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[BugFix][Multi Modal] Fix TensorSchema shape mismatch in Molmo #24559

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Merged
vllm-bot merged 2 commits into from
Sep 10, 2025
+8 −6
Merged

[BugFix][Multi Modal] Fix TensorSchema shape mismatch in Molmo #24559

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c697b40
fix shape mismatch
wwl2755 Sep 10, 2025
571ffea
fix comment
wwl2755 Sep 10, 2025
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14 changes: 8 additions & 6 deletions vllm/model_executor/models/molmo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,20 +76,22 @@ class MolmoImageInputs(TensorSchema):
"""
Dimensions:
- bn: Batch size * number of images
- nc: Number of crops
- nc: Number of crops (dynamic)
- np: Number of patches
- tp: Token sequence positions
- pd: Patch dimension
"""
images: Annotated[Union[torch.Tensor, list[torch.Tensor]],
TensorShape("bn", "nc", "np", "pd")]
TensorShape("bn", "nc", "np", "pd", dynamic_dims={"nc"})]
# Number of crops may vary per batch and image, so pass it as a list.

image_masks: Annotated[Optional[Union[torch.Tensor, list[torch.Tensor]]],
TensorShape("bn", "nc", "np")]
TensorShape("bn", "nc", "np", dynamic_dims={"nc"})]

feat_is_patch: Annotated[Union[torch.Tensor, list[torch.Tensor]],
TensorShape("bn", "nc", "np")]
feat_is_patch: Annotated[
Union[torch.Tensor, list[torch.Tensor]],
TensorShape("bn", "nc", "tp", dynamic_dims={"nc"})]
Comment on lines +91 to +93
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@gemini-code-assist gemini-code-assist bot Sep 10, 2025

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high

The number of token sequence positions (tp) can also be dynamic for different images, similar to the number of crops (nc). The number of tokens depends on the image's height and width. To prevent potential ValueError during tensor shape validation when processing a batch of images with varying sizes, tp should also be marked as a dynamic dimension.

Suggested change
feat_is_patch: Annotated[
Union[torch.Tensor, list[torch.Tensor]],
TensorShape("bn", "nc", "tp", dynamic_dims={"nc"})]
feat_is_patch: Annotated[
Union[torch.Tensor, list[torch.Tensor]],
TensorShape("bn", "nc", "tp", dynamic_dims={"nc", "tp"})]

# A boolean mask indicating which image features correspond to patch tokens.

num_crops: Annotated[torch.Tensor, TensorShape("bn")]


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