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@khluu khluu commented Nov 7, 2025

Revert #27538 since it's breaking Multi-Modal Test Extended 3

Signed-off-by: Kevin H. Luu <[email protected]>
@khluu khluu requested a review from DarkLight1337 November 7, 2025 09:58
@khluu khluu added the ready ONLY add when PR is ready to merge/full CI is needed label Nov 7, 2025
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Code Review

This pull request correctly reverts a previous change that introduced a regression in the multi-modal test suite for Gemma3 models. The revert ensures the proper ordering of newline tokens during placeholder replacement, which is critical for the correct functioning of multi-modal processing.

def get_repl_toks(tok: int) -> list[int]:
if tok == newline_3:
return [newline_2, newline_1]
return [newline_1, newline_2]
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high

The change from [newline_2, newline_1] to [newline_1, newline_2] is crucial for correctly decomposing the newline_3 token (\n\n\n). While _apply_token_matches (lines 370-380) handles both permutations as equivalent for combining into newline_3, the _find_mm_placeholders function, which uses this decomposition, relies on a specific order for accurate matching of multi-modal placeholders. The previous incorrect order led to a breaking test, highlighting the sensitivity of the system to this sequence. It would be beneficial to add a comment explaining why this specific order is required for decomposition, given that combination is order-agnostic, to prevent future regressions.

Suggested change
return [newline_1, newline_2]
return [newline_1, newline_2] # Decompose as '\n' then '\n\n' for consistent placeholder matching

@khluu khluu enabled auto-merge (squash) November 7, 2025 10:53
@khluu khluu merged commit 8e19d47 into main Nov 7, 2025
59 of 61 checks passed
@khluu khluu deleted the khluu/revert_gemma3 branch November 7, 2025 12:09
ZhengHongming888 pushed a commit to ZhengHongming888/vllm that referenced this pull request Nov 8, 2025
xuebwang-amd pushed a commit to xuebwang-amd/vllm that referenced this pull request Nov 13, 2025
devpatelio pushed a commit to SumanthRH/vllm that referenced this pull request Nov 29, 2025
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3 participants