[Bugfix][Spec Decode] Skip uniform spec-decode padding for diffusion models

[kl527]

Purpose

Fix a deterministic engine-core crash for diffusion models (model_config.is_diffusion) caused by the scheduler's uniform spec-decode padding.

The waiting-path padding promotes any request needing exactly 1 token to 1 + num_spec_tokens so decode batches stay uniform for full CUDA graphs. For AR speculative decoding this is harmless — the placeholder drafts simply fail verification. For diffusion models, spec tokens are the fixed-size denoising canvas, not rejectable drafts, so the padded span overflows the canvas and crashes the engine core:

RuntimeError: The size of tensor a (257) must match the size of tensor b (256) at non-singleton dimension 1

How this is reached in practice: under KV-cache pressure, a preempted diffusion request resumes via the waiting queue and prefix-caches against its own previously committed blocks at block-size granularity. Whenever prompt_len % block_size == 1, the resumed request needs exactly 1 token and gets padded. We hit this deterministically with DiffusionGemma-26B (canvas 256) under KV-pressure preemption: a 129-token prompt with 16-token blocks resumes needing 129 − 128 = 1 token, and the engine crashed identically on 3 consecutive runs, always on the same request.

The fix gates the padding on num_sampled_tokens_per_step > 0. The scheduler's own __init__ already sets this field to 0 iff model_config.is_diffusion, and other diffusion special cases in this file already key on it, so this is a one-condition change using the existing mechanism. AR behavior is unchanged.

Not a duplicate: searched open issues and PRs for this area. #47417 pads mixed running decode batches (extends padding for AR uniformity on a different code path — complementary, no hunk overlap); #42261 is an unrelated non-deterministic CUDA assert with MTP. No open issue or PR addresses spec-decode padding for diffusion models.

Test Plan

pytest tests/v1/core/test_scheduler.py -k spec_decode_padding -v

Adds test_spec_decode_padding_skipped_for_diffusion, mirroring the existing test_spec_decode_padding_first_decode_step (the AR case, which must keep padding and still passes).

Test Result

• Full file: pytest tests/v1/core/test_scheduler.py → 124 passed (CPU, macOS, Python 3.12).
• -k spec_decode_padding → 3 passed (the two existing AR padding tests are unchanged and still pass).
• Without the scheduler change, the new test fails as expected: assert 4 == 1 — the 1-token request is padded to 1 + num_spec_tokens.
• End-to-end on a fork carrying this same gate: the 3×-reproduced deterministic crash under KV-pressure preemption disappeared; 393 preemption+resume cycles and an AIME N=30 quality run subsequently completed with zero span anomalies.

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This PR was prepared with AI assistance (Claude Code); the submitting human has reviewed every changed line and run the tests above.

🤖 Generated with Claude Code

[claude]

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[njhill]

Thanks @kl527, LGTM!

[kl527]

Sounds good!

[njhill]

@kl527 please stop rebasing since it triggers a full new CI each time.