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[Bugfix] Fix MRoPE Errors in the Qwen-VL Model When Processing Pure Text #18526

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Merged
merged 3 commits into from
May 22, 2025
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[Bugfix] Fix MRoPE Errors in the Qwen-VL Model When Processing Pure Text #18526

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ba02e25
[Bugfix] Fix MRoPE Errors in the Qwen-VL Model When Processing Pure Text
May 22, 2025
bd3004e
Update vllm/worker/model_runner.py
DarkLight1337 May 22, 2025
c430224
Merge branch 'main' into fix_qwenvl_pure_text_error_v2
DarkLight1337 May 22, 2025
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11 changes: 4 additions & 7 deletions vllm/worker/model_runner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -729,7 +729,10 @@ def _compute_multi_modal_input(self, inter_data: InterDataForSeqGroup,
mm_kwargs, placeholder_maps = MultiModalPlaceholderMap.from_seq_group(
seq_group_metadata,
range(positions[0], positions[0] + len(positions)))
if not mm_kwargs:

# M-RoPE requires mrope_positions even for plain text; return early
# when mm_kwargs is empty only if inter_data.is_prompt is False.
if not mm_kwargs and not inter_data.is_prompt:
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is this effectively equivalent to checking whether self.runner.model_config.uses_mrope?

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No, the two do not appear to be equivalent. During the prefill stage (the first step), mm_kwargs is non-empty, but it becomes an empty dictionary during the next generation phase. The issue arises when processing pure text, where mm_kwargs is empty, and mrope_positions cannot be assigned correct values.

I think the purpose of this condition is to facilitate an early exit during the generation phase.

image

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oh yeah I get that, I was actually referring to and not inter_data.is_prompt, whether it was more accurate to replace with:

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if not mm_kwargs and not inter_data.is_prompt:
if not mm_kwargs and not self.runner.model_config.uses_mrope:

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@DarkLight1337 DarkLight1337 May 22, 2025 •
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self.runner.model_config.uses_mrope is a static value based on the model config, whereas inter_data.is_prompt can differ for each iteration.

return

inter_data.multi_modal_kwargs = mm_kwargs
Expand All @@ -741,12 +744,6 @@ def _compute_multi_modal_input(self, inter_data: InterDataForSeqGroup,
video_grid_thw = mm_kwargs.get("video_grid_thw", None)
audio_feature_lengths = mm_kwargs.get("audio_feature_lengths",
None)
assert (
image_grid_thw is not None or video_grid_thw is not None
or audio_feature_lengths is not None), (
"mrope embedding type requires multi-modal input mapper "
"returns 'image_grid_thw' or 'video_grid_thw' or "
"'audio_feature_lengths'.")

second_per_grid_ts = mm_kwargs.get("second_per_grid_ts", None)
use_audio_in_video = mm_kwargs.get("use_audio_in_video", False)
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