Yueqian LinandSYLAR
3f504b45d2
Signed-off-by: Yueqian Lin <linyueqian@outlook.com> Co-authored-by: SYLAR <125541396+lishunyang12@users.noreply.github.com>
52 lines
1.8 KiB
Python
52 lines
1.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Fish Speech S2 Pro pipeline topology (frozen).
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Stage 0: slow_ar — text → RVQ codec tokens (LLM autoregressive).
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Stage 1: dac_decoder — RVQ tokens → audio waveform (LLM_GENERATION).
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The HF config top-level reports ``model_type = "fish_qwen3_omni"`` (the
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OmniConfig that bundles slow-AR and fast-AR sub-configs), which is why the
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registry key follows the HF name rather than the human-readable "fish_speech".
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"""
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from vllm_omni.config.stage_config import (
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PipelineConfig,
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StageExecutionType,
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StagePipelineConfig,
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)
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_PROC = "vllm_omni.model_executor.stage_input_processors.fish_speech"
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FISH_SPEECH_PIPELINE = PipelineConfig(
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model_type="fish_qwen3_omni",
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model_arch="FishSpeechSlowARForConditionalGeneration",
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stages=(
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StagePipelineConfig(
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stage_id=0,
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model_stage="fish_speech_slow_ar",
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execution_type=StageExecutionType.LLM_AR,
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input_sources=(),
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owns_tokenizer=True,
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engine_output_type="latent",
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async_chunk_process_next_stage_input_func=(f"{_PROC}.slow_ar_to_dac_decoder_async_chunk"),
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sampling_constraints={
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"detokenize": False,
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# <|im_end|> — stop when the model emits end-of-turn.
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"stop_token_ids": [151645],
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},
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),
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StagePipelineConfig(
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stage_id=1,
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model_stage="dac_decoder",
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model_arch="FishSpeechDACDecoder",
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execution_type=StageExecutionType.LLM_GENERATION,
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input_sources=(0,),
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final_output=True,
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final_output_type="audio",
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engine_output_type="audio",
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sampling_constraints={"detokenize": True},
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),
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),
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)
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