Python Requirements

• pyyaml
• torch
• h5py
• tensorboard
• tqdm
• pytest

Begin working

• clone the repository
• install the requirements
• download the raw / prepared data, (optional models and data sets for 2nd stage) and set the paths in paths.yaml (see later)

Training a 1st stage model (1HP-NN):

• run main.py

  python main.py --dataset NAME_OF_DATASET
  

Infer a 1st stage model:

• run main.py:

  python main.py --dataset NAME_OF_DATASET --case test --model PATH_TO_MODEL (after "runs/")
  
  optional arguments:
  --inputs: make sure, they are the same as in the model (default `gksi`)
  --visualize: visualize the results (default `False`)
  

Training a 2nd stage model (2HP-NN):

• for running a 2HP-NN you need the prepared 2HP-dataset in datasets_prepared_dir_2hp

• for preparing 2HP-NN: expects that 1HP-NN exists and trained on; for 2HP-NN (including preparation) run main.py with the following arguments:

  python main.py --dataset NAME_OF_DATASET --case_2hp True --model PATH_TO_1HPNN_MODEL (after "runs/") --inputs INPUTS (rather preparation case from 1HP-NN)
  

  more information on required arguments: --inputs: make sure, they are the same as in the model (default gksi) + the number of datapoints (e.g. gksi_1000dp)

  optional arguments: --visualize: visualize the results (default False) --case: test, train or finetune (default train)

#TODO

Infer a 2nd stage model:

Exemplary paths.yaml file:

```
default_raw_dir: /scratch/sgs/pelzerja/datasets # where the raw 1st stage data is stored
datasets_prepared_dir: /home/pelzerja/pelzerja/test_nn/datasets_prepared/1HP_NN # where the prepared 1st stage data is stored
datasets_raw_domain_dir: /scratch/sgs/pelzerja/datasets/2hps_demonstrator_copy_of_local
datasets_prepared_domain_dir: /home/pelzerja/pelzerja/test_nn/datasets_prepared/2HP_domain
prepared_1hp_best_models_and_data_dir: /home/pelzerja/pelzerja/test_nn/1HP_NN_preparation_BEST_models_and_data
models_2hp_dir: /home/pelzerja/pelzerja/test_nn/1HP_NN/runs
datasets_prepared_dir_2hp: /home/pelzerja/pelzerja/test_nn/datasets_prepared/2HP_NN
```

GPU support

• if you want to use the GPU, you need to install pflotran with cuda support

• check nvidia-smi for the available gpus and cuda version

• export CUDA_VISIBLE_DEVICES=<gpu_id> (e.g. 0)

• if the gpu is not found after suspension, try

  sudo rmmod nvidia_uvm sudo modprobe nvidia_uvm

  if it does not help, you have to reboot

important commits

• directly after paper submission (Oct. '23): cdc41426184756b9b1870e5c0f52d399bee0fae0
• after clean up, one month after paper submission (Oct. '23): c8da3da