| | from modal import App,Image,gpu,Volume,Image |
| | import os |
| | from dotenv import load_dotenv |
| | _ = load_dotenv('./.env') |
| |
|
| | app = App(f'PreDiff Sample Run') |
| |
|
| | image = ( |
| | Image.micromamba(python_version='3.10.12') |
| | .apt_install("awscli") |
| | .pip_install_from_requirements( |
| | requirements_txt='requirements.txt' |
| | ) |
| | .add_local_dir( |
| | local_path=os.path.abspath('./'), |
| | remote_path='/root', |
| | copy=True, |
| | ignore= [ |
| | '__pycache__/*', |
| | './.venv/*', |
| | './data/*', |
| | './pretrained_weights/*' |
| | ] |
| | ) |
| | .env({ |
| | "WANDB_API_KEY": os.getenv('WANDB_API_KEY'), |
| | "WANDB_ENTITY": os.getenv('WANDB_ENTITY'), |
| | 'WANDB_PROJECT':os.getenv('WANDB_PROJECT') |
| | }) |
| | ) |
| |
|
| | @app.function( |
| | image=image, |
| | gpu = 'T4', |
| | timeout = 86400, |
| | retries = 0, |
| | volumes = { |
| | "/root/sevir_data": Volume.from_name("prediff_vil_precipitation_data"), |
| | "/root/pretrained_weights": Volume.from_name("prediff_pretrained_weights"), |
| | "/root/logs": Volume.from_name('prediff_logs') |
| | } |
| | ) |
| | def entry(): |
| | import os |
| | |
| | |
| | os.system('python -m scripts.train_vae.train_vae_sevirlr --cfg ./scripts/train_vae/cfg.yaml') |