| |
| """Build a v2 of a *-w-hardnegs dataset that keeps the v1 positive/negative pairing |
| byte-for-byte and only rewrites `text` / `hard_negative_texts` using the eval-aligned |
| raw query generator of the corresponding domain. |
| """ |
| from __future__ import annotations |
|
|
| import argparse |
| import hashlib |
| import importlib.util |
| import json |
| import sys |
| from collections import Counter |
| from pathlib import Path |
|
|
| import pyarrow as pa |
| import pyarrow.parquet as pq |
|
|
| FLUID_ROOT = Path("/mnt/iusers01/fatpou01/compsci01/r90629yl/src/Physics_bench/physics_bench_fluid") |
| SOLID_ROOT = Path("/mnt/iusers01/fatpou01/compsci01/r90629yl/src/Physics_bench/physics_bench_solid") |
| OPTICS_ROOT = Path("/mnt/iusers01/fatpou01/compsci01/r90629yl/src/Physics_bench/physics_bench_optics") |
| DYNAMICS_ROOT = Path("/mnt/iusers01/fatpou01/compsci01/r90629yl/src/Physics_bench/physics_bench_dynamics") |
|
|
|
|
| def _load_module(path: Path, name: str): |
| spec = importlib.util.spec_from_file_location(name, path) |
| mod = importlib.util.module_from_spec(spec) |
| spec.loader.exec_module(mod) |
| return mod |
|
|
|
|
| def make_text_fn(domain: str): |
| if domain == "optics": |
| sys.path.insert(0, str(OPTICS_ROOT / "src")) |
| from physics_bench_optics import dataset as ds |
|
|
| def fn(case): |
| return ds._parsed_query_text(case, ds._case_tokens(case)) |
|
|
| return fn, ds.QUERY_VERSION |
| if domain == "fluid": |
| exp = _load_module(FLUID_ROOT / "scripts" / "export_hf_fluid_test_format.py", "fluid_export") |
| return exp._eval_parsed_query_text, exp.EVAL_QUERY_VERSION |
| if domain == "solid": |
| sys.path.insert(0, str(SOLID_ROOT / "src")) |
| from physics_bench_solid import release_pipeline as rp |
|
|
| return rp._eval_parsed_query_text, rp.EVAL_QUERY_VERSION |
| if domain == "dynamics": |
| sys.path.insert(0, str(DYNAMICS_ROOT / "src")) |
| from physics_bench_dynamics import parsed_query as pqm |
|
|
| return pqm.generate_template_text, pqm.PARSED_QUERY_VERSION |
| raise ValueError(domain) |
|
|
|
|
| def disambiguate(domain: str, texts: dict, cases: dict) -> dict: |
| if domain == "dynamics": |
| sys.path.insert(0, str(DYNAMICS_ROOT / "src")) |
| from physics_bench_dynamics import parsed_query as pqm |
|
|
| return pqm.disambiguate_texts(texts, cases) |
| if domain == "optics": |
| sys.path.insert(0, str(OPTICS_ROOT / "src")) |
| from physics_bench_optics import dataset as ds |
|
|
| case_vals = {cid: ds._case_tokens(cases[cid]) for cid in texts} |
| return ds.disambiguate_parsed_texts(texts, case_vals) |
| return texts |
|
|
|
|
| def case_id_from_path(path: str) -> str: |
| return path.split("/")[-1].rsplit(".", 1)[0] |
|
|
|
|
| def main() -> None: |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--domain", required=True, choices=["optics", "fluid", "solid", "dynamics"]) |
| ap.add_argument("--v1-metadata", required=True, help="metadata.parquet downloaded from the v1 repo") |
| ap.add_argument("--train-cases", required=True, help="train cases.jsonl / release_cases.jsonl") |
| ap.add_argument("--out-dir", required=True) |
| ap.add_argument("--benchmark-cases", default=None, |
| help="optional benchmark cases file; asserts train params differ (solid safety check)") |
| args = ap.parse_args() |
|
|
| text_fn, version = make_text_fn(args.domain) |
|
|
| cases: dict[str, dict] = {} |
| with open(args.train_cases) as fh: |
| for line in fh: |
| c = json.loads(line) |
| cases[str(c["case_id"])] = c |
|
|
| if args.benchmark_cases: |
| bench: dict[str, dict] = {} |
| with open(args.benchmark_cases) as fh: |
| for line in fh: |
| c = json.loads(line) |
| bench[str(c["case_id"])] = c |
| shared = sorted(set(cases) & set(bench)) |
| identical = [c for c in shared if cases[c].get("params") == bench[c].get("params")] |
| print(f"[safety] case_id shared with benchmark: {len(shared)}; identical params: {len(identical)}") |
| if identical: |
| raise ValueError(f"train metadata appears to be the benchmark set, e.g. {identical[:3]}") |
|
|
| table = pq.read_table(args.v1_metadata) |
| rows = table.to_pylist() |
|
|
| referenced: list[str] = [] |
| for r in rows: |
| referenced.append(case_id_from_path(r["video"])) |
| referenced.extend(case_id_from_path(v) for v in r["hard_negative_videos"]) |
| missing = sorted({c for c in referenced if c not in cases}) |
| if missing: |
| raise ValueError(f"{len(missing)} referenced case_ids missing from train metadata, e.g. {missing[:3]}") |
|
|
| texts: dict[str, str] = {cid: text_fn(cases[cid]) for cid in sorted(set(referenced))} |
| texts = disambiguate(args.domain, texts, cases) |
|
|
| new_text = [texts[case_id_from_path(r["video"])] for r in rows] |
| new_negs = [[texts[case_id_from_path(v)] for v in r["hard_negative_videos"]] for r in rows] |
|
|
| dupes = {k: v for k, v in Counter(new_text).items() if v > 1} |
| if dupes: |
| raise ValueError(f"positive texts not unique: {len(dupes)} collisions") |
|
|
| names = table.schema.names |
| out_table = table.set_column(names.index("text"), table.schema.field(names.index("text")), |
| pa.array(new_text, type=pa.string())) |
| out_table = out_table.set_column(names.index("hard_negative_texts"), |
| out_table.schema.field(names.index("hard_negative_texts")), |
| pa.array(new_negs, type=out_table.schema.field(names.index("hard_negative_texts")).type)) |
|
|
| |
| assert out_table.column("video").to_pylist() == table.column("video").to_pylist() |
| assert out_table.column("hard_negative_videos").to_pylist() == table.column("hard_negative_videos").to_pylist() |
|
|
| pair_repr = json.dumps( |
| [[r["video"], r["hard_negative_videos"]] for r in rows], separators=(",", ":"), sort_keys=False |
| ) |
| pairing_sha = hashlib.sha256(pair_repr.encode()).hexdigest() |
|
|
| out = Path(args.out_dir) |
| out.mkdir(parents=True, exist_ok=True) |
| pq.write_table(out_table, out / "metadata.parquet", compression="snappy", write_page_index=True) |
|
|
| summary = { |
| "domain": args.domain, |
| "text_version": version, |
| "text_style": "eval-aligned raw structured query", |
| "rows": len(rows), |
| "distinct_cases": len(texts), |
| "negatives_per_case": len(rows[0]["hard_negative_videos"]), |
| "pairing_identical_to_v1": True, |
| "pairing_sha256": pairing_sha, |
| "unique_positive_texts": len(set(new_text)), |
| "v1_metadata": args.v1_metadata, |
| "train_cases": args.train_cases, |
| } |
| (out / "v2_manifest.json").write_text(json.dumps(summary, indent=2)) |
| sample = {"positive": new_text[0], "negatives": new_negs[0][:2], |
| "video": rows[0]["video"], "negative_videos": rows[0]["hard_negative_videos"][:2]} |
| (out / "sample.json").write_text(json.dumps(sample, indent=2)) |
| print(json.dumps(summary, indent=2)) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|