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Improve static type checking in LoRAModelRunnerMixin #17104

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merged 1 commit into from
Apr 24, 2025
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Improve static type checking in LoRAModelRunnerMixin #17104

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16 changes: 6 additions & 10 deletions vllm/v1/worker/lora_model_runner_mixin.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,20 +28,16 @@ def load_lora_model(self, model: nn.Module, model_config: ModelConfig,
scheduler_config: SchedulerConfig,
lora_config: LoRAConfig, device: str) -> nn.Module:

assert supports_lora(
model), f"{model.__class__.__name__} does not support LoRA yet."
if not supports_lora(model):
raise ValueError(
f"{model.__class__.__name__} does not support LoRA yet.")

if supports_multimodal(model):
logger.warning("Regarding multimodal models, vLLM currently "
"only supports adding LoRA to language model.")

# It's necessary to distinguish between the max_position_embeddings
# of VLMs and LLMs.
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)
# Use get_text_config() in case of multimodal models
text_config = model_config.hf_config.get_text_config()

# Add LoRA Manager to the Model Runner
self.lora_manager = LRUCacheWorkerLoRAManager(
Expand All @@ -52,7 +48,7 @@ def load_lora_model(self, model: nn.Module, model_config: ModelConfig,
device,
model.embedding_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)

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