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torch.compile with dynamic=True still specializes per shape family on first call. The warmup was running one text length, leaving real requests to JIT-compile their own shapes (15-22s for first chunk). HA freezes because it gets no AudioChunk for 22 seconds. Fix: - Run 3 warmup passes (short/medium/long text) so torch.compile builds a dynamic shape graph covering the range HA actually sends. Real requests then hit a cached compilation and synthesize in 3-8s. - Reduce default chunk_size from 300 to 120 chars so the first text chunk is shorter, producing faster synthesis and earlier first audio. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
78 lines
2.4 KiB
Python
78 lines
2.4 KiB
Python
import asyncio
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import logging
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import sys
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from functools import partial
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from wyoming.server import AsyncServer
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import engine
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from config import get_wyoming_host, get_wyoming_port, load_config
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from wyoming_handler import ChatterboxWyomingHandler
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from wyoming_voices import create_wyoming_info, load_voices
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s %(levelname)s %(name)s: %(message)s",
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stream=sys.stdout,
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)
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logger = logging.getLogger(__name__)
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_WARMUP_TEXTS = [
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# Short: covers brief HA notifications (lights on/off, etc.)
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"Okay.",
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# Medium: covers typical HA announcements
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"The front door is open. Please close it.",
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# Long: covers longer TTS requests and pre-compiles dynamic shape graph
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(
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"This is a warmup synthesis to pre-compile neural network kernels "
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"for longer text lengths used in Home Assistant announcements and notifications."
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),
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]
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def _warmup(voices: dict) -> None:
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from wyoming_voices import resolve_voice
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audio_prompt = resolve_voice(None, voices) if voices else None
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logger.info(
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f"Running {len(_WARMUP_TEXTS)}-pass warmup to pre-compile torch kernels "
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"for short, medium, and long text lengths..."
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)
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for i, text in enumerate(_WARMUP_TEXTS, 1):
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try:
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engine.synthesize(text=text, audio_prompt_path=audio_prompt)
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logger.info(f"Warmup pass {i}/{len(_WARMUP_TEXTS)} complete")
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except Exception:
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logger.warning(f"Warmup pass {i} failed (non-fatal)", exc_info=True)
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logger.info("Warmup complete")
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async def main() -> None:
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load_config()
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logger.info("Loading TTS model...")
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if not engine.load_model():
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logger.error("Failed to load model, exiting")
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sys.exit(1)
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voices = load_voices()
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wyoming_info = create_wyoming_info(engine.get_sample_rate(), voices)
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# Run a warmup synthesis before accepting connections so MIOpen benchmarks
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# and caches the best convolution algorithms for all layer shapes. Without
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# this, the first real HA request triggers benchmarking (hundreds of runs)
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# and times out before any audio is returned.
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_warmup(voices)
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host = get_wyoming_host()
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port = get_wyoming_port()
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uri = f"tcp://{host}:{port}"
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logger.info(f"Starting Wyoming server on {uri}")
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server = AsyncServer.from_uri(uri)
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await server.run(partial(ChatterboxWyomingHandler, wyoming_info, voices))
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if __name__ == "__main__":
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asyncio.run(main())
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