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Diffstat (limited to 'app/backends/sglomni/configs/moss_tts.yaml')
| -rw-r--r-- | app/backends/sglomni/configs/moss_tts.yaml | 22 |
1 files changed, 22 insertions, 0 deletions
diff --git a/app/backends/sglomni/configs/moss_tts.yaml b/app/backends/sglomni/configs/moss_tts.yaml index ef8d8fa..41bddd5 100644 --- a/app/backends/sglomni/configs/moss_tts.yaml +++ b/app/backends/sglomni/configs/moss_tts.yaml @@ -1,2 +1,24 @@ +# MOSS-TTS v1.5 with a pinned AR-engine memory budget. +# +# The upstream pipeline (MossTTSPipelineConfig) colocates its three stages +# (preprocessing -> tts_engine -> vocoder) in one process on GPU 0 and leaves +# the engine's sglang mem_fraction_static unset: the static pool (weights + +# KV cache) is auto-sized to nearly all free VRAM at boot. On a 24 GB card +# that leaves only tens of MiB free once the engine's CUDA graphs and the +# colocated vocoder are resident — the first /v1/audio/speech request aborts +# with "CUDA out of memory. Tried to allocate ~100 MiB" and every retry fails +# identically (the same failure the qwen3_tts/higgs/zonos2 vendored configs +# fix; note moss_tts_local does NOT need this — MossTTSLocalPipelineConfig +# already budgets its colocated stages explicitly: 0.15/0.67/0.18). +# +# 0.70 pins the static pool at ~70% of the card (~16.5 GB on a 24 GB GPU — +# a KV pool far larger than any narration request needs) and leaves ~7 GB +# for the vocoder, CUDA graphs, transient allocations, and other GPU +# processes. Precedent: dots_tts.yaml pins this same knob. config_cls: MossTTSPipelineConfig model_path: OpenMOSS-Team/MOSS-TTS-v1.5 + +stages: + tts_engine: + engine: + mem_fraction_static: 0.70 |