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Upgrade to vllm 0.17.0 corex v4.1 overlay

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LZiBee
2026-04-29 19:38:22 +08:00
parent 8fac6062e4
commit 938d0854a5
430 changed files with 35969 additions and 14511 deletions
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26
vllm/model_executor/models/transformers/multimodal.py
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@@ -218,7 +218,7 @@ class MultiModalProcessor(BaseMultiModalProcessor[MultiModalProcessingInfo]):
if "mm_token_type_ids" in processed_data
else "token_type_ids"
)
mm_token_type_ids = processed_data.pop(token_type_key)
mm_token_type_ids = processed_data.get(token_type_key)
# We can infer vLLM style placeholder from token type ids, if we split
# it for each input `mm_data`.
@@ -353,6 +353,7 @@ class MultiModalMixin(SupportsMultiModal, SupportsMRoPE):
num_image_patches = kwargs.pop("num_image_patches")
kwargs.pop("token_type_ids", None) # used only in `forward`
kwargs.pop("mm_token_type_ids", None) # used only in `model.get_rope_index`
if pixel_values is not None:
# ROCm: Force math SDP backend for vision encoder to avoid accuracy issues
@@ -443,6 +444,7 @@ class MultiModalMixin(SupportsMultiModal, SupportsMRoPE):
{
"image_grid_thw",
"video_grid_thw",
"mm_token_type_ids",
"second_per_grid_ts",
"audio_feature_lengths",
"use_audio_in_video",
@@ -451,7 +453,7 @@ class MultiModalMixin(SupportsMultiModal, SupportsMRoPE):
if any(
v
for k, v in kwargs.items()
if k not in {"image_grid_thw", "video_grid_thw"}
if k not in {"image_grid_thw", "mm_token_type_ids"}
):
raise NotImplementedError(
"Transformers modeling backend only supports images."
@@ -459,6 +461,7 @@ class MultiModalMixin(SupportsMultiModal, SupportsMRoPE):
image_grid_thw = kwargs.get("image_grid_thw", [])
video_grid_thw = kwargs.get("video_grid_thw", [])
mm_token_type_ids = kwargs.get("mm_token_type_ids")
image_grid_thw = (torch.stack if image_grid_thw else torch.tensor)(
image_grid_thw
@@ -467,10 +470,29 @@ class MultiModalMixin(SupportsMultiModal, SupportsMRoPE):
video_grid_thw
)
# In v4 `get_rope_index` doesn't have wildcard `kwargs`, and
# can't accept arbitrary args, even if its value is `None`
kwargs = {}
if mm_token_type_ids:
if not hasattr(self, "_get_rope_index_accepts_mm_token_type_ids"):
import inspect
sig = inspect.signature(self.model.get_rope_index)
params = sig.parameters
self._get_rope_index_accepts_mm_token_type_ids = (
"mm_token_type_ids" in params
or any(
p.kind == inspect.Parameter.VAR_KEYWORD for p in params.values()
)
)
if self._get_rope_index_accepts_mm_token_type_ids:
kwargs["mm_token_type_ids"] = torch.cat(mm_token_type_ids)
mrope_positions, mrope_position_delta = self.model.get_rope_index(
input_ids=torch.tensor(input_tokens).unsqueeze(0),
image_grid_thw=image_grid_thw,
video_grid_thw=video_grid_thw,
**kwargs,
)
mrope_positions = mrope_positions[:, 0]