"""Build memmap shards from I.PHI TRAIN segments (val/test never enter training data). Same plane format as Stoicheia shards so MultiTierLoader can mix iphi with the pretraining tiers transparently. tier='iphi', clean=1.0. python insc_data/build_shards.py --out $INS_DATA/shards/iphi_punct """ from __future__ import annotations import argparse, json, sys from pathlib import Path import numpy as np import pyarrow as pa import pyarrow.parquet as pq sys.path.insert(0, str(Path(__file__).resolve().parent)) from iphi import load PLANES = ("chars", "boundary", "dia", "cap", "punct") def main(): ap = argparse.ArgumentParser() ap.add_argument("--out", required=True) ap.add_argument("--min-len", type=int, default=32) a = ap.parse_args() out = Path(a.out); out.mkdir(parents=True, exist_ok=True) bufs = {p: [] for p in PLANES} rows = {"offset": [], "length": [], "tier": [], "clean": [], "source": [], "id": [], "region_id": [], "century_id": []} off = 0 # real edition text (tier iphi) + synthetic paraphrase columns (tier iphi_syn). # ONLY train-split inscriptions in both cases: the synthetic columns of val/test # items paraphrase the held-out answers — using them would leak the eval. for field, tier in (("with_diacritics", "iphi"), ("synthetic", "iphi_syn"), ("synthetic_2", "iphi_syn")): for r in load(split="train", min_len=a.min_len, field=field): for p in PLANES: bufs[p].append(r[p]) rows["offset"].append(off); rows["length"].append(len(r["chars"])) rows["tier"].append(tier); rows["clean"].append(1.0) rows["source"].append(field); rows["id"].append(f"{r['phi_id']}#{r['seg']}") rows["region_id"].append(r["region_id"]); rows["century_id"].append(r["century_id"]) off += len(r["chars"]) for p in PLANES: np.concatenate(bufs[p]).tofile(out / f"{p}.bin") pq.write_table(pa.table(rows), out / "index.parquet") (out / "stats.json").write_text(json.dumps(dict(records=len(rows["offset"]), letters=off))) print(f"iphi shards: {len(rows['offset']):,} records, {off/1e6:.1f}M letters -> {out}") if __name__ == "__main__": main()