#!/usr/bin/env python3 """subset_lerobot.py — download the first N episodes of a LeRobot v2.1 dataset + patch its meta, so a big dataset (e.g. abc-teleop = 6,586 files) becomes a tiny, fast, still-valid local dataset for a minimal mixture experiment. LeRobot loads it from --out (local root) → no version tag needed. Usage: python subset_lerobot.py --repo angkul07/abc-teleop --out /workspace/data/yam7h/teleop --n 8 """ import argparse import json import os from huggingface_hub import snapshot_download def main(): ap = argparse.ArgumentParser() ap.add_argument("--repo", required=True) ap.add_argument("--out", required=True) ap.add_argument("--n", type=int, default=8) ap.add_argument("--token", default=os.environ.get("HF_TOKEN")) a = ap.parse_args() pats = [f"episode_{i:06d}" for i in range(a.n)] allow = ["meta/*"] + [f"data/**/{p}.parquet" for p in pats] + [f"videos/**/{p}.mp4" for p in pats] snapshot_download(a.repo, repo_type="dataset", local_dir=a.out, allow_patterns=allow, token=a.token) meta = os.path.join(a.out, "meta") eps = [json.loads(l) for l in open(os.path.join(meta, "episodes.jsonl"))][: a.n] with open(os.path.join(meta, "episodes.jsonl"), "w") as f: for e in eps: f.write(json.dumps(e) + "\n") stpath = os.path.join(meta, "episodes_stats.jsonl") if os.path.exists(stpath): st = [json.loads(l) for l in open(stpath)][: a.n] with open(stpath, "w") as f: for s in st: f.write(json.dumps(s) + "\n") info = json.load(open(os.path.join(meta, "info.json"))) vkeys = [k for k, v in (info.get("features") or {}).items() if isinstance(v, dict) and v.get("dtype") == "video"] info["total_episodes"] = a.n info["total_frames"] = sum(int(e.get("length", 0)) for e in eps) info["total_videos"] = a.n * len(vkeys) info["splits"] = {"train": f"0:{a.n}"} json.dump(info, open(os.path.join(meta, "info.json"), "w"), indent=4) print(f"subset {a.repo} -> {a.out}: {a.n} episodes, {info['total_frames']} frames, {len(vkeys)} cams") if __name__ == "__main__": main()