[Bugfix][Spec Decode] Wire draft_probs into probabilistic draft_model rejection

[bedeks]

Purpose

Fixes #40149 by wiring draft-model proposal probabilities through the legacy V1 speculative decoding path when rejection_sample_method="probabilistic".

Previously, GPUModelRunner._sample() passed None for draft_probs, which forced the rejection sampler onto its no-draft-probs fallback instead of using the draft model’s actual proposal distribution. This change captures draft probabilities in the proposer, preserves them across the runner boundary, realigns them by request, and passes them into RejectionSampler so probabilistic rejection sampling can use the intended p(x) / q(x) logic for draft_model.

Test Plan

• .venv/bin/python -m py_compile tests/v1/spec_decode/test_eagle.py tests/v1/worker/test_gpu_model_runner.py vllm/v1/spec_decode/eagle.py vllm/v1/worker/gpu_model_runner.py
• .venv/bin/python -m pytest tests/v1/worker/test_gpu_model_runner.py -k reordered_draft_probs -v
• .venv/bin/python -m pytest tests/v1/spec_decode/test_eagle.py -k probabilistic_draft_probs -v
• Manual GPU validation on equivalent code:
  • compared baseline vs fixed probabilistic draft-model acceptance on Qwen/Qwen3-1.7B + Qwen/Qwen3-0.6B

Test Result

• py_compile: passed
• tests/v1/worker/test_gpu_model_runner.py -k reordered_draft_probs -v
  • verifies that runner-side cached draft_probs are reordered and sliced correctly before being passed to RejectionSampler
• tests/v1/spec_decode/test_eagle.py -k probabilistic_draft_probs -v
  • verifies that the proposer captures the expected per-step draft probabilities in probabilistic mode
• Manual GPU validation on an L40S with equivalent code showed consistent improvement in speculative acceptance:
  • run 1: acceptance_rate 0.2207 -> 0.4512, acceptance_len 1.6620 -> 2.3535
  • run 2: acceptance_rate 0.2207 -> 0.4491, acceptance_len 1.6620 -> 2.3474
  • run 3: acceptance_rate 0.2255 -> 0.4551, acceptance_len 1.6766 -> 2.3653

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[claude]

Claude Code Review

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[gemini-code-assist]

Code Review

This pull request implements support for probabilistic rejection sampling within the V1 speculative decoding framework, specifically targeting the Eagle proposer. Key changes include the addition of logic to capture and cache draft probabilities during the proposal phase in EagleProposer and GPUModelRunner, ensuring these probabilities are correctly reordered and passed to the rejection sampler. New unit tests were added to verify that draft probabilities are accurately stored and handled across different request batches. I have no feedback to provide as there are no review comments to assess.

[benchislett]

Thanks, this looks great! Just left one question

[mergify]

Hi @bedeks, the pre-commit checks have failed. Please run:

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pre-commit run --all-files

Then, commit the changes and push to your branch.

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[repne]

Thank you @bedeks for the PR. Five or so days ago the logic around draft_model rejection method was changed, so the PR requires some update. See #40651

[bedeks]

@benchislett could you please take a look again?

[benchislett]

One nitpick around the use of "gumbel" in MRV1 but otherwise LGTM!

[benchislett]

Thanks!

[bedeks]

@benchislett looks like the failing test is flaky and had to be retried on previously merged prs too. Could you help retry the failing test please?