iHore/vLLM
8
0
Fork 0
Code Issues Pull Requests Actions 1 Packages Projects Releases Wiki Activity

[Model] Enable EVS for Qwen3.5 (#48912)

Browse Source 
Signed-off-by: Rui "Garry" Gao <garrygaogg@gmail.com>
This commit is contained in:
Rui "Garry" Gao
2026-07-27 13:42:35 +00:00
committed by GitHub
parent a89015c6df
commit dbccc5ae32
1 changed files with 32 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files
vllm/model_executor/models/qwen3_5.py
+32 -12
View File
@@ -53,6 +53,7 @@ from vllm.model_executor.layers.vocab_parallel_embedding import (
)
from vllm.multimodal import MULTIMODAL_REGISTRY
from vllm.sequence import IntermediateTensors
from vllm.tokenizers.registry import cached_tokenizer_from_config
from vllm.transformers_utils.configs.qwen3_5 import Qwen3_5Config, Qwen3_5TextConfig
from vllm.transformers_utils.configs.qwen3_5_moe import (
Qwen3_5MoeConfig,
@@ -397,8 +398,7 @@ class Qwen3_5MoeForCausalLM(Qwen3_5ForCausalLMBase, QwenNextMixtureOfExperts):
dummy_inputs=Qwen3VLDummyInputsBuilder,
)
class Qwen3_5ForConditionalGeneration(Qwen3VLForConditionalGeneration, IsHybrid):
# Qwen3.5 does not support multimodal pruning (EVS).
supports_multimodal_pruning = False
supports_multimodal_pruning = True
packed_modules_mapping = Qwen3VLForConditionalGeneration.packed_modules_mapping | {
"in_proj_qkvz": ["in_proj_qkv", "in_proj_z"],
@@ -416,8 +416,21 @@ class Qwen3_5ForConditionalGeneration(Qwen3VLForConditionalGeneration, IsHybrid)
self.model_config = vllm_config.model_config
self.multimodal_config = multimodal_config
self.use_data_parallel = multimodal_config.mm_encoder_tp_mode == "data"
# Qwen3.5 does not support multimodal pruning (EVS).
self.is_multimodal_pruning_enabled = False
self.is_multimodal_pruning_enabled = (
multimodal_config.is_multimodal_pruning_enabled()
)
self.video_pruning_rate = self.multimodal_config.video_pruning_rate
self._tokenizer = cached_tokenizer_from_config(vllm_config.model_config)
# attributes needed by EVS-related functions inherited from Qwen3-VL
self.use_deepstack = hasattr(config.vision_config, "deepstack_visual_indexes")
self.deepstack_num_level = (
len(config.vision_config.deepstack_visual_indexes)
if self.use_deepstack
else 0
)
self.visual_dim = config.vision_config.out_hidden_size
self.multiscale_dim = self.visual_dim * self.deepstack_num_level
with self._mark_tower_model(vllm_config, {"image", "video"}):
self.visual = Qwen3_VisionTransformer(
@@ -462,12 +475,6 @@ class Qwen3_5ForConditionalGeneration(Qwen3VLForConditionalGeneration, IsHybrid)
return inputs_embeds
def recompute_mrope_positions(self, *args, **kwargs):
raise NotImplementedError(
"Qwen3.5 does not support multimodal pruning (EVS). "
"recompute_mrope_positions should never be called."
)
def forward(
self,
input_ids: torch.Tensor,
@@ -628,8 +635,21 @@ class Qwen3_5MoeForConditionalGeneration(
self.model_config = vllm_config.model_config
self.multimodal_config = multimodal_config
self.use_data_parallel = multimodal_config.mm_encoder_tp_mode == "data"
# Qwen3.5 does not support multimodal pruning (EVS).
self.is_multimodal_pruning_enabled = False
self.is_multimodal_pruning_enabled = (
multimodal_config.is_multimodal_pruning_enabled()
)
self.video_pruning_rate = self.multimodal_config.video_pruning_rate
self._tokenizer = cached_tokenizer_from_config(vllm_config.model_config)
# attributes needed by EVS-related functions inherited from Qwen3-VL
self.use_deepstack = hasattr(config.vision_config, "deepstack_visual_indexes")
self.deepstack_num_level = (
len(config.vision_config.deepstack_visual_indexes)
if self.use_deepstack
else 0
)
self.visual_dim = config.vision_config.out_hidden_size
self.multiscale_dim = self.visual_dim * self.deepstack_num_level
with self._mark_tower_model(vllm_config, {"image", "video"}):
self.visual = Qwen3_VisionTransformer(