You may need install packages by pip on JUWELS/JURECA, followed the installation instruction from [Workflow project](https://gitlab.version.fz-juelich.de/gong1/workflow_parallel_frame_prediction)
### Download data
### Download data
- Download the ERA5 data (.hkl) from the output of DataPreprocess in the [Workflow project](https://gitlab.version.fz-juelich.de/gong1/workflow_parallel_frame_prediction)
- Download the ERA5 data (.hkl) from the output of DataPreprocess in the [Workflow project](https://gitlab.version.fz-juelich.de/gong1/workflow_parallel_frame_prediction)
