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[Misc] Factor out common _apply_feature_select_strategy #26003

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Merged
merged 1 commit into from
Oct 1, 2025
Merged

[Misc] Factor out common _apply_feature_select_strategy #26003

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19 changes: 3 additions & 16 deletions vllm/model_executor/models/llava.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@
from .siglip import SiglipVisionModel
from .utils import (AutoWeightsLoader, WeightsMapper, flatten_bn,
init_vllm_registered_model, maybe_prefix)
from .vision import get_vision_encoder_info
from .vision import get_num_selected_vision_tokens, get_vision_encoder_info


class LlavaImagePixelInputs(TensorSchema):
Expand Down Expand Up @@ -147,19 +147,6 @@ def get_hf_processor(self, **kwargs: object) -> LlavaLikeProcessor:
def get_supported_mm_limits(self) -> Mapping[str, Optional[int]]:
return {"image": None}

def _apply_feature_select_strategy(
self,
strategy: str,
encoder_num_image_tokens: int,
) -> int:
if strategy == "default":
return encoder_num_image_tokens - 1
if strategy == "full":
return encoder_num_image_tokens

msg = f"Unexpected feature select strategy: {strategy!r}"
raise NotImplementedError(msg)

def get_num_image_tokens(
self,
*,
Expand All @@ -169,12 +156,12 @@ def get_num_image_tokens(
hf_config = self.get_hf_config()
vision_encoder_info = self.get_vision_encoder_info()

return self._apply_feature_select_strategy(
hf_config.vision_feature_select_strategy,
return get_num_selected_vision_tokens(
vision_encoder_info.get_num_image_tokens(
image_width=image_width,
image_height=image_height,
),
hf_config.vision_feature_select_strategy,
)

def get_image_size_with_most_features(self) -> ImageSize:
Expand Down
5 changes: 3 additions & 2 deletions vllm/model_executor/models/llava_next.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,7 @@
from .siglip import SiglipVisionModel
from .utils import (AutoWeightsLoader, WeightsMapper, flatten_bn,
init_vllm_registered_model, maybe_prefix)
from .vision import get_num_selected_vision_tokens


class LlavaNextImagePixelInputs(TensorSchema):
Expand Down Expand Up @@ -95,12 +96,12 @@ def get_num_image_tokens(
hf_config = self.get_hf_config()
vision_encoder_info = self.get_vision_encoder_info()

base_feature_size = self._apply_feature_select_strategy(
hf_config.vision_feature_select_strategy,
base_feature_size = get_num_selected_vision_tokens(
vision_encoder_info.get_num_image_tokens(
image_width=image_width,
image_height=image_height,
),
hf_config.vision_feature_select_strategy,
)

num_patch_height, num_patch_width = get_anyres_image_grid_shape(
Expand Down
23 changes: 6 additions & 17 deletions vllm/model_executor/models/tarsier.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,8 @@
from .siglip import SiglipVisionModel
from .utils import (AutoWeightsLoader, flatten_bn, init_vllm_registered_model,
maybe_prefix)
from .vision import VisionEncoderInfo, get_vision_encoder_info
from .vision import (VisionEncoderInfo, get_num_selected_vision_tokens,
get_vision_encoder_info)


class TarsierImagePixelInputs(TensorSchema):
Expand Down Expand Up @@ -201,18 +202,6 @@ def get_hf_processor(self, **kwargs: object) -> TarsierProcessor:
def get_supported_mm_limits(self) -> Mapping[str, Optional[int]]:
return {"image": None}

def _apply_feature_select_strategy(
self,
strategy: str,
encoder_num_image_tokens: int,
) -> int:
if strategy == "default":
return encoder_num_image_tokens - 1
if strategy == "full":
return encoder_num_image_tokens
msg = f"Unexpected feature select strategy: {strategy!r}"
raise NotImplementedError(msg)

def get_num_image_tokens(
self,
*,
Expand All @@ -221,21 +210,21 @@ def get_num_image_tokens(
) -> int:
hf_config = self.get_hf_config()
vision_encoder_info = self.get_vision_encoder_info()
num_projected_patches = self._apply_feature_select_strategy(
hf_config.vision_feature_select_strategy,
num_projected_patches = get_num_selected_vision_tokens(
vision_encoder_info.get_num_image_tokens(
image_width=image_width,
image_height=image_height,
),
hf_config.vision_feature_select_strategy,
)
if num_projected_patches <= 0:
default_size = self.get_image_size_with_most_features()
num_projected_patches_default = self._apply_feature_select_strategy(
hf_config.vision_feature_select_strategy,
num_projected_patches_default = get_num_selected_vision_tokens(
vision_encoder_info.get_num_image_tokens(
image_width=default_size.width,
image_height=default_size.height,
),
hf_config.vision_feature_select_strategy,
)
if num_projected_patches_default <= 0:
raise ValueError(
Expand Down
32 changes: 28 additions & 4 deletions vllm/model_executor/models/vision.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,6 @@

import torch
from transformers import PretrainedConfig
from typing_extensions import assert_never

from vllm.distributed import (get_tensor_model_parallel_rank,
get_tensor_model_parallel_world_size,
Expand All @@ -22,9 +21,13 @@
_C = TypeVar("_C", bound=PretrainedConfig)


class _RootConfig(Protocol[_C]):
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The previous type annotation was incorrect

vision_config: _C


class VisionEncoderInfo(ABC, Generic[_C]):

def __init__(self, hf_config: _C) -> None:
def __init__(self, hf_config: _RootConfig[_C]) -> None:
super().__init__()

self.hf_config = hf_config
Expand Down Expand Up @@ -95,7 +98,7 @@ def get_vit_attn_backend(head_size: int, dtype: torch.dtype) -> _Backend:


def _get_vision_feature_selector(
strategy: VisionFeatureSelectStrategy,
strategy: Union[VisionFeatureSelectStrategy, str],
) -> Callable[[torch.Tensor], torch.Tensor]:
if callable(strategy):
return strategy
Expand All @@ -111,7 +114,28 @@ def _get_vision_feature_selector(
if strategy == "full":
return lambda feats: feats

assert_never(strategy)
raise ValueError(f"Unexpected feature select strategy: {strategy!r}")


def get_num_selected_vision_tokens(
num_vision_tokens: int,
strategy: Union[VisionFeatureSelectStrategy, str],
) -> int:
if callable(strategy):
dummy_features = torch.empty(1, num_vision_tokens, 64) # [B, L, D]
dummy_selected_features = strategy(dummy_features)
return dummy_selected_features.shape[1]

if strategy == "class":
return 1

if strategy == "default":
return num_vision_tokens - 1

if strategy == "full":
return num_vision_tokens

raise ValueError(f"Unexpected feature select strategy: {strategy!r}")


def resolve_visual_encoder_outputs(
Expand Down
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