Buckets:
| print('import start') | |
| import os | |
| import pickle | |
| from pathlib import Path | |
| # These utilities must be part of submission repo | |
| from batteryswap_public.utils import make_submissions | |
| from batteryswap_public.interfaces import Planner | |
| # ensure classes that might be referenced in pickle is imported | |
| from batteryswap_example.train import * | |
| def pickle_loader(path : str): | |
| def load() -> Planner: | |
| with open(path, "rb") as f: | |
| return pickle.load(f) | |
| return load | |
| def main(): | |
| print('main start') | |
| # Load a trained model from repo | |
| default_planner_path = 'batteryswap_example/planners/best.pickle' | |
| planner_path = Path(os.environ.get('BATTERYSWAP_PLANNER_PATH', default_planner_path)) | |
| loader = pickle_loader(planner_path) | |
| # NOTE: On HuggingFace the dataset will be in /tmp/data | |
| dataset_path = Path(os.environ.get('BATTERYSWAP_DATASET_PATH', '/tmp/data')) | |
| splits = os.environ.get('BATTERYSWAP_SPLITS', 'public,private').split(',') | |
| make_submissions(loader, dataset_path=dataset_path, splits=splits) | |
| # NOTE: On HuggingFace the output must be submission.csv | |
| assert os.path.exists('submission.csv') | |
| if __name__ == '__main__': | |
| main() | |
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