Files
imagefind/scripts/audio_small_ab.py
T

110 lines
4.2 KiB
Python

from __future__ import annotations
import argparse
import json
import subprocess
import sys
import tempfile
import time
import wave
from pathlib import Path
COMBINATIONS = (
("small_vad_gpu_1beam", "small", "GPU", "vad"),
("small_context_gpu_1beam", "small", "GPU", "continuous"),
("small_context_cpu_5beam", "small", "CPU", "continuous"),
("medium_current_baseline", "medium", "GPU", "vad"),
)
def arguments() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Read-only Small/Medium audio A/B diagnostics")
parser.add_argument("--data-dir", required=True, type=Path)
parser.add_argument("--media", required=True, type=Path, action="append")
parser.add_argument("--windows", required=True, type=Path)
parser.add_argument("--output", required=True, type=Path)
parser.add_argument("--ffmpeg", default="ffmpeg")
parser.add_argument("--force", action="store_true")
return parser.parse_args()
def worker_run(data_dir: Path, wav: Path, window: dict, combination: tuple[str, ...]) -> dict:
name, model, device, segmentation = combination
with wave.open(str(wav), "rb") as handle:
sample_rate = handle.getframerate()
start_ms = int(window["start_ms"])
duration_ms = int(window["end_ms"]) - start_ms
command = [
sys.executable, "-m", "imagefind.audio_worker",
"--data-dir", str(data_dir), "--wav", str(wav),
"--device", device, "--model-variant", model,
"--segmentation", segmentation, "--quality-profile", "accuracy",
"--language-policy", str(window.get("language_policy", "zh_priority")),
"--chunk-seconds", str(max(15, min(30, (duration_ms + 999) // 1000))),
"--overlap-seconds", "0",
"--start-frame", str(start_ms * sample_rate // 1000),
"--max-chunks", "1", "--cpu-threads", "2",
]
started = time.monotonic()
process = subprocess.run(command, text=True, capture_output=True, encoding="utf-8", errors="replace")
elapsed = time.monotonic() - started
events = []
for line in process.stdout.splitlines():
try:
events.append(json.loads(line))
except json.JSONDecodeError:
pass
return {
"combination": name,
"model": model,
"device": device,
"beam": 1 if device == "GPU" else 5,
"segmentation": segmentation,
"elapsed_seconds": round(elapsed, 3),
"window_seconds": round(duration_ms / 1000, 3),
"rtf": round(elapsed / max(0.001, duration_ms / 1000), 3),
"exit_code": process.returncode,
"events": events,
"stderr_tail": process.stderr[-2000:],
}
def main() -> int:
args = arguments()
if args.output.exists() and not args.force:
raise SystemExit("output exists; pass --force to replace this diagnostic artifact")
windows = json.loads(args.windows.read_text(encoding="utf-8"))
artifact = {
"schema_version": 1,
"created_at": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
"database_writes": False,
"runs": [],
}
with tempfile.TemporaryDirectory(prefix="imagefind-audio-ab-") as work:
for media in args.media:
wav = Path(work) / f"{media.stem}.wav"
subprocess.run(
[
args.ffmpeg, "-nostdin", "-y", "-i", str(media), "-vn",
"-ac", "1", "-ar", "16000", "-c:a", "pcm_s16le", str(wav),
],
check=True,
capture_output=True,
)
selected = windows.get(media.name)
if not isinstance(selected, list) or len(selected) != 8:
raise SystemExit(f"{media.name}: windows JSON must contain exactly 8 labelled windows")
for window in selected:
for combination in COMBINATIONS:
result = worker_run(args.data_dir, wav, window, combination)
result.update({"media": media.name, "window": window})
artifact["runs"].append(result)
args.output.parent.mkdir(parents=True, exist_ok=True)
args.output.write_text(json.dumps(artifact, ensure_ascii=False, indent=2), encoding="utf-8")
return 0
if __name__ == "__main__":
raise SystemExit(main())