Yukim1andHongsheng Liu
793d3e9ab7
Signed-off-by: zwhzzz0821 <2831474076@qq.com> Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""MammothModa2 pipeline topology (frozen).
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Stage 0: AR — multimodal understanding + latent generation
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Stage 1: DiT — latent → image
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For text/image understanding tasks (text output only), use MAMMOTH_MODA2_AR_PIPELINE.
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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.mammoth_moda2"
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MAMMOTH_MODA2_PIPELINE = PipelineConfig(
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model_type="mammoth_moda2",
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default_deploy_config_name="mammoth_moda2.yaml",
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model_arch="MammothModa2ForConditionalGeneration",
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hf_architectures=("Mammothmoda2Model", "MammothModa2ForConditionalGeneration"),
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stages=(
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StagePipelineConfig(
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stage_id=0,
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model_stage="ar",
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execution_type=StageExecutionType.LLM_AR,
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input_sources=(),
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final_output=False,
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owns_tokenizer=True,
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requires_multimodal_data=True,
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engine_output_type="latent",
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),
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StagePipelineConfig(
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stage_id=1,
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model_stage="dit",
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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="image",
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owns_tokenizer=False,
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requires_multimodal_data=False,
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engine_output_type="image",
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custom_process_input_func=f"{_PROC}.ar2dit",
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),
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),
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)
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# Single-stage AR variant for understanding / summarization tasks
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MAMMOTH_MODA2_AR_PIPELINE = PipelineConfig(
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model_type="mammoth_moda2_ar",
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default_deploy_config_name="mammoth_moda2_ar.yaml",
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model_arch="MammothModa2ForConditionalGeneration",
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stages=(
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StagePipelineConfig(
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stage_id=0,
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model_stage="ar",
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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="text",
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owns_tokenizer=True,
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requires_multimodal_data=True,
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engine_output_type="text",
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),
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),
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)
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