HCAI-Lab/w2-consensus-deepdive-unlearning-artifacts / social-data-attribution-w2 /src /data_attribution /attribution /influence_test.py
| from pathlib import Path | |
| import torch | |
| from data_attribution.attribution.index import _import_attributor | |
| def main(): | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| Attributor = _import_attributor() | |
| print("before index attributor", flush=True) | |
| Attributor( | |
| Path("runs/data_small"), | |
| device=device, | |
| unit_norm=True, | |
| ) | |
| print("after index attributor", flush=True) | |
| if __name__ == "__main__": | |
| main() | |
Xet Storage Details
- Size:
- 458 Bytes
- Xet hash:
- c06609ad716311cf661142bf566ecf7ba82bdb85bdca58468e3e5a07695c5765
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.