| """Check that every counted leaderboard attempt has its run on HF (works without a token). |
| |
| usage: python3 check_coverage.py [trials.csv] [--revision REV] |
| |
| For each row of trials.csv (one row per counted attempt), it checks in the dataset MLL-Lab/embodied-exam-runs: |
| - runs/<h2>/<slug>/run.json and trajectory.jsonl.gz exist, and replay.mp4 exists when has_video = 1; |
| - the slug has a row in index/<suite>.json whose run and outcome equal the leaderboard's. |
| It lists the runs/<h2>/ folders through the HF API (at most 256 calls) and reads the index files. Without a token, |
| HF's rate limit may make it wait a few minutes; with HF_TOKEN set it runs in about a minute. |
| Exit status 0 only at 100% coverage. |
| """ |
| import argparse, collections, csv, hashlib, json, sys, time, urllib.request |
| from huggingface_hub import HfApi |
| REPO = 'MLL-Lab/embodied-exam-runs' |
| ap = argparse.ArgumentParser(); ap.add_argument('trials', nargs='?', default='trials.csv'); ap.add_argument('--revision', default='main') |
| a = ap.parse_args() |
| api = HfApi() |
| rev = api.dataset_info(REPO, revision=a.revision).sha |
| rows = list(csv.DictReader(open(a.trials))) |
| h2 = lambda s: hashlib.sha1(s.encode()).hexdigest()[:2] |
| files = set() |
| def tree(d): |
| for k in range(20): |
| try: |
| return [e.path for e in api.list_repo_tree(REPO, path_in_repo=f'runs/{d}', recursive=True, repo_type='dataset', revision=rev)] |
| except Exception as e: |
| if '429' not in str(e) and 'rate limit' not in str(e).lower() or k == 19: raise |
| print('rate limited, waiting 60 s', file=sys.stderr, flush=True); time.sleep(60) |
| for d in sorted({h2(r['hf_slug']) for r in rows}): |
| files.update(tree(d)) |
| def get(path): |
| return json.loads(urllib.request.urlopen(f'https://huggingface.co/datasets/{REPO}/resolve/{rev}/{path}', timeout=300).read()) |
| idx = get('index.json') |
| irow = {} |
| for s in idx['suites']: |
| for x in get(f'index/{s}.json')['runs']: |
| irow[x['slug']] = x |
| c = collections.Counter(); bad = [] |
| for r in rows: |
| s = r['hf_slug']; base = f'runs/{h2(s)}/{s}/' |
| need = ['run.json', 'trajectory.jsonl.gz'] + (['replay.mp4'] if r['has_video'] == '1' else []) |
| miss = [f for f in need if base + f not in files] |
| x = irow.get(s) |
| ok_idx = bool(x) and x['run'] == r['run_id'] and ((x.get('success') == 1 or x.get('state') == 'success') == (r['verdict'] == 'success')) |
| if miss or not ok_idx: |
| bad.append((r['run_id'], r['task_dir'], s, miss, 'index ok' if ok_idx else ('index outcome differs' if x else 'not in index'))) |
| else: |
| c['covered'] += 1 |
| c['with video'] += r['has_video'] == '1' |
| print(f'{REPO}@{rev[:10]}: {c["covered"]} of {len(rows)} counted attempts covered ' |
| f'(run.json + trajectory + index row with the same outcome; replay.mp4 for the {c["with video"]} with a video)') |
| for b in bad: print('MISSING', *b) |
| sys.exit(0 if not bad else 1) |
|
|
