vlm: enable radix cache for qwen-vl models (#5349)

Co-authored-by: Xinyuan Tong <justinning0323@outlook.com>
This commit is contained in:
Mick
2025-04-24 12:35:05 +09:00
committed by GitHub
parent 7d0edf3cae
commit c998d04b46
26 changed files with 429 additions and 331 deletions

View File

@@ -49,7 +49,7 @@ from sglang.srt.layers.pooler import Pooler, PoolingType
from sglang.srt.layers.quantization.base_config import QuantizationConfig
from sglang.srt.layers.vocab_parallel_embedding import ParallelLMHead
from sglang.srt.managers.mm_utils import (
MultiModalityDataPaddingPatternTokenPairs,
MultiModalityDataPaddingPatternMultimodalTokens,
general_mm_embed_routine,
)
from sglang.srt.managers.schedule_batch import MultimodalDataItem, MultimodalInputs
@@ -488,11 +488,8 @@ class Qwen2_5_VLForConditionalGeneration(nn.Module):
def pad_input_ids(self, input_ids: List[int], mm_inputs: MultimodalInputs):
# Get all special token IDs
im_start_id: int = mm_inputs.im_start_id
im_end_id: int = mm_inputs.im_end_id
media_token_pairs = [(im_start_id, im_end_id)]
pattern = MultiModalityDataPaddingPatternTokenPairs(media_token_pairs)
im_token_id: int = mm_inputs.im_token_id
pattern = MultiModalityDataPaddingPatternMultimodalTokens([im_token_id])
return pattern.pad_input_tokens(input_ids, mm_inputs)
def get_image_feature(self, items: List[MultimodalDataItem]) -> torch.Tensor: