#!/usr/bin/env python3 """Apply instruction strings into ArenaVlaSafety HDF5 files. Input is a JSONL file whose each line contains at least: - path: path to HDF5 relative to --base-dir (or an absolute path) - instruction or instructions: text string, or a list of strings For every HDF5, this script writes the instruction into all groups under `data//instruction`. If the dataset is missing, it will be created as UTF-8 variable-length string. If it already exists (scalar or array), it is overwritten with the provided text. Example: python scripts/apply_instructions.py \ --instructions /path/to/instructions.jsonl \ --base-dir /mnt/nvme1/WS/czx/data/trainv0 """ from __future__ import annotations import argparse import json from pathlib import Path from typing import Any, Optional import h5py import numpy as np def _resolve_h5(base_dir: Path, file_path: str) -> Path: p = Path(file_path) if not p.is_absolute(): p = base_dir / p return p.expanduser().resolve() def _pick_instruction(obj: Any) -> Optional[str]: # Accept either `instruction` (str) or `instructions` (list[str]/str) if obj is None: return None if isinstance(obj, str): return obj.strip() or None if isinstance(obj, (list, tuple)): for item in obj: if isinstance(item, str) and item.strip(): return item.strip() return None return None def _write_instruction(h5_path: Path, text: str) -> None: text = str(text) with h5py.File(h5_path, "a") as f: data_group = f.get("data") if data_group is None: raise ValueError(f"{h5_path} missing 'data' group") # Use variable-length UTF-8 strings str_dtype = h5py.string_dtype(encoding="utf-8") for ts_key in list(data_group.keys()): grp = data_group[ts_key] ds = grp.get("instruction") if ds is None: ds = grp.create_dataset("instruction", shape=(), dtype=str_dtype) ds[...] = text continue # Scalar dataset if ds.shape == (): try: ds[...] = text except TypeError: # Recreate dataset with string dtype del grp["instruction"] ds = grp.create_dataset("instruction", shape=(), dtype=str_dtype) ds[...] = text else: fill = np.empty(ds.shape, dtype=ds.dtype) try: fill[...] = text except TypeError: fill = np.empty(ds.shape, dtype=str) fill[...] = text ds[...] = fill def main() -> None: ap = argparse.ArgumentParser(description="Inject instruction text into HDF5 episodes") ap.add_argument("--instructions", required=True, help="Path to JSONL file") ap.add_argument("--base-dir", required=True, help="Base dir to resolve relative HDF5 paths") args = ap.parse_args() base_dir = Path(args.base_dir).expanduser().resolve() jsonl = Path(args.instructions).expanduser().resolve() if not jsonl.exists(): raise FileNotFoundError(jsonl) updated = 0 skipped = 0 missing = 0 with jsonl.open("r", encoding="utf-8") as fh: for line in fh: line = line.strip() if not line: continue try: rec = json.loads(line) except json.JSONDecodeError: print(f"[WARN] skip invalid JSON: {line[:80]}...") skipped += 1 continue # Flexible field names for path path_field = rec.get("path") or rec.get("relpath") or rec.get("file") or rec.get("h5_path") if not path_field: print("[WARN] skip record without path") skipped += 1 continue instr = ( _pick_instruction(rec.get("instruction")) or _pick_instruction(rec.get("instructions")) ) if not instr: print(f"[WARN] no instruction for {path_field}; skip") skipped += 1 continue h5_path = _resolve_h5(base_dir, str(path_field)) if not h5_path.exists(): print(f"[WARN] missing file: {h5_path}") missing += 1 continue try: _write_instruction(h5_path, instr) updated += 1 except Exception as e: print(f"[ERROR] write failed for {h5_path}: {e}") skipped += 1 print(f"Done. Updated={updated}, Missing={missing}, Skipped={skipped}") if __name__ == "__main__": main()