| |
| """Reproduce all 18 cells and paired intervals from 72,000 saved scoring records.""" |
|
|
| from __future__ import annotations |
|
|
| import argparse |
| import json |
| import subprocess |
| import sys |
| from pathlib import Path |
|
|
| from analyze_crossdomain_paper import CROSS_KEYS, MODELS, analyze |
| from hf_release_common import read_json, read_rows, write_json |
| from score_hf_dataset import score |
|
|
|
|
| def replay(dataset, output): |
| output.mkdir(parents=True, exist_ok=True) |
| |
| |
| result = json.loads( |
| json.dumps(analyze(dataset / "inputs", dataset / "expected"), allow_nan=False) |
| ) |
| expected = read_json(dataset / "expected/revision-analysis.json") |
| if result != expected: |
| differing = [key for key in result if result[key] != expected.get(key)] |
| raise ValueError("Numerical replay differs from frozen analysis: " + ", ".join(differing)) |
| labels = read_rows(dataset / "metadata/views.jsonl.gz") |
| for model in MODELS: |
| predictions = read_rows(dataset / f"inputs/plotqa/{model}.jsonl.gz") + read_rows( |
| dataset / f"inputs/crossdomain/{CROSS_KEYS[model]}.jsonl.gz" |
| ) |
| scored = score(labels, predictions) |
| for source, values in scored["by_source"].items(): |
| archived = result["domains"][source]["models"][model] |
| if values["counts"] != archived["counts"] or values["states"] != archived["states"]: |
| raise ValueError( |
| "Public prediction scorer disagrees with paper: " + source + "/" + model |
| ) |
| write_json(output / (model + "-score.json"), scored) |
| from build_answerability_rewrite_assets import build as build_chart |
|
|
| result_path = output / "analysis.json" |
| write_json(result_path, result) |
| subprocess.run( |
| [ |
| sys.executable, |
| str(dataset / "scripts/build_crossdomain_paper_assets.py"), |
| "--analysis", |
| str(result_path), |
| "--output", |
| str(output / "tables"), |
| ], |
| check=True, |
| ) |
| build_chart( |
| dataset / "inputs", |
| result_path, |
| output / "charts", |
| dataset / "evidence/plotqa/bounded-witness-proofs.jsonl.gz", |
| ) |
| from collections import Counter |
|
|
| finite = read_rows(dataset / "evidence/finite/original-results.jsonl.gz") |
| solver = read_rows(dataset / "evidence/finite/solver-results.jsonl.gz") |
| if ( |
| len(finite) != 1024 |
| or len(solver) != 1456 |
| or Counter(row["truth"] for row in solver) != {"ambiguous": 822, "constant": 634} |
| ): |
| raise ValueError("Finite study counts differ") |
| if not all(row["enumeration_status"] == row["smt_status"] == row["truth"] for row in solver): |
| raise ValueError("Archived solver decisions disagree") |
| report = { |
| "status": "passed", |
| "saved_records": 72000, |
| "model_domain_cells": 18, |
| "exact_analysis_replay": True, |
| "bootstrap_draws": 10000, |
| "new_prediction_scorer_matches_all_18_cells": True, |
| "finite_cases": len(finite), |
| "solver_cases": len(solver), |
| "solver_constructors_rerun": False, |
| "inference_calls": 0, |
| "gqa_question_text": "ID references; original text verified separately during reconstruction", |
| } |
| write_json(output / "replay-validation.json", report) |
| return report |
|
|
|
|
| if __name__ == "__main__": |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument("--dataset", type=Path, default=Path(__file__).resolve().parents[1]) |
| parser.add_argument("--output", type=Path, required=True) |
| args = parser.parse_args() |
| if args.output.resolve().is_relative_to(args.dataset.resolve()): |
| parser.error("Write replay outputs outside the frozen dataset directory") |
| print(json.dumps(replay(args.dataset, args.output))) |
|
|
