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[Bugfix] Fix Gemma4 audio crash with variable-length batched inputs - #47459
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batched() only stacks items of equal shape, so when concurrent audio requests have different lengths it returns a list of per-clip tensors instead of a stacked tensor. _process_audio_input called .squeeze(1) on that list and raised AttributeError, which killed the engine. Pad the features and masks to the batch max before the audio tower, which already takes a padded batch plus a validity mask. Add regression tests for the list reduce and the padding. Signed-off-by: Fikri Karim <fkfikrikarim@gmail.com>
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This seems to be fixed by #50958 |
Purpose
When two audio requests with different lengths are batched into one step,
MultiModalFieldConfig.batched()returns a list of per-clip tensors instead of a stacked tensor (it only stacks items of equal shape)._process_audio_inputassumed a stacked tensor and called.squeeze(1)on the list, raisingAttributeErrorand taking down the engine.Pad the variable-length features and masks to the batch max before the audio tower, which already takes a padded batch plus a validity mask and strips the padding afterward. The single/equal-length tensor path is unchanged.
The same
batched()list case comes up in other audio models (ultravox, granite_speech, voxtral each pad and stack it separately), so this is a broader pattern; a shared helper or padded field variant would avoid handling it per model, but that's out of scope here.Test
Two CPU tests in
tests/models/multimodal/processing/test_gemma4.py, mirroring the existing image batching test: one checksbatched("audio")returns a list for variable-length clips, the other checks the padding and mask.