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[Model] vllm v1 support mlp_speculator #20655

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@skylee-01 skylee-01 commented Jul 9, 2025

Essential Elements of an Effective PR Description Checklist

  • The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
  • The test plan, such as providing test command.
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  • (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

Purpose

vllm v1 support mlp_speculator

Test Plan

Test Result

(Optional) Documentation Update

Signed-off-by: skylee-01 <497627264@qq.com>
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Summary of Changes

Hello @skylee-01, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces comprehensive support for mlp_speculator as a new speculative decoding method in vLLM v1. It involves updating configuration utilities to recognize the new method, adapting the MLPSpeculator model for its role as a draft model, and integrating a dedicated proposer class into the GPU model runner to manage the generation of speculative tokens.

Highlights

  • New Speculative Decoding Method: Added support for "mlp_speculator" as a new speculative decoding method within vLLM v1, allowing its configuration and use.
  • MLPSpeculator Model Adaptation: Modified the MLPSpeculator model's initialization to correctly handle configurations when used as a draft model in speculative decoding, and adjusted its generate_proposals method for conditional sampling_metadata usage.
  • New Proposer Class: Introduced MLPSpeculatorProposer (vllm/v1/spec_decode/mlp_speculator.py) to encapsulate the logic for generating draft tokens specifically for the MLPSpeculator model.
  • Integration into GPU Model Runner: Integrated MLPSpeculatorProposer into GPUModelRunner to enable the mlp_speculator method, including the necessary data preparation and call flow for proposing draft tokens.
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Code Review

This pull request adds support for mlp_speculator in vLLM v1. The changes are in the right direction, but I've found several critical issues related to the integration with the v1 engine, particularly in vllm/model_executor/models/mlp_speculator.py and vllm/v1/worker/gpu_model_runner.py. These issues could lead to runtime errors or incorrect behavior. I've provided detailed suggestions to fix them. Addressing these points will be important for the stability of this new feature.

Comment on lines +73 to +78
if hasattr(vllm_config, 'speculative_config'):
config = vllm_config.speculative_config.draft_model_config.hf_config
self.sampling_metadata_is_required = False
else:
config = vllm_config.model_config.hf_config
self.sampling_metadata_is_required = True
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critical

The logic to differentiate between v0 and v1 paths is incomplete. For the v1 path (hasattr(vllm_config, 'speculative_config')), self.sampler and self.logits_processor are still initialized with v0 components at the end of __init__ (lines 147-149), which will cause a crash due to type mismatches with SamplingMetadata.

To fix this, the initialization of sampler and logits_processor should be moved inside this if/else block. For the v1 path, self.sampler should be an instance of vllm.v1.sample.sampler.Sampler and self.logits_processor should be None.

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skylee-01 added 5 commits July 9, 2025 10:45
Signed-off-by: skylee-01 <497627264@qq.com>
Signed-off-by: skylee-01 <497627264@qq.com>
Signed-off-by: skylee-01 <497627264@qq.com>
Signed-off-by: skylee-01 <497627264@qq.com>
Signed-off-by: skylee-01 <497627264@qq.com>
@skylee-01
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How should pre-commit be handled?
image

@skylee-01
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Hi Curys, please help me review this PR. Thank you very much. @DarkLight1337

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@WoosukKwon can you review this? I'm not that familiar with spec decode code

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Teacher, could you please help me take a look at this pull request? @WoosukKwon

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Teacher Lily, please help me review it. @LiuXiaoxuanPKU

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