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[Bugfix] Fix handling of image embeds in models (#29480)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
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Cyrus Leung 2025-11-26 21:00:15 +08:00 committed by GitHub
parent 452a7c9f7c
commit e30859dff3
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3 changed files with 4 additions and 15 deletions
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15
vllm/model_executor/models/deepseek_vl2.py
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@ -48,7 +48,6 @@ from vllm.transformers_utils.configs.deepseek_vl2 import (
)
from vllm.transformers_utils.processors.deepseek_vl2 import DeepseekVLV2Processor
from vllm.transformers_utils.tokenizer import cached_tokenizer_from_config
from vllm.utils.collection_utils import is_list_of
from vllm.utils.tensor_schema import TensorSchema, TensorShape
from vllm.utils.torch_utils import set_default_torch_dtype
@ -595,19 +594,9 @@ class DeepseekVLV2ForCausalLM(nn.Module, SupportsMultiModal, SupportsPP):
def _process_image_input(
self, image_input: DeepseekVL2ImageInputs
) -> list[torch.Tensor]:
) -> torch.Tensor | list[torch.Tensor]:
if image_input["type"] == "image_embeds":
image_data = image_input["data"]
if is_list_of(image_data, torch.Tensor):
# it's already a list of tensors
return image_data
if len(image_data.shape) == 3:
# 3D tensor
return list(torch.unbind(image_data, dim=0))
raise ValueError(
"We expect batched 2D tensors; "
"this can be either a list of 2D tensors or a single 3D tensor."
)
return image_input["data"]
pixel_values = image_input["data"]
images_spatial_crop = image_input["images_spatial_crop"]

2
vllm/model_executor/models/llava_next.py
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@ -460,7 +460,7 @@ class LlavaNextForConditionalGeneration(nn.Module, SupportsMultiModal, SupportsP
image_input: LlavaNextImageInputs,
) -> torch.Tensor | list[torch.Tensor]:
if image_input["type"] == "image_embeds":
return [image_input["data"]]
return image_input["data"]
patch_embeddings = self._process_image_pixels(image_input)

2
vllm/model_executor/models/llava_onevision.py
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@ -763,7 +763,7 @@ class LlavaOnevisionForConditionalGeneration(nn.Module, SupportsMultiModal, Supp
image_input: LlavaOnevisionImageInputs,
) -> torch.Tensor | list[torch.Tensor]:
if image_input["type"] == "image_embeds":
return [image_input["data"]]
return image_input["data"]
patch_embeddings = self._process_image_pixels(image_input)