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[Refactor] Simplify dummy data generation (#35025)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung
2026-02-23 12:55:27 +08:00
committed by GitHub
parent c645e9a214
commit 987506bca6
78 changed files with 282 additions and 367 deletions
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5
vllm/model_executor/models/aria.py
View File

@@ -444,15 +444,14 @@ class AriaDummyInputsBuilder(BaseDummyInputsBuilder[AriaProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
vision_config = self.info.get_vision_config()
max_image_size = vision_config.image_size
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

9
vllm/model_executor/models/audioflamingo3.py
View File

@@ -252,16 +252,13 @@ class AudioFlamingo3DummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
feature_extractor = self.info.get_feature_extractor(
**(mm_processor_kwargs or {})
)
feature_extractor = self.info.get_feature_extractor()
sampling_rate = feature_extractor.sampling_rate
audio_len = MAX_AUDIO_LEN * sampling_rate
num_audios = mm_counts.get("audio", 0)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(

5
vllm/model_executor/models/aya_vision.py
View File

@@ -191,13 +191,12 @@ class AyaVisionDummyInputsBuilder(BaseDummyInputsBuilder[AyaVisionProcessingInfo
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
image_size = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/bagel.py
View File

@@ -249,8 +249,7 @@ class BagelDummyInputsBuilder(BaseDummyInputsBuilder[BagelProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
hf_config = self.info.get_hf_config()
@@ -258,7 +257,7 @@ class BagelDummyInputsBuilder(BaseDummyInputsBuilder[BagelProcessingInfo]):
# Use the configured image size
image_size = vit_config.image_size
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/bee.py
View File

@@ -90,14 +90,13 @@ class BeeDummyInputsBuilder(LlavaDummyInputsBuilder[BeeProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/blip2.py
View File

@@ -445,8 +445,7 @@ class Blip2DummyInputsBuilder(BaseDummyInputsBuilder[Blip2ProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
hf_config = self.info.get_hf_config()
vision_config = hf_config.vision_config
@@ -454,7 +453,7 @@ class Blip2DummyInputsBuilder(BaseDummyInputsBuilder[Blip2ProcessingInfo]):
max_image_size = vision_config.image_size
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/chameleon.py
View File

@@ -116,15 +116,14 @@ class ChameleonDummyInputsBuilder(BaseDummyInputsBuilder[ChameleonProcessingInfo
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
config = self.info.get_hf_config()
width = height = config.vq_config.resolution
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/clip.py
View File

@@ -174,14 +174,13 @@ class CLIPDummyInputsBuilder(BaseDummyInputsBuilder[CLIPProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/cohere2_vision.py
View File

@@ -197,13 +197,12 @@ class Cohere2VisionDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
image_size = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

6
vllm/model_executor/models/colmodernvbert.py
View File

@@ -132,12 +132,12 @@ class ColModernVBertDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(
width=target_width,

3
vllm/model_executor/models/deepseek_ocr.py
View File

@@ -255,8 +255,7 @@ class DeepseekOCRDummyInputsBuilder(BaseDummyInputsBuilder[DeepseekOCRProcessing
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)

3
vllm/model_executor/models/deepseek_ocr2.py
View File

@@ -137,8 +137,7 @@ class DeepseekOCR2DummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)

5
vllm/model_executor/models/deepseek_vl2.py
View File

@@ -214,14 +214,13 @@ class DeepseekVL2DummyInputsBuilder(BaseDummyInputsBuilder[DeepseekVL2Processing
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
max_image_size = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

10
vllm/model_executor/models/dots_ocr.py
View File

@@ -106,17 +106,13 @@ class DotsOCRDummyInputsBuilder(Qwen2VLDummyInputsBuilder):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
mm_processor_kwargs = mm_processor_kwargs or {}
target_width, target_height = self.info.get_image_size_with_most_features( # noqa: E501
mm_processor_kwargs.get("max_pixels", None)
)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

7
vllm/model_executor/models/ernie45_vl.py
View File

@@ -1168,8 +1168,7 @@ class Ernie4_5_VLDummyInputsBuilder(BaseDummyInputsBuilder[Ernie4_5_VLProcessing
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
@@ -1179,8 +1178,8 @@ class Ernie4_5_VLDummyInputsBuilder(BaseDummyInputsBuilder[Ernie4_5_VLProcessing
seq_len, mm_counts
)
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
return {
"image": self._get_dummy_images(

15
vllm/model_executor/models/funasr.py
View File

@@ -746,23 +746,22 @@ class FunASRDummyInputsBuilder(BaseDummyInputsBuilder[FunASRProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
feature_extractor = self.info.get_feature_extractor(
**(mm_processor_kwargs or {})
)
feature_extractor = self.info.get_feature_extractor()
sampling_rate = feature_extractor.sampling_rate
audio_len = feature_extractor.chunk_length * sampling_rate
num_audios = mm_counts.get("audio", 0)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(
length=audio_len, num_audios=num_audios, overrides=audio_overrides
)
length=audio_len,
num_audios=num_audios,
overrides=audio_overrides,
),
}

9
vllm/model_executor/models/funaudiochat.py
View File

@@ -610,12 +610,9 @@ class FunAudioChatDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
feature_extractor = self.info.get_feature_extractor(
**(mm_processor_kwargs or {})
)
feature_extractor = self.info.get_feature_extractor()
sampling_rate = int(feature_extractor.sampling_rate)
# Dummy inputs are used for profiling; construct the worst-case audio
@@ -632,7 +629,7 @@ class FunAudioChatDummyInputsBuilder(
)
num_audios = int(mm_counts.get("audio", 0))
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(
length=audio_len,

5
vllm/model_executor/models/fuyu.py
View File

@@ -142,13 +142,12 @@ class FuyuDummyInputsBuilder(BaseDummyInputsBuilder[FuyuProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
target_width, target_height = self.info.get_image_size_with_most_features()
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/gemma3_mm.py
View File

@@ -241,14 +241,13 @@ class Gemma3DummyInputsBuilder(BaseDummyInputsBuilder[Gemma3ProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

11
vllm/model_executor/models/gemma3n_mm.py
View File

@@ -175,8 +175,7 @@ class Gemma3nDummyInputsBuilder(BaseDummyInputsBuilder[Gemma3nProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_audios = mm_counts.get("audio", 0)
@@ -189,8 +188,8 @@ class Gemma3nDummyInputsBuilder(BaseDummyInputsBuilder[Gemma3nProcessingInfo]):
img_width = image_processor.size.get("width", 224)
img_height = image_processor.size.get("height", 224)
image_overrides = mm_options.get("image") if mm_options else None
audio_overrides = mm_options.get("audio") if mm_options else None
image_overrides = mm_options.get("image")
audio_overrides = mm_options.get("audio")
return {
"image": self._get_dummy_images(
@@ -200,7 +199,9 @@ class Gemma3nDummyInputsBuilder(BaseDummyInputsBuilder[Gemma3nProcessingInfo]):
overrides=image_overrides,
),
"audio": self._get_dummy_audios(
length=audio_len, num_audios=num_audios, overrides=audio_overrides
length=audio_len,
num_audios=num_audios,
overrides=audio_overrides,
),
}

7
vllm/model_executor/models/glm4_1v.py
View File

@@ -1163,8 +1163,7 @@ class Glm4vDummyInputsBuilder(BaseDummyInputsBuilder[Glm4vProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
@@ -1174,8 +1173,8 @@ class Glm4vDummyInputsBuilder(BaseDummyInputsBuilder[Glm4vProcessingInfo]):
seq_len, mm_counts
)
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/glm4v.py
View File

@@ -492,8 +492,7 @@ class GLM4VDummyInputsBuilder(BaseDummyInputsBuilder[GLM4VProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
hf_config = self.info.get_hf_config()
vision_config = hf_config.vision_config
@@ -501,7 +500,7 @@ class GLM4VDummyInputsBuilder(BaseDummyInputsBuilder[GLM4VProcessingInfo]):
target_width = target_height = vision_config["image_size"]
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

13
vllm/model_executor/models/glmasr.py
View File

@@ -726,15 +726,12 @@ class GlmAsrDummyInputsBuilder(BaseDummyInputsBuilder[GlmAsrProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
feature_extractor = self.info.get_feature_extractor(
**(mm_processor_kwargs or {})
)
feature_extractor = self.info.get_feature_extractor()
sampling_rate = feature_extractor.sampling_rate
num_audios = mm_counts.get("audio", 0)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
max_audio_len = getattr(
self.info.get_hf_processor(), "max_audio_len", DEFAULT_MAX_AUDIO_LEN_S
@@ -743,7 +740,9 @@ class GlmAsrDummyInputsBuilder(BaseDummyInputsBuilder[GlmAsrProcessingInfo]):
return {
"audio": self._get_dummy_audios(
length=audio_len, num_audios=num_audios, overrides=audio_overrides
length=audio_len,
num_audios=num_audios,
overrides=audio_overrides,
)
}

5
vllm/model_executor/models/granite_speech.py
View File

@@ -216,11 +216,10 @@ class GraniteSpeechDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_audios = mm_counts.get("audio", 0)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(

3
vllm/model_executor/models/hunyuan_vision.py
View File

@@ -713,8 +713,7 @@ class HunYuanVLDummyInputsBuilder(BaseDummyInputsBuilder[HunYuanVLProcessingInfo
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 1)

7
vllm/model_executor/models/hyperclovax_vision.py
View File

@@ -165,8 +165,7 @@ class HCXVisionDummyInputsBuilder(BaseDummyInputsBuilder[HCXVisionProcessingInfo
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
@@ -174,8 +173,8 @@ class HCXVisionDummyInputsBuilder(BaseDummyInputsBuilder[HCXVisionProcessingInfo
target_width, target_height = self.info.get_image_size_with_most_features()
target_num_frames = 32
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
return {
"image": self._get_dummy_images(

7
vllm/model_executor/models/idefics3.py
View File

@@ -277,15 +277,14 @@ class Idefics3DummyInputsBuilder(BaseDummyInputsBuilder[Idefics3ProcessingInfo])
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
hf_processor = self.info.get_hf_processor(**(mm_processor_kwargs or {}))
hf_processor = self.info.get_hf_processor()
image_processor: Idefics3ImageProcessor = hf_processor.image_processor
longest_edge = image_processor.max_image_size["longest_edge"]
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

7
vllm/model_executor/models/interns1.py
View File

@@ -297,8 +297,7 @@ class InternS1DummyInputsBuilder(BaseDummyInputsBuilder[InternS1ProcessingInfo])
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
target_width, target_height = self.info.get_image_size_with_most_features()
target_num_frames = self.info.get_num_frames_with_most_features(
@@ -310,8 +309,8 @@ class InternS1DummyInputsBuilder(BaseDummyInputsBuilder[InternS1ProcessingInfo])
config = self.info.get_hf_config()
image_size_h, image_size_w = config.vision_config.image_size
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
return {
"image": self._get_dummy_images(

14
vllm/model_executor/models/internvl.py
View File

@@ -762,13 +762,12 @@ class BaseInternVLDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
target_width, target_height = self.info.get_image_size_with_most_features()
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(
@@ -935,12 +934,9 @@ class InternVLDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
dummy_image = super().get_dummy_mm_data(
seq_len=seq_len, mm_counts=mm_counts, mm_options=mm_options
)
dummy_image = super().get_dummy_mm_data(seq_len, mm_counts, mm_options)
if self.info.supports_video:
config = self.info.get_hf_config()
image_size: int = config.vision_config.image_size
@@ -948,7 +944,7 @@ class InternVLDummyInputsBuilder(
seq_len, mm_counts
)
num_videos = mm_counts.get("video", 0)
video_overrides = mm_options.get("video") if mm_options else None
video_overrides = mm_options.get("video")
dummy_video = {
"video": self._get_dummy_videos(
width=image_size,

6
vllm/model_executor/models/isaac.py
View File

@@ -18,6 +18,7 @@ from typing_extensions import TypedDict, Unpack
from vllm.config import VllmConfig
from vllm.config.model import ModelConfig
from vllm.config.multimodal import BaseDummyOptions
from vllm.distributed import parallel_state
from vllm.distributed import utils as dist_utils
from vllm.model_executor.layers.attention import MMEncoderAttention
@@ -849,13 +850,12 @@ class IsaacDummyInputsBuilder(BaseDummyInputsBuilder[IsaacProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

3
vllm/model_executor/models/kanana_v.py
View File

@@ -444,8 +444,7 @@ class KananaVDummyInputsBuilder(BaseDummyInputsBuilder[KananaVProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
return {

7
vllm/model_executor/models/keye.py
View File

@@ -1170,8 +1170,7 @@ class KeyeBaseDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
@@ -1179,8 +1178,8 @@ class KeyeBaseDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
target_width, target_height = self.info.get_image_size_with_most_features()
target_num_frames = self.info.get_num_frames_with_most_features(seq_len)
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
mm_data = {
"image": self._get_dummy_images(

3
vllm/model_executor/models/kimi_k25.py
View File

@@ -240,8 +240,7 @@ class KimiK25DummyInputsBuilder(BaseDummyInputsBuilder[KimiK25ProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
# TODO: Support mm_options for vision_chunk to allow user configuration
dummy_items = self.get_dummy_mm_items()

5
vllm/model_executor/models/kimi_vl.py
View File

@@ -215,12 +215,11 @@ class KimiVLDummyInputsBuilder(BaseDummyInputsBuilder[KimiVLProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/lfm2_vl.py
View File

@@ -343,14 +343,13 @@ class Lfm2VLDummyInputsBuilder(BaseDummyInputsBuilder[Lfm2VLProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/llava.py
View File

@@ -232,14 +232,13 @@ class LlavaDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/llava_next_video.py
View File

@@ -165,8 +165,7 @@ class LlavaNextVideoDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_videos = mm_counts.get("video", 0)
@@ -175,7 +174,7 @@ class LlavaNextVideoDummyInputsBuilder(
seq_len, mm_counts
)
video_overrides = mm_options.get("video") if mm_options else None
video_overrides = mm_options.get("video")
return {
"video": self._get_dummy_videos(

7
vllm/model_executor/models/llava_onevision.py
View File

@@ -276,8 +276,7 @@ class LlavaOnevisionDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
@@ -287,8 +286,8 @@ class LlavaOnevisionDummyInputsBuilder(
seq_len, mm_counts
)
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/midashenglm.py
View File

@@ -565,12 +565,11 @@ class MiDashengLMDummyInputsBuilder(BaseDummyInputsBuilder[MiDashengLMProcessing
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_audios = mm_counts.get("audio", 0)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(

9
vllm/model_executor/models/minicpmo.py
View File

@@ -301,8 +301,7 @@ class MiniCPMODummyInputsBuilder(MiniCPMVDummyInputsBuilder[MiniCPMOProcessingIn
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_audios = mm_counts.get("audio", 0)
audio_len = (
@@ -310,11 +309,13 @@ class MiniCPMODummyInputsBuilder(MiniCPMVDummyInputsBuilder[MiniCPMOProcessingIn
* self.info.get_default_audio_sampling_rate()
)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
audio_mm_data = {
"audio": self._get_dummy_audios(
length=audio_len, num_audios=num_audios, overrides=audio_overrides
length=audio_len,
num_audios=num_audios,
overrides=audio_overrides,
)
}

7
vllm/model_executor/models/minicpmv.py
View File

@@ -707,8 +707,7 @@ class MiniCPMVDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
@@ -719,8 +718,8 @@ class MiniCPMVDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
seq_len, mm_counts
)
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/mistral3.py
View File

@@ -236,14 +236,13 @@ class Mistral3DummyInputsBuilder(BaseDummyInputsBuilder[_I]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/mllama4.py
View File

@@ -707,14 +707,13 @@ class Mllama4DummyInputsBuilder(BaseDummyInputsBuilder[Mllama4ProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
(target_width, target_height) = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/molmo.py
View File

@@ -1274,13 +1274,12 @@ class MolmoDummyInputsBuilder(BaseDummyInputsBuilder[MolmoProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
target_width, target_height = self.info.get_image_size_with_most_features()
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

7
vllm/model_executor/models/molmo2.py
View File

@@ -2082,8 +2082,7 @@ class Molmo2DummyInputsBuilder(BaseDummyInputsBuilder[Molmo2ProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
@@ -2094,7 +2093,7 @@ class Molmo2DummyInputsBuilder(BaseDummyInputsBuilder[Molmo2ProcessingInfo]):
if num_images > 0:
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
dummy_images = self._get_dummy_images(
width=target_width,
@@ -2110,7 +2109,7 @@ class Molmo2DummyInputsBuilder(BaseDummyInputsBuilder[Molmo2ProcessingInfo]):
seq_len, mm_counts
)
video_overrides = mm_options.get("video") if mm_options else None
video_overrides = mm_options.get("video")
if video_overrides:
assert isinstance(video_overrides, VideoDummyOptions)

14
vllm/model_executor/models/nano_nemotron_vl.py
View File

@@ -1388,8 +1388,7 @@ class NanoNemotronVLDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
processor = self.info.get_hf_processor()
@@ -1404,7 +1403,7 @@ class NanoNemotronVLDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
max_num_tiles
)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(
@@ -1461,12 +1460,9 @@ class NanoNemotronVLDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
dummy_image = super().get_dummy_mm_data(
seq_len=seq_len, mm_counts=mm_counts, mm_options=mm_options
)
dummy_image = super().get_dummy_mm_data(seq_len, mm_counts, mm_options)
if self.info.supports_video:
config = self.info.get_hf_config()
image_size: int = config.force_image_size
@@ -1474,7 +1470,7 @@ class NanoNemotronVLDummyInputsBuilder(
seq_len, mm_counts
)
num_videos = mm_counts.get("video", 0)
video_overrides = mm_options.get("video") if mm_options else None
video_overrides = mm_options.get("video")
dummy_video = {
"video": self._get_dummy_videos(
width=image_size,

3
vllm/model_executor/models/nemotron_parse.py
View File

@@ -645,8 +645,7 @@ class NemotronParseDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)

5
vllm/model_executor/models/nvlm_d.py
View File

@@ -92,13 +92,12 @@ class NVLMDummyInputsBuilder(BaseInternVLDummyInputsBuilder[NVLMProcessingInfo])
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
target_width, target_height = self.info.get_image_size_with_most_features()
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/ovis.py
View File

@@ -306,14 +306,13 @@ class OvisDummyInputsBuilder(BaseDummyInputsBuilder[OvisProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
mm_data = {
"image": self._get_dummy_images(

7
vllm/model_executor/models/ovis2_5.py
View File

@@ -287,8 +287,7 @@ class Ovis2_5DummyInputsBuilder(BaseDummyInputsBuilder[Ovis2_5ProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
@@ -298,8 +297,8 @@ class Ovis2_5DummyInputsBuilder(BaseDummyInputsBuilder[Ovis2_5ProcessingInfo]):
seq_len, mm_counts
)
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
mm_data = {
"image": self._get_dummy_images(

5
vllm/model_executor/models/paddleocr_vl.py
View File

@@ -206,13 +206,12 @@ class PaddleOCRVLDummyInputsBuilder(BaseDummyInputsBuilder[PaddleOCRVLProcessing
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
max_image_size = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/paligemma.py
View File

@@ -131,8 +131,7 @@ class PaliGemmaDummyInputsBuilder(BaseDummyInputsBuilder[PaliGemmaProcessingInfo
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
hf_config = self.info.get_hf_config()
vision_config = hf_config.vision_config
@@ -140,7 +139,7 @@ class PaliGemmaDummyInputsBuilder(BaseDummyInputsBuilder[PaliGemmaProcessingInfo
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/phi3v.py
View File

@@ -376,14 +376,13 @@ class Phi3VDummyInputsBuilder(BaseDummyInputsBuilder[Phi3VProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

7
vllm/model_executor/models/phi4mm.py
View File

@@ -822,16 +822,15 @@ class Phi4MMDummyInputsBuilder(BaseDummyInputsBuilder[Phi4MMProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_audios = mm_counts.get("audio", 0)
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
audio_overrides = mm_options.get("audio") if mm_options else None
image_overrides = mm_options.get("image")
audio_overrides = mm_options.get("audio")
mm_data = {
"image": self._get_dummy_images(

8
vllm/model_executor/models/pixtral.py
View File

@@ -249,14 +249,13 @@ class PixtralDummyInputsBuilder(BaseDummyInputsBuilder[PixtralProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(
@@ -271,8 +270,7 @@ class PixtralDummyInputsBuilder(BaseDummyInputsBuilder[PixtralProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> ProcessorInputs:
tokenizer = self.info.get_tokenizer()

16
vllm/model_executor/models/qwen2_5_omni_thinker.py
View File

@@ -357,15 +357,13 @@ class Qwen2_5OmniThinkerDummyInputsBuilder(
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_audios = mm_counts.get("audio", 0)
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
mm_processor_kwargs = mm_processor_kwargs or {}
feature_extractor = self.info.get_feature_extractor(**mm_processor_kwargs)
feature_extractor = self.info.get_feature_extractor()
target_audio_length = (
min(
@@ -375,16 +373,14 @@ class Qwen2_5OmniThinkerDummyInputsBuilder(
* feature_extractor.sampling_rate
)
target_width, target_height = self.info.get_image_size_with_most_features(
max_pixels=mm_processor_kwargs.get("max_pixels", None),
)
target_width, target_height = self.info.get_image_size_with_most_features()
target_num_frames = self.info.get_num_frames_with_most_features(
seq_len, mm_counts
)
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
audio_overrides = mm_options.get("audio") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
audio_overrides = mm_options.get("audio")
mm_data = {
"audio": self._get_dummy_audios(

13
vllm/model_executor/models/qwen2_audio.py
View File

@@ -195,22 +195,21 @@ class Qwen2AudioDummyInputsBuilder(BaseDummyInputsBuilder[Qwen2AudioProcessingIn
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
feature_extractor = self.info.get_feature_extractor(
**(mm_processor_kwargs or {})
)
feature_extractor = self.info.get_feature_extractor()
sampling_rate = feature_extractor.sampling_rate
audio_len = feature_extractor.chunk_length * sampling_rate
num_audios = mm_counts.get("audio", 0)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(
length=audio_len, num_audios=num_audios, overrides=audio_overrides
length=audio_len,
num_audios=num_audios,
overrides=audio_overrides,
)
}

19
vllm/model_executor/models/qwen2_vl.py
View File

@@ -925,9 +925,14 @@ class Qwen2VLProcessingInfo(BaseProcessingInfo):
vision_config = hf_config.vision_config
patch_size = vision_config.patch_size
merge_size = vision_config.spatial_merge_size
if max_pixels is None:
image_processor = self.get_image_processor()
max_pixels = image_processor.size["longest_edge"]
mm_kwargs = self.ctx.get_merged_mm_kwargs({})
size = mm_kwargs.get("size", image_processor.size)
max_pixels = size["longest_edge"]
unit = patch_size * merge_size
max_seq_len = max_pixels // (unit * unit)
@@ -1027,22 +1032,18 @@ class Qwen2VLDummyInputsBuilder(BaseDummyInputsBuilder[Qwen2VLProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
mm_processor_kwargs = mm_processor_kwargs or {}
target_width, target_height = self.info.get_image_size_with_most_features(
max_pixels=mm_processor_kwargs.get("max_pixels", None)
)
target_width, target_height = self.info.get_image_size_with_most_features()
target_num_frames = self.info.get_num_frames_with_most_features(
seq_len, mm_counts
)
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
return {
"image": self._get_dummy_images(

9
vllm/model_executor/models/qwen3_asr.py
View File

@@ -146,14 +146,11 @@ class Qwen3ASRDummyInputsBuilder(BaseDummyInputsBuilder[Qwen3ASRProcessingInfo])
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_audios = mm_counts.get("audio", 0)
feature_extractor = self.info.get_feature_extractor(
**(mm_processor_kwargs or {})
)
feature_extractor = self.info.get_feature_extractor()
target_audio_length = (
min(
@@ -163,7 +160,7 @@ class Qwen3ASRDummyInputsBuilder(BaseDummyInputsBuilder[Qwen3ASRProcessingInfo])
* feature_extractor.sampling_rate
)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(

36
vllm/model_executor/models/qwen3_vl.py
View File

@@ -703,11 +703,18 @@ class Qwen3VLProcessingInfo(Qwen2VLProcessingInfo):
mm_counts: Mapping[str, int],
) -> int:
video_processor = self.get_video_processor()
video_max_pixels = video_processor.size["longest_edge"]
mm_kwargs = self.ctx.get_merged_mm_kwargs({})
video_size = mm_kwargs.get("size", video_processor.size)
temporal_patch_size = mm_kwargs.get(
"temporal_patch_size", video_processor.temporal_patch_size
)
# video_max_pixels contains the temporal compression factor,
# so we divide by 2 to get the maximum number of image pixels.
video_max_pixels = video_size["longest_edge"]
target_width, target_height = self.get_image_size_with_most_features(
max_pixels=video_max_pixels // video_processor.temporal_patch_size
max_pixels=video_max_pixels // temporal_patch_size
)
num_video_soft_tokens = self.get_num_video_tokens(
image_width=target_width,
@@ -789,19 +796,15 @@ class Qwen3VLDummyInputsBuilder(BaseDummyInputsBuilder[Qwen3VLProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
num_videos = mm_counts.get("video", 0)
image_overrides = mm_options.get("image") if mm_options else None
video_overrides = mm_options.get("video") if mm_options else None
image_overrides = mm_options.get("image")
video_overrides = mm_options.get("video")
mm_processor_kwargs = mm_processor_kwargs or {}
target_image_width, target_image_height = (
self.info.get_image_size_with_most_features(
max_pixels=mm_processor_kwargs.get("max_pixels", None),
)
self.info.get_image_size_with_most_features()
)
# treat videos as special images
@@ -826,13 +829,20 @@ class Qwen3VLDummyInputsBuilder(BaseDummyInputsBuilder[Qwen3VLProcessingInfo]):
target_num_frames = min(target_num_frames, num_frames_override)
target_num_frames = max(target_num_frames, 2)
video_processor = self.info.get_video_processor(**(mm_processor_kwargs or {}))
video_max_pixels = video_processor.size["longest_edge"]
video_processor = self.info.get_video_processor()
mm_kwargs = self.info.ctx.get_merged_mm_kwargs({})
video_size = mm_kwargs.get("size", video_processor.size)
temporal_patch_size = mm_kwargs.get(
"temporal_patch_size", video_processor.temporal_patch_size
)
# video_max_pixels contains the temporal compression factor,
# so we divide by 2 to get the maximum number of image pixels.
video_max_pixels = video_size["longest_edge"]
target_video_width, target_video_height = (
self.info.get_image_size_with_most_features(
max_pixels=video_max_pixels // video_processor.temporal_patch_size
max_pixels=video_max_pixels // temporal_patch_size
)
)
target_video_size, _ = self.info._get_vision_info(

5
vllm/model_executor/models/qwen_vl.py
View File

@@ -617,8 +617,7 @@ class QwenVLDummyInputsBuilder(BaseDummyInputsBuilder[QwenVLProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
hf_config = self.info.get_hf_config()
vision_config = hf_config.visual
@@ -626,7 +625,7 @@ class QwenVLDummyInputsBuilder(BaseDummyInputsBuilder[QwenVLProcessingInfo]):
target_width = target_height = vision_config["image_size"]
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/rvl.py
View File

@@ -40,14 +40,13 @@ class RVLDummyInputsBuilder(LlavaDummyInputsBuilder[RVLProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/siglip.py
View File

@@ -158,14 +158,13 @@ class SiglipDummyInputsBuilder(BaseDummyInputsBuilder[SiglipProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_image_size_with_most_features()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/skyworkr1v.py
View File

@@ -529,13 +529,12 @@ class SkyworkR1VDummyInputsBuilder(BaseDummyInputsBuilder[SkyworkR1VProcessingIn
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
target_width, target_height = self.info.get_image_size_with_most_features()
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

5
vllm/model_executor/models/step3_vl.py
View File

@@ -564,13 +564,12 @@ class Step3VLDummyInputsBuilder(BaseDummyInputsBuilder[Step3VLProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
target_width, target_height = self.info.get_image_size_with_most_features()
num_images = mm_counts.get("image", 0)
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

3
vllm/model_executor/models/terratorch.py
View File

@@ -154,8 +154,7 @@ class TerratorchInputBuilder(BaseDummyInputsBuilder[TerratorchProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
# Dummy data is generated based on the 'input' section
# defined in the HF configuration file

5
vllm/model_executor/models/transformers/multimodal.py
View File

@@ -101,14 +101,13 @@ class MultiModalDummyInputsBuilder(BaseDummyInputsBuilder[MultiModalProcessingIn
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, "BaseDummyOptions"] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, "BaseDummyOptions"],
) -> MultiModalDataDict:
num_images = mm_counts.get("image", 0)
target_width, target_height = self.info.get_max_image_size()
image_overrides = mm_options.get("image") if mm_options else None
image_overrides = mm_options.get("image")
return {
"image": self._get_dummy_images(

13
vllm/model_executor/models/ultravox.py
View File

@@ -164,12 +164,9 @@ class UltravoxDummyInputsBuilder(BaseDummyInputsBuilder[UltravoxProcessingInfo])
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
feature_extractor = self.info.get_feature_extractor(
**(mm_processor_kwargs or {})
)
feature_extractor = self.info.get_feature_extractor()
sampling_rate = feature_extractor.sampling_rate
audio_len = (
@@ -177,11 +174,13 @@ class UltravoxDummyInputsBuilder(BaseDummyInputsBuilder[UltravoxProcessingInfo])
)
num_audios = mm_counts.get("audio", 0)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(
length=audio_len, num_audios=num_audios, overrides=audio_overrides
length=audio_len,
num_audios=num_audios,
overrides=audio_overrides,
)
}

12
vllm/model_executor/models/voxtral.py
View File

@@ -218,18 +218,19 @@ class VoxtralDummyInputsBuilder(BaseDummyInputsBuilder[VoxtralProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
num_audios = mm_counts.get("audio", 0)
target_length = self.info.get_max_audio_array_len()
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(
length=target_length, num_audios=num_audios, overrides=audio_overrides
length=target_length,
num_audios=num_audios,
overrides=audio_overrides,
)
}
@@ -237,8 +238,7 @@ class VoxtralDummyInputsBuilder(BaseDummyInputsBuilder[VoxtralProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> ProcessorInputs:
tokenizer = self.info.get_tokenizer()

13
vllm/model_executor/models/whisper.py
View File

@@ -695,22 +695,21 @@ class WhisperDummyInputsBuilder(BaseDummyInputsBuilder[WhisperProcessingInfo]):
self,
seq_len: int,
mm_counts: Mapping[str, int],
mm_options: Mapping[str, BaseDummyOptions] | None = None,
mm_processor_kwargs: Mapping[str, object] | None = None,
mm_options: Mapping[str, BaseDummyOptions],
) -> MultiModalDataDict:
feature_extractor = self.info.get_feature_extractor(
**(mm_processor_kwargs or {})
)
feature_extractor = self.info.get_feature_extractor()
sampling_rate = feature_extractor.sampling_rate
audio_len = feature_extractor.chunk_length * sampling_rate
num_audios = mm_counts.get("audio", 0)
audio_overrides = mm_options.get("audio") if mm_options else None
audio_overrides = mm_options.get("audio")
return {
"audio": self._get_dummy_audios(
length=audio_len, num_audios=num_audios, overrides=audio_overrides
length=audio_len,
num_audios=num_audios,
overrides=audio_overrides,
)
}