- Create conda environment and install all packages from
requirements.txt
conda create --name <environment_name> --file requirements.txt
conda activate <environment_name>
- Download datasets for Darcy Flow released by Li et al. 2021 [Follow this google drive link]
- Download datasets for Navier-Stokes from this link.
All bash scripts used for training and evaluating models on Darcy flow are located at darcy_flow/scripts
.
First, update the following variables in darcy_flow/configs/config.yml
and in the script, if necessary:
data_base_path
: path to datasetmodel_base_path
: path to folder to store checkpoints
Command to train FNO-DEQ would be bash scripts/run_deq.sh
.
Similar commands can be used to train other models. Refer to the following table choose an appropriate script:
Model | File |
---|---|
FNO | run_non_wt_no_inj.sh |
FNO++ | run_non_wt.sh |
FNO-WT | run_wt.sh |
FNO-DEQ | run_deq.sh |
To evaluate with a pretrained checkpoint, set train=False
in the script, and set ckpt
to the pretrained checkpoint in config.
Note: wandb logging is disabled by default. You can enable it by setting use_wandb=True
in the scripts.
All bash scripts used for training and evaluating models on Darcy flow are located at steady_state_navier_stokes/scripts
.
First, update the following variables in steady_state_navier_stokes/configs/config.yml
and in the script, if necessary:
data_base_path
: path to datasetmodel_base_path
: path to folder to store checkpoints
Command to train FNO-DEQ would be bash scripts/run_deq.sh
.
Please use the following scripts to train models:
Model | File |
---|---|
FNO | run_non_wt_no_inj.sh |
FNO++ | run_non_wt.sh |
FNO-WT | run_wt.sh |
FNO-DEQ | run_deq.sh |
To evaluate with a pretrained checkpoint, set train=False
in the script, and set ckpt
to the pretrained checkpoint in config.