[Bugfix][Model][CI/Build] Fix CUDA graph capture in GLM-OCR / GLM4-MoE-Lite MTP layers - #51966
[Bugfix][Model][CI/Build] Fix CUDA graph capture in GLM-OCR / GLM4-MoE-Lite MTP layers#51966bulatovv wants to merge 2 commits into
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… layers The MTP layers masked position-0 embeddings with an in-place boolean-mask assignment. Boolean-mask index_put_ calls nonzero(), which syncs device to host to size its output, and that is illegal during CUDA graph capture. The V2 model runner captures the MTP prefill graph, so engine startup died with cudaErrorStreamCaptureUnsupported. Use the capture-safe torch.where form already used by deepseek_mtp.py and glm4_moe_mtp.py. GLM-OCR keeps its existing positions[0] indexing: it is an MRoPE model, so positions has shape (3, seq_len) rather than (seq_len,). FIX vllm-project#48749 Co-authored-by: Claude Opus 5 <noreply@anthropic.com> Signed-off-by: Albert Fazlyev <albert.fz@yandex.ru>
Covers the CUDA graph capture crash fixed in the previous commit: without it the entry dies at glm_ocr_mtp.py while capturing prefill FULL graphs. The entry runs text-only with limit_mm_per_prompt zeroed, matching the Qwen3.5 and gemma-4 entries, and uses a 0.0 accuracy threshold because GSM8k is not meaningful for an OCR model; correctness is asserted by matching the speculative output against the non-speculative reference. This entry cannot pass on main until vllm-project#49869 lands: GLM-OCR MTP weights fail to load (vllm-project#49856), so the engine dies before graph capture is reached. Co-authored-by: Claude Opus 5 <noreply@anthropic.com> Signed-off-by: Albert Fazlyev <albert.fz@yandex.ru>
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Purpose
FIX #48749
GlmOcrMultiTokenPredictorLayer.forwardandGlm4MoeLiteMultiTokenPredictorLayer.forwardmask the position-0 embedding with an in-place boolean-mask assignment:
A boolean-mask
index_put_callsnonzero(), whose output shape is data-dependent, so itsynchronizes device to host to size the allocation. That is not allowed inside an active
CUDA graph capture, and the V2 model runner captures the MTP prefill graph
(
speculator.capture()->prefill_cudagraph_manager.capture()), so engine startup fails:It was reported on A100-SXM4-80GB in #48749.
The equivalent capture-safe form is already used by the other two MTP implementations:
vllm/model_executor/models/deepseek_mtp.py:113vllm/model_executor/models/glm4_moe_mtp.py:113both of which read
inputs_embeds = torch.where(positions.unsqueeze(-1) == 0, 0, inputs_embeds).This PR applies the same form to the two remaining implementations. GLM-OCR keeps
positions[0]because it is an MRoPE model, wherepositionshas shape(3, seq_len).Duplicate-work checks were performed before opening: no open PR references #48749 or
touches
glm_ocr_mtp.py. #39483 and #43747 fix different code paths that surface the sameCUDA error.
Related: #49869 fixes an unrelated GLM-OCR MTP weight-loading regression (#49856). On main
as of 3ee2df3 with the HF checkpoint, startup fails there before reaching graph capture,
so that patch was applied locally to reproduce this crash. The crash fixed here reproduces
with no local patches on v0.25.1. The two fixes are independent and can merge in either
order.
Test Plan
Adds a GLM-OCR entry to
tests/v1/e2e/spec_decode/mtp/test_mtp.py, covering engine startupand CUDA graph capture with MTP for this model.
The entry will fail in CI until #49869 lands, because GLM-OCR MTP weights fail to load
(#49856) and the engine dies before reaching graph capture. It was run locally with that
patch applied, before and after the fix:
Test Result
cudaErrorStreamCaptureUnsupportedatglm_ocr_mtp.py:87while capturing prefill FULL graphsexact text matches=100/100num_speculative_tokens: 3pre-commit: all hooks passed on the three changed files.
AI assistance
AI assistance was used to investigate the stream-capture failure, implement this change,
run validation, and prepare this PR.