mARTin-B78/tts-dgx-spark-faster-qwen3-tts
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feat: deterministic per-voice RNG seed for consistent voice across requests (v6.7)

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Each API request now seeds PyTorch's CPU and CUDA RNGs before generation.
The seed is auto-derived from the voice name (stable MD5 hash) if not set
in voices.json, so all existing voices get consistent voice character with
zero config changes. Override per-voice with "seed": <int> in voices.json.

Previously the sampling RNG was unseeded, causing pitch/modulation drift
across requests even when speaker embeddings (.pt files) were identical.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
mARTin-B78 2026-06-21 14:32:58 +02:00
parent e58a6843b8
commit 602cf9e5df
1 changed files with 47 additions and 10 deletions
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57
patches/openai_server.patch
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@ -1,6 +1,14 @@
--- /tmp/upstream_openai_server.py 2026-06-20 20:43:53.380341702 +0200
+++ build/examples/openai_server.py 2026-06-20 21:18:30.515352046 +0200
@@ -66,6 +66,8 @@
--- /tmp/upstream_openai_server.py 2026-06-21 14:29:34.858114787 +0200
+++ build/examples/openai_server.py 2026-06-21 14:26:33.557536313 +0200
@@ -36,6 +36,7 @@
"""
import argparse
import asyncio
+import hashlib
import io
import json
import logging
@@ -66,10 +67,29 @@
tts_model = None
voices: dict = {}
@ -9,7 +17,28 @@
default_voice: Optional[str] = None
SAMPLE_RATE = 24000 # updated once the model loads
_model_lock = threading.Lock() # prevent concurrent GPU inference
@@ -145,6 +147,21 @@
+
+def _voice_seed(voice_name: str) -> int:
+ """Return a stable per-voice seed derived from the voice name.
+
+ Used as the default when no explicit 'seed' is set in voices.json.
+ MD5 is used only for its stable byte output — not for security.
+ """
+ return int(hashlib.md5(voice_name.encode()).hexdigest(), 16) % (2 ** 31)
+
+
+def _seed_rng(seed: int) -> None:
+ """Seed PyTorch CPU and CUDA RNGs for reproducible sampling."""
+ torch.manual_seed(seed)
+ if torch.cuda.is_available():
+ torch.cuda.manual_seed_all(seed)
+
+
# ---------------------------------------------------------------------------
# Request / response models
# ---------------------------------------------------------------------------
@@ -145,6 +165,21 @@
def resolve_voice(voice_name: str) -> dict:
"""Return voice config dict or fall back to default, else raise 400."""
@ -31,7 +60,7 @@
if voice_name in voices:
return voices[voice_name]
if default_voice and default_voice in voices:
@@ -168,7 +185,47 @@
@@ -168,7 +203,47 @@
# ---------------------------------------------------------------------------
@ -80,7 +109,11 @@
"""
Run generate_voice_clone_streaming in a background thread and yield
raw PCM bytes for each chunk as they arrive.
@@ -182,10 +239,15 @@
@@ -179,13 +254,19 @@
def producer():
try:
with _model_lock:
+ _seed_rng(voice_cfg.get("seed", _voice_seed(voice_name)))
for chunk, _sr, _timing in tts_model.generate_voice_clone_streaming(
text=text,
language=voice_cfg.get("language", "Auto"),
@ -98,7 +131,11 @@
):
q.put(chunk)
except Exception as exc:
@@ -247,8 +309,14 @@
@@ -244,11 +325,18 @@
def _generate():
with _model_lock:
+ _seed_rng(voice_cfg.get("seed", _voice_seed(req.voice)))
return tts_model.generate_voice_clone(
text=req.input,
language=voice_cfg.get("language", "Auto"),
@ -114,7 +151,7 @@
)
audio_arrays, sr = await loop.run_in_executor(None, _generate)
@@ -259,7 +327,7 @@
@@ -259,7 +347,7 @@
async def audio_stream():
if fmt == "wav":
yield _wav_header(SAMPLE_RATE) # stream with unknown data length
@ -123,7 +160,7 @@
yield raw_chunk
return StreamingResponse(audio_stream(), media_type=content_type)
@@ -306,16 +374,20 @@
@@ -306,16 +394,20 @@
p.add_argument("--host", default="0.0.0.0", help="Bind host (default: 0.0.0.0)")
p.add_argument("--port", type=int, default=8000, help="Bind port (default: 8000)")
p.add_argument("--device", default="cuda", help="Torch device (default: cuda)")
@ -145,7 +182,7 @@
with open(args.voices) as f:
voices = json.load(f)
default_voice = next(iter(voices))
@@ -344,6 +416,7 @@
@@ -344,6 +436,7 @@
args.model,
device=args.device,
dtype=torch.bfloat16,