[Recipe] Add Fish Speech S2 Pro 2-GPU deploy profile (#3323)
Signed-off-by: Yueqian Lin <linyueqian@outlook.com>
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# Fish Speech S2 Pro 2-GPU deploy: Stage0 AR on GPU 0, Stage1 DAC on GPU 1.
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#
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# Opt-in profile validated on H100x2. Compared with the single-GPU default
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# (``fish_qwen3_omni.yaml``), it splits AR and DAC across devices to remove
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# AR/DAC contention, enlarges Stage0 AR batching, and lets Stage1 consume
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# multiple DAC chunks in parallel.
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#
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# Select via:
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# CUDA_VISIBLE_DEVICES=0,1 vllm serve fishaudio/s2-pro --omni \
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# --deploy-config vllm_omni/deploy/fish_qwen3_omni_2gpu.yaml
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#
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# Or programmatically:
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# Omni(model="fishaudio/s2-pro",
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# deploy_config_path="vllm_omni/deploy/fish_qwen3_omni_2gpu.yaml")
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async_chunk: true
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enable_chunked_prefill: false
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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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shm_threshold_bytes: 65536
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codec_streaming: true
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# Tightened from 10ms to 1ms: chunks become available sooner under
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# cross-GPU pipelining, so connector idle waiting dominates if left high.
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connector_get_sleep_s: 0.001
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connector_get_max_wait_first_chunk: 3000
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connector_get_max_wait: 300
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# ~21 Hz codec; 25 frames ≈ 1.16s of audio.
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codec_chunk_frames: 25
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codec_left_context_frames: 25
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initial_codec_chunk_frames: 4
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stages:
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- stage_id: 0
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max_num_seqs: 64
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gpu_memory_utilization: 0.75
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enforce_eager: false
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async_scheduling: false
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# vLLM scheduler requires max_num_batched_tokens >= max_model_len when
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# chunked prefill is off (SlowAR decode loop isn't chunked-prefill-safe).
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max_num_batched_tokens: 16384
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max_model_len: 16384
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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: 0.8
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top_k: 30
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top_p: 0.9
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max_tokens: 2048
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seed: 42
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repetition_penalty: 1.0
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- stage_id: 1
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max_num_seqs: 64
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gpu_memory_utilization: 0.2
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enforce_eager: true
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async_scheduling: false
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max_num_batched_tokens: 16384
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max_model_len: 16384
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devices: "1"
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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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seed: 42
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repetition_penalty: 1.0
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