social-data-attribution-w2/scripts/unlearning/cleanup_truncated.py

#!/usr/bin/env python3
"""Delete faithful multiseed dirs whose latest checkpoint is truncated/incomplete
(adapter_model.safetensors < 30MB or missing adapter_config.json) so they get re-trained."""

from pathlib import Path
import shutil

MS = Path.home() / "scratch/n16_selectivity/multiseed"
GOOD_MIN = 30_000_000  # complete rank-8 LoRA adapter is ~33.6MB
deleted = []
for d in sorted(MS.glob("faithful_*")):
    if not d.is_dir():
        continue
    cks = sorted(
        d.glob("checkpoint-*"),
        key=lambda c: (
            int(c.name.split("-")[-1]) if c.name.split("-")[-1].isdigit() else 0
        ),
    )
    if not cks:
        continue
    latest = cks[-1]
    model = latest / "adapter_model.safetensors"
    cfg = latest / "adapter_config.json"
    ok = model.exists() and model.stat().st_size >= GOOD_MIN and cfg.exists()
    if not ok:
        shutil.rmtree(d)
        deleted.append(d.name)
print(f"deleted {len(deleted)} truncated/incomplete dirs:")
for x in deleted:
    print("  ", x)