Datasets:
Download scripts/test_harness.py from modulate/entity-transcription-benchmark: direct link, hf CLI and curl.
- Browser
- Download file 10.7 kB
-
https://huggingface.co/datasets/modulate/entity-transcription-benchmark/resolve/main/scripts/test_harness.py
- Command line
-
hf download hf://datasets/modulate/entity-transcription-benchmark/scripts/test_harness.py
-
curl -L -o test_harness.py https://huggingface.co/datasets/modulate/entity-transcription-benchmark/resolve/main/scripts/test_harness.py
10.7 kB
| #!/usr/bin/env python3 | |
| """Offline end-to-end test for the harness. | |
| Builds a synthetic dataset with the SAME schema as | |
| modulate/entity-transcription-benchmark (id, subset, transcript, entities, | |
| entity_types, entity_tiers, entity_offsets, n_entities, duration_s, audio), | |
| stands up a fake STT endpoint, and runs the real CLIs against the real | |
| matcher_v5. No network and no API keys required. | |
| python test_harness.py | |
| """ | |
| from __future__ import annotations | |
| import io | |
| import json | |
| import os | |
| import shutil | |
| import subprocess | |
| import sys | |
| import tempfile | |
| import threading | |
| import time | |
| from http.server import BaseHTTPRequestHandler, HTTPServer | |
| import numpy as np | |
| HERE = os.path.dirname(os.path.abspath(__file__)) | |
| # id, transcript, entities, types, per-span tiers, subset, what the fake STT returns | |
| CLIPS = [ | |
| ("c001", "Nadia Boulanger taught in Paris", | |
| ["Nadia Boulanger", "Paris"], ["PERSON", "GPE"], ["A", "A"], "synthetic", | |
| "nadia boulanger taught in paris"), | |
| ("c002", "Addenbrooke's Hospital is in Cambridge", | |
| ["Addenbrooke's Hospital", "Cambridge"], ["ORG", "GPE"], ["A", "B"], "meetings", | |
| "addenbrookes hospital is in cambridge"), | |
| ("c003", "The Mapuche live in Chile", | |
| ["Mapuche", "Chile"], ["NORP", "GPE"], ["A", "A"], "belebele", | |
| "the mapoochay live in chilly"), | |
| ("c004", "Ikeda visited Osaka", | |
| ["Ikeda", "Osaka"], ["PERSON", "GPE"], ["A", "B"], "synthetic", | |
| "ikeda visited osaka"), | |
| ("c005", "nothing named here at all", [], [], [], "meetings", | |
| "nothing named here at all"), | |
| ("c006", "Trivial mention of London", | |
| ["London"], ["GPE"], ["B"], "belebele", | |
| "trivial mention of london"), | |
| ] | |
| class FakeSTT(BaseHTTPRequestHandler): | |
| order: list[str] = [] | |
| served = 0 | |
| def do_POST(self): # noqa: N802 | |
| self.rfile.read(int(self.headers.get("Content-Length", 0))) | |
| if self.headers.get("Authorization") != "Bearer test-key-123": | |
| self.send_response(401) | |
| self.end_headers() | |
| self.wfile.write(b'{"error":"bad key"}') | |
| return | |
| cls = type(self) | |
| body = json.dumps({"result": {"transcript": cls.order[cls.served % len(cls.order)]}}).encode() | |
| cls.served += 1 | |
| self.send_response(200) | |
| self.send_header("Content-Type", "application/json") | |
| self.send_header("Content-Length", str(len(body))) | |
| self.end_headers() | |
| self.wfile.write(body) | |
| def log_message(self, *args): | |
| pass | |
| def build_dataset(path: str) -> None: | |
| import soundfile as sf | |
| from datasets import Audio, Dataset | |
| rng = np.random.default_rng(0) | |
| rows: dict[str, list] = {k: [] for k in ( | |
| "audio", "id", "subset", "transcript", "entities", "entity_types", | |
| "n_entities", "duration_s", "entity_tiers", "entity_offsets")} | |
| for clip_id, text, entities, types, tiers, subset, _ in CLIPS: | |
| buf = io.BytesIO() | |
| sf.write(buf, rng.normal(0, 0.01, 8000).astype(np.float32), 16000, | |
| format="WAV", subtype="PCM_16") | |
| rows["audio"].append({"bytes": buf.getvalue(), "path": f"{clip_id}.wav"}) | |
| rows["id"].append(f"named_entities-{subset}-{clip_id}") | |
| rows["subset"].append(subset) | |
| rows["transcript"].append(text) | |
| # stored as JSON strings, exactly as the published parquet does | |
| rows["entities"].append(json.dumps(entities)) | |
| rows["entity_types"].append(json.dumps(types)) | |
| rows["entity_tiers"].append(json.dumps(tiers)) | |
| rows["n_entities"].append(len(entities)) | |
| rows["duration_s"].append(0.5) | |
| rows["entity_offsets"].append(json.dumps( | |
| [{"start": text.find(e), "end": text.find(e) + len(e), "label": t, "text": e} | |
| for e, t in zip(entities, types)])) | |
| Dataset.from_dict(rows).cast_column("audio", Audio(decode=False)).save_to_disk(path) | |
| def run(cmd: list[str], env: dict) -> subprocess.CompletedProcess: | |
| return subprocess.run(cmd, cwd=HERE, env={**os.environ, **env}, capture_output=True, text=True) | |
| def main() -> int: | |
| matcher_path = os.path.join(HERE, "matcher_v5.py") | |
| if not os.path.exists(matcher_path): | |
| print("matcher_v5.py is not next to this script -- copy it in first:") | |
| print(" cp ../bench2/matcher_v5.py .") | |
| return 2 | |
| sys.path.insert(0, HERE) | |
| import matcher_v5 # noqa: E402 | |
| work = tempfile.mkdtemp(prefix="ebench_") | |
| dataset_path = os.path.join(work, "ds") | |
| hyps = os.path.join(work, "run.jsonl") | |
| failures: list[str] = [] | |
| def check(label: str, ok: bool, detail: str = "") -> None: | |
| print(f" [{'ok' if ok else 'FAIL'}] {label}" + (f" -- {detail}" if detail and not ok else "")) | |
| if not ok: | |
| failures.append(label) | |
| # Ground truth computed by calling the matcher directly, so the test checks | |
| # the harness plumbing (tier filter, join, aggregation) not the match rule. | |
| tier_a, tier_all = [], [] | |
| for clip_id, _, entities, types, tiers, _, hypothesis in CLIPS: | |
| for entity, tier in zip(entities, tiers): | |
| outcome = bool(matcher_v5.hit(entity, hypothesis)) | |
| tier_all.append(outcome) | |
| if tier == "A": | |
| tier_a.append(outcome) | |
| expect_a_spans, expect_a_hits = len(tier_a), sum(tier_a) | |
| expect_all_spans = len(tier_all) | |
| print(f"matcher_v5 self-test: {matcher_v5.validate(verbose=False)} ({len(matcher_v5.CASES)} cases)") | |
| print(f"expected tier-A: {expect_a_hits}/{expect_a_spans} spans; all tiers: {expect_all_spans} spans\n") | |
| print("building fixture dataset...") | |
| build_dataset(dataset_path) | |
| FakeSTT.order = [c[6] for c in CLIPS] | |
| server = HTTPServer(("127.0.0.1", 0), FakeSTT) | |
| port = server.server_address[1] | |
| threading.Thread(target=server.serve_forever, daemon=True).start() | |
| time.sleep(0.2) | |
| base = [ | |
| sys.executable, "run_benchmark.py", "--provider", "http", | |
| "--endpoint", f"http://127.0.0.1:{port}/stt", "--api-key-env", "TEST_STT_KEY", | |
| "--response-path", "result.transcript", "--local-path", dataset_path, "--workers", "1", | |
| ] | |
| good = {"TEST_STT_KEY": "test-key-123"} | |
| print("collection:") | |
| proc = run(base + ["--out", hyps], good) | |
| check("run_benchmark exits clean", proc.returncode == 0, proc.stderr[-600:]) | |
| check("columns resolved from real schema", | |
| "transcript" in proc.stderr and "entity_tiers" in proc.stderr, proc.stderr[:400]) | |
| records = [json.loads(l) for l in open(hyps)] if os.path.exists(hyps) else [] | |
| check("all 6 clips transcribed by default", len(records) == 6, f"got {len(records)}") | |
| check("no failed clips", all(r.get("hypothesis") is not None for r in records)) | |
| check("manifest written", os.path.exists(os.path.splitext(hyps)[0] + ".manifest.json")) | |
| print("\nauth failure surfaces:") | |
| bad = run(base + ["--out", os.path.join(work, "bad.jsonl")], {"TEST_STT_KEY": "wrong"}) | |
| check("bad key does not silently score", bad.returncode != 0 or "401" in bad.stderr) | |
| print("\nresume:") | |
| before = len(open(hyps).readlines()) | |
| again = run(base + ["--out", hyps], good) | |
| check("rerun is a no-op", again.returncode == 0 and len(open(hyps).readlines()) == before) | |
| print("\nscoring (tier A, the published protocol):") | |
| scored = run([sys.executable, "score_benchmark.py", "--hyps", hyps, | |
| "--local-path", dataset_path], {}) | |
| check("score_benchmark exits clean", scored.returncode == 0, scored.stderr[-700:]) | |
| summary_path = os.path.splitext(hyps)[0] + ".summary.json" | |
| summary = json.load(open(summary_path)) if os.path.exists(summary_path) else {} | |
| check("summary written", bool(summary)) | |
| if summary: | |
| check(f"tier-A spans only ({expect_a_spans})", | |
| summary["entity_spans"] == expect_a_spans, str(summary.get("entity_spans"))) | |
| check(f"hits match direct matcher calls ({expect_a_hits})", | |
| summary["entity_hits"] == expect_a_hits, str(summary.get("entity_hits"))) | |
| check("tier-B spans excluded", summary["entity_spans"] < expect_all_spans) | |
| check("matcher self-test gate = 49/49", | |
| summary["matcher_self_test"] == f"{len(matcher_v5.CASES)}/{len(matcher_v5.CASES)}", | |
| str(summary.get("matcher_self_test"))) | |
| check("WER covers every transcribed clip", summary["clips_with_hypothesis"] == 6) | |
| check("WER computed", summary["wer"] is not None) | |
| check("subset breakdown present", | |
| bool(summary["by_subset"]) and set(summary["by_subset"]) <= {"synthetic", "meetings", "belebele"}) | |
| check("provider recorded", summary["provider"] == "http") | |
| hits_csv = os.path.splitext(hyps)[0] + ".hits.csv" | |
| check("per-span hits CSV written", os.path.exists(hits_csv)) | |
| if os.path.exists(hits_csv): | |
| check("hits CSV carries tier column", "tier" in open(hits_csv).readline()) | |
| print("\nscoring (tier all):") | |
| every = run([sys.executable, "score_benchmark.py", "--hyps", hyps, "--local-path", dataset_path, | |
| "--tier", "all", "--out-prefix", os.path.join(work, "all")], {}) | |
| all_summary = os.path.join(work, "all.summary.json") | |
| ok = os.path.exists(all_summary) and json.load(open(all_summary))["entity_spans"] == expect_all_spans | |
| check(f"tier all scores every span ({expect_all_spans})", every.returncode == 0 and ok, | |
| every.stderr[-400:]) | |
| print("\ncompare / diff:") | |
| diffed = run([sys.executable, "score_benchmark.py", "--hyps", hyps, "--local-path", dataset_path, | |
| "--compare", hits_csv], {}) | |
| check("self-diff reports zero disagreements", "disagreements 0" in diffed.stdout, | |
| diffed.stdout[-400:]) | |
| print("\nmissing matcher is fatal, not silent:") | |
| nomatcher = run([sys.executable, "score_benchmark.py", "--hyps", hyps, | |
| "--local-path", dataset_path, "--matcher-path", os.path.join(work, "nope.py")], | |
| {}) | |
| check("refuses to score without a real matcher path", nomatcher.returncode != 0) | |
| print("\nclip-level tier filter (collection):") | |
| a_only = os.path.join(work, "a.jsonl") | |
| FakeSTT.served = 0 | |
| filt = run(base + ["--tier", "A", "--out", a_only], good) | |
| expect_clips = sum(1 for c in CLIPS if "A" in c[4]) | |
| check(f"--tier A skips clips with no A span ({expect_clips})", | |
| filt.returncode == 0 and len(open(a_only).readlines()) == expect_clips, | |
| filt.stderr[-400:]) | |
| server.shutdown() | |
| shutil.rmtree(work, ignore_errors=True) | |
| print() | |
| if failures: | |
| print(f"{len(failures)} FAILED: {failures}") | |
| return 1 | |
| print("all checks passed") | |
| return 0 | |
| if __name__ == "__main__": | |
| sys.exit(main()) | |