A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 15, 09:45 UTC
[Bugfix] Fix MRoPE Errors in the Qwen-VL Model When Processing Pure Text (#18407)
Co-authored-by: 松灵 <wpf272043@alibaba-inc.com>
燃 committed
May 20, 2025 at 21:59 UTC
be48360c1fb9284804f9e1cae23b58e23e762877
1 file changed
-8
vllm/worker/model_runner.py
-8
@@ -729,8 +729,6 @@ class ModelInputForGPUBuilder(ModelRunnerInputBuilderBase[ModelInputForGPU]):
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mm_kwargs, placeholder_maps = MultiModalPlaceholderMap.from_seq_group(
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seq_group_metadata,
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range(positions[0], positions[0] + len(positions)))
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- if not mm_kwargs:
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- return
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inter_data.multi_modal_kwargs = mm_kwargs
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inter_data.multi_modal_placeholder_maps = placeholder_maps
@@ -741,12 +739,6 @@ class ModelInputForGPUBuilder(ModelRunnerInputBuilderBase[ModelInputForGPU]):
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video_grid_thw = mm_kwargs.get("video_grid_thw", None)
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audio_feature_lengths = mm_kwargs.get("audio_feature_lengths",
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None)
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- assert (
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- image_grid_thw is not None or video_grid_thw is not None
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- or audio_feature_lengths is not None), (
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- "mrope embedding type requires multi-modal input mapper "
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- "returns 'image_grid_thw' or 'video_grid_thw' or "
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- "'audio_feature_lengths'.")
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second_per_grid_ts = mm_kwargs.get("second_per_grid_ts", None)
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use_audio_in_video = mm_kwargs.get("use_audio_in_video", False)