35cacf020c
Signed-off-by: Mengjie Zhao <zmj0129@gmail.com> Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com> Co-authored-by: Yueqian Lin <70319226+linyueqian@users.noreply.github.com>
46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Gepard-1.0 pipeline topology.
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Single-stage AR TTS. The Qwen3.5 backbone runs under paged attention, the 32
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codebook heads and the binary stop head are sampled inside the talker, and the
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NeMo NanoCodec decodes the accumulated frames outside vLLM.
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``compute_logits`` scatters head0 into vLLM's vocab-wide logits; head0's valid
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range is 0..7, so the synthetic STOP sentinel is 8. ``stop_token_ids=[8]``
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couples it to vLLM's stop machinery, with ``detokenize=False`` because head0 is
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an audio code. Same idiom as VoxCPM2/MOSS.
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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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# head0 valid range is 0..7 (its FSQ cardinality is 8); STOP is the sentinel
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# one past that range. Mirrors the reference config.py STOP_TOKEN = 8.
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_GEPARD_STOP_TOKEN_ID = 8
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GEPARD_PIPELINE = PipelineConfig(
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model_type="gepard",
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default_deploy_config_name="gepard.yaml",
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model_arch="GepardTalkerForConditionalGeneration",
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stages=(
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StagePipelineConfig(
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stage_id=0,
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model_stage="gepard",
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execution_type=StageExecutionType.LLM_AR,
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input_sources=(),
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final_output=True,
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final_output_type="audio",
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owns_tokenizer=True,
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engine_output_type="audio",
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sampling_constraints={
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"detokenize": False,
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"stop_token_ids": [_GEPARD_STOP_TOKEN_ID],
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},
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),
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),
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)
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