Download scripts/attach_cfg_norm_stats.py from myx160/rl-post-train-artifacts: direct link, hf CLI and curl.
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https://huggingface.co/datasets/myx160/rl-post-train-artifacts/resolve/main/scripts/attach_cfg_norm_stats.py
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hf download hf://datasets/myx160/rl-post-train-artifacts/scripts/attach_cfg_norm_stats.py
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curl -L -o attach_cfg_norm_stats.py https://huggingface.co/datasets/myx160/rl-post-train-artifacts/resolve/main/scripts/attach_cfg_norm_stats.py
3.22 kB
| #!/usr/bin/env python | |
| """Attach the frozen LIBERO norm stats to an RLinf CFG actor checkpoint. | |
| RLinf's training checkpoint writer stores DCP and full weights but does not | |
| copy the small OpenPI norm-statistics tree. This helper adds only that file, | |
| atomically and without duplicating the base model. | |
| """ | |
| from __future__ import annotations | |
| import argparse | |
| import hashlib | |
| import json | |
| import os | |
| import shutil | |
| from pathlib import Path | |
| PROJECT_ROOT = Path("/data/myx/RL_post_train").resolve() | |
| BASE_NORM_STATS = PROJECT_ROOT / "checkpoints/base/RLinf-Pi05-LIBERO-SFT/physical-intelligence/libero/norm_stats.json" | |
| def _sha256(path: Path) -> str: | |
| digest = hashlib.sha256() | |
| with path.open("rb") as handle: | |
| for chunk in iter(lambda: handle.read(1024 * 1024), b""): | |
| digest.update(chunk) | |
| return digest.hexdigest() | |
| def _resolve(raw: Path) -> Path: | |
| path = raw.expanduser() | |
| if not path.is_absolute(): | |
| path = PROJECT_ROOT / path | |
| path = path.resolve() | |
| try: | |
| path.relative_to(PROJECT_ROOT) | |
| except ValueError as exc: | |
| raise ValueError(f"checkpoint must remain under {PROJECT_ROOT}: {path}") from exc | |
| return path | |
| def main() -> int: | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument( | |
| "--checkpoint", | |
| type=Path, | |
| required=True, | |
| help="Actor checkpoint directory (the directory containing model_state_dict/).", | |
| ) | |
| args = parser.parse_args() | |
| actor_root = _resolve(args.checkpoint) | |
| if not actor_root.is_dir(): | |
| raise FileNotFoundError(f"actor checkpoint directory does not exist: {actor_root}") | |
| if not (actor_root / "model_state_dict" / "full_weights.pt").is_file(): | |
| raise FileNotFoundError( | |
| f"full_weights.pt is missing below actor checkpoint: {actor_root}" | |
| ) | |
| if not BASE_NORM_STATS.is_file(): | |
| raise FileNotFoundError(f"frozen base norm stats missing: {BASE_NORM_STATS}") | |
| source_hash = _sha256(BASE_NORM_STATS) | |
| destination = actor_root / "physical-intelligence/libero/norm_stats.json" | |
| destination.parent.mkdir(parents=True, exist_ok=True) | |
| if destination.exists(): | |
| destination_hash = _sha256(destination) | |
| if destination_hash != source_hash: | |
| raise RuntimeError( | |
| f"existing norm stats hash differs: {destination_hash} != {source_hash}" | |
| ) | |
| action = "already_present" | |
| else: | |
| temporary = destination.with_name( | |
| f".{destination.name}.tmp.{os.getpid()}" | |
| ) | |
| try: | |
| shutil.copyfile(BASE_NORM_STATS, temporary) | |
| os.replace(temporary, destination) | |
| finally: | |
| if temporary.exists(): | |
| temporary.unlink() | |
| action = "copied" | |
| print( | |
| json.dumps( | |
| { | |
| "ok": True, | |
| "action": action, | |
| "actor_root": str(actor_root), | |
| "norm_stats": str(destination), | |
| "sha256": source_hash, | |
| "bytes": destination.stat().st_size, | |
| }, | |
| ensure_ascii=False, | |
| sort_keys=True, | |
| ) | |
| ) | |
| return 0 | |
| if __name__ == "__main__": | |
| raise SystemExit(main()) | |