87 lines
3.3 KiB
Python
87 lines
3.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
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"""CosyVoice3 pipeline topology (frozen).
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Stage 0: Talker — text prompt → speech tokens (LLM autoregressive).
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Stage 1: Code2Wav — flow-matching decoder → acoustic features → waveform.
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* ``sync_process_input_func`` (``text2flow_token_only``) runs when
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``deploy.async_chunk=false``: stage 1 allocates placeholder slots while
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bulk tensors arrive via ``text2flow_full_payload`` on the connector.
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* ``async_chunk_process_next_stage_input_func`` runs when
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``deploy.async_chunk=true``: stage 0 streams codec chunks to stage 1
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through the shared-memory connector.
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"""
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import shutil
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from dataclasses import replace
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from transformers import PretrainedConfig
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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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from vllm_omni.transformers_utils.configs.cosyvoice3 import CosyVoice3Config
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_PROC = "vllm_omni.model_executor.stage_input_processors.cosyvoice3"
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COSYVOICE3_PIPELINE = PipelineConfig(
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model_type="cosyvoice3",
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default_deploy_config_name="cosyvoice3.yaml",
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model_arch="CosyVoice3Model",
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stages=(
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StagePipelineConfig(
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stage_id=0,
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model_stage="cosyvoice3_talker",
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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}.talker2code2wav_async_chunk"),
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custom_process_next_stage_input_func=f"{_PROC}.text2flow_full_payload",
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sampling_constraints={
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# Standard sampling can emit any of the 200 control tokens.
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# RAS merges their logits into 6562, which is also in this range.
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"stop_token_ids": list(range(6561, 6761)),
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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="cosyvoice3_code2wav",
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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="latent",
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sync_process_input_func=f"{_PROC}.text2flow_token_only",
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requires_full_payload_input=True,
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),
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),
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)
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def resolve_cosyvoice3_pipeline(hf_config: PretrainedConfig | None = None) -> PipelineConfig | None:
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"""Select a streaming default compatible with the device and runtime.
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Query the platform through NVML without initializing CUDA in the parent.
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Explicit deploy configs still take precedence over this pipeline default.
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"""
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from vllm.platforms import current_platform
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if hf_config is not None and not isinstance(hf_config, CosyVoice3Config):
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return None
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if current_platform.is_cuda():
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capability = current_platform.get_device_capability()
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if (
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capability is not None
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and capability.major == 9
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and current_platform.get_device_total_memory() >= 140 * 1024**3
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and shutil.which("nvidia-cuda-mps-control") is not None
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):
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return replace(
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COSYVOICE3_PIPELINE,
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default_deploy_config_name="cosyvoice3_packed_streaming_optimized_standard.yaml",
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)
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return COSYVOICE3_PIPELINE
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