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Improve static type checking in LoRAModelRunnerMixin (#17104)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
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Harry Mellor 2025-04-24 14:14:47 +01:00 committed by GitHub
parent b0c1f6202d
commit 21f4f1c9a4
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1 changed files with 6 additions and 10 deletions
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vllm/v1/worker/lora_model_runner_mixin.py
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@ -28,20 +28,16 @@ class LoRAModelRunnerMixin:
scheduler_config: SchedulerConfig, scheduler_config: SchedulerConfig,
lora_config: LoRAConfig, device: str) -> nn.Module: lora_config: LoRAConfig, device: str) -> nn.Module:
assert supports_lora( if not supports_lora(model):
model), f"{model.__class__.__name__} does not support LoRA yet." raise ValueError(
f"{model.__class__.__name__} does not support LoRA yet.")
if supports_multimodal(model): if supports_multimodal(model):
logger.warning("Regarding multimodal models, vLLM currently " logger.warning("Regarding multimodal models, vLLM currently "
"only supports adding LoRA to language model.") "only supports adding LoRA to language model.")
# It's necessary to distinguish between the max_position_embeddings # Use get_text_config() in case of multimodal models
# of VLMs and LLMs. text_config = model_config.hf_config.get_text_config()
if hasattr(model.config, "max_position_embeddings"):
max_pos_embeddings = model.config.max_position_embeddings
else:
max_pos_embeddings = (
model.config.text_config.max_position_embeddings)
# Add LoRA Manager to the Model Runner # Add LoRA Manager to the Model Runner
self.lora_manager = LRUCacheWorkerLoRAManager( self.lora_manager = LRUCacheWorkerLoRAManager(
@ -52,7 +48,7 @@ class LoRAModelRunnerMixin:
device, device,
model.embedding_modules, model.embedding_modules,
model.embedding_padding_modules, model.embedding_padding_modules,
max_position_embeddings=max_pos_embeddings, max_position_embeddings=text_config.max_position_embeddings,
) )
return self.lora_manager.create_lora_manager(model) return self.lora_manager.create_lora_manager(model)