Qwen3-TTS auf der DGX: Startskript, Deploy-Config, Node-Client
- dgx/start-qwen3-tts.sh startet CustomVoice (:8011) oder Base/Klon (:8012) via vllm-omni im Image vllm-node-030-omni - dgx/qwen3_tts_spark.yaml: V1-Runner (MRV2 scheitert am vLLM-dev-Build) und 0.08/0.06 Speicher statt 2x 0.3 - SpeechSynthesis_Qwen.js als Ersatz fuer das Azure-Skript: Stimmenauswahl inkl. Klonstimmen, <break>-Pausen, Musik, Ausgabe als WAV/G.722/MP3 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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# DGX-Spark-Variante von vllm_omni/deploy/qwen3_tts.yaml (vllm-omni 0.30.0):
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# * model_runner v1 statt v2 -- MRV2 importiert RoutedExpertsTensors, das im
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# vLLM-dev-Build des Images (vllm-node-030-omni) fehlt -> ImportError.
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# * gpu_memory_utilization 0.08 / 0.06 statt 2x 0.3 (Unified Memory ist geteilt).
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# * max_num_seqs 8 statt 64.
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#
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# Qwen3-TTS deploy: talker → code2wav via shared-memory chunk streaming.
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# Verified on 1x H100.
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#
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# Runner selection:
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# Model Runner V2 (MRV2) is EXPERIMENTAL and is the default runner on CUDA
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# for this model. Set `model_runner: v1` to opt out. The `platforms:`
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# sections at the end of this file keep V1 on NPU, XPU, ROCm and MUSA.
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# See docs/configuration/stage_configs.md ("Qwen3-TTS with Model Runner V2").
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#
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# Fields omitted from a stage fall back to StageDeployConfig defaults (see
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# vllm_omni/config/stage_config.py). Notable choices for this model:
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# * Stage 0 (talker) sets max_num_batched_tokens=512 for async-chunk
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# latency tuning (not correctness) — small per-step batches keep
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# first-chunk latency low, and the MRV2 profiles rely on that bound.
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# * Stage 1 (code2wav) sets max_num_batched_tokens=65536 for correctness:
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# codec prefill length (Q * num_frames) exceeds the 32k default.
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# * Stage 0 does not set enforce_eager — talker runs cudagraph by default.
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# Stage 1 defaults to false so Code2Wav can use its inner cudagraph;
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# set true to disable that path in eager mode.
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model_runner: v1
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async_chunk: true
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connectors:
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connector_of_shared_memory:
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name: SharedMemoryConnector
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extra:
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codec_streaming: true
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connector_get_sleep_s: 0.01
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connector_get_max_wait_first_chunk: 3000
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connector_get_max_wait: 300
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# Must match the decoder sliding attention window.
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codec_chunk_frames: 25
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codec_left_context_frames: 72
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# Emit only the first audio chunk early, then return to codec_chunk_frames.
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initial_codec_chunk_frames: 1
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# Chunk ramp (opt-in): gradual size increase for first N chunks to
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# eliminate the IC→steady cliff (1→25). Uncomment to enable.
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# Each entry is the size of that chunk index; indices past the table
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# fall back to codec_chunk_frames. When enabled, ramp overrides
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# initial_codec_chunk_frames (including the per-request API field).
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# Example:
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# codec_chunk_ramp: [4, 4, 8, 16, 25]
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# Adaptive chunk ramp (opt-in, takes precedence over fixed codec_chunk_ramp):
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# Chunk 0 uses dynamic IC; chunk 1+ sizes from live buffer-depth feedback.
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# Self-tunes across hardware (NPU/NVIDIA) and load conditions.
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# codec_chunk_adaptive: true
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# codec_chunk_min_frames: 2
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# Code2Wav decode + transfer margin
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# codec_chunk_safety_margin_ms: 50
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# EWMA->delta divisor (delta=max(delta_min, int(ewma/divisor))); higher=gentler ramp
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# codec_chunk_ramp_divisor: 15
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# min chunk-size growth per emit
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# codec_chunk_ramp_delta_min: 2
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# Decoder CUDA Graph sizing:
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# * async_chunk=true derives all stateful ICL/xvec shapes from
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# codec_chunk_ramp when enabled, otherwise from
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# initial_codec_chunk_frames, codec_chunk_frames, and sliding_window;
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# decode_cudagraph_capture_sizes is ignored in this mode.
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# * async_chunk=false captures stateless shapes 150 and
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# decode_chunk_frames + decode_left_context_frames (325 by default).
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# Extra stateless shapes may be added (union, not intersection) with:
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# decode_cudagraph_capture_sizes: [97, 400]
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# Graph batch size defaults to 1. Add larger buckets only when needed:
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# decode_cudagraph_batch_sizes: [1, 2, 4]
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# Limit eager batches to reduce temporary stateful cache allocations; CUDA Graph batching uses the buckets above.
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decode_batch_max_size: 4
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stages:
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- stage_id: 0
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max_num_seqs: 8
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gpu_memory_utilization: 0.08
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trust_remote_code: true
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# Omni prefix cache (reuse of talker codec rows on shared prefixes). Off
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# by default; set true when text repeats across requests (same voice or
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# shared ref_audio). The talker opts out of hidden-state caching and
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# defers codes.audio writes, so per-step cost is small. Stage 1 (codec
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# decoder) is not a supported prefix-cache stage: keep it false there.
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# See docs/design/feature/prefix_caching.md for the stage matrix.
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enable_prefix_caching: false
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async_scheduling: true
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# Bound per-step prefill work (validated MRV2 basic profile). Small
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# per-step batches keep first-chunk latency low.
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max_num_batched_tokens: 512
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max_model_len: 4096
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devices: "0"
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output_connectors:
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to_stage_1: connector_of_shared_memory
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default_sampling_params:
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temperature: 0.9
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top_k: 50
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max_tokens: 4096
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# Official qwen-tts generates the talker with min_new_tokens=2; without
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# it, checkpoints that sample codec EOS on the first frame return empty
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# audio (HTTP 400). See #4962.
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min_tokens: 2
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repetition_penalty: 1.05
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# Suppress codebook-0 silence tokens for the first N decode frames of a
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# request (#4966). Applies to every request on this stage, so intended
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# for x-vector-only (Base voice-clone) deploys. 0 = off.
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silence_ban_frames: 0
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subtalker_sampling_params:
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do_sample: true
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temperature: 0.9
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top_k: 50
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top_p: 1.0
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- stage_id: 1
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# Decoder compute dtype on GPU/NPU; 310P requires FP16 and overrides this.
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dtype: bfloat16
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# Tuned for Base voice clone; CustomVoice / VoiceDesign are TTFA-optimal at 1.
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max_num_seqs: 8
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gpu_memory_utilization: 0.06
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enforce_eager: false
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trust_remote_code: true
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enable_prefix_caching: false
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async_scheduling: true
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# Must be divisible by num_code_groups and cover (left_context + chunk).
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# Prefill length is Q * num_frames (e.g. 16 * 2148 = 34368); keep
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# headroom past 32k.
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max_num_batched_tokens: 65536
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# async_chunk appends windows per step; max_model_len must cover the
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# accumulated flat codec stream.
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max_model_len: 65536
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devices: "0"
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input_connectors:
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from_stage_0: connector_of_shared_memory
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default_sampling_params:
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temperature: 0.0
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top_p: 1.0
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top_k: -1
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max_tokens: 65536
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repetition_penalty: 1.0
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platforms:
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rocm:
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# MRV2 is not qualified on ROCm; keep the legacy V1 runner.
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model_runner: v1
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stages:
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- stage_id: 1
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# MIOpen Conv1d cannot be invoked while vLLM captures the outer
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# Code2Wav model graph. Keep CUDA's graph-enabled default, but run
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# Stage 1 eager on ROCm so decoder convolutions execute normally.
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enforce_eager: true
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npu:
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model_runner: v1
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stages:
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- stage_id: 0
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enforce_eager: false
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compilation_config:
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cudagraph_mode: PIECEWISE
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- stage_id: 1
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compilation_config:
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cudagraph_mode: PIECEWISE
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xpu:
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model_runner: v1
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musa:
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model_runner: v1
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