Datasets:
File size: 10,685 Bytes
0041cfd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 | #!/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())
|