[LoRA]: Add lora support to qwen-2.5-omni (#24231)

Author: pratapyash

docs/models/supported_models.md

@@ -662,7 +662,7 @@ These models primarily accept the [`LLM.generate`](./generative_models.md#llmgen
 | `Qwen2AudioForConditionalGeneration` | Qwen2-Audio | T + A<sup>+</sup> | `Qwen/Qwen2-Audio-7B-Instruct` | | ✅︎ | ✅︎ |
 | `Qwen2VLForConditionalGeneration` | QVQ, Qwen2-VL | T + I<sup>E+</sup> + V<sup>E+</sup> | `Qwen/QVQ-72B-Preview`, `Qwen/Qwen2-VL-7B-Instruct`, `Qwen/Qwen2-VL-72B-Instruct`, etc. | ✅︎ | ✅︎ | ✅︎ |
 | `Qwen2_5_VLForConditionalGeneration` | Qwen2.5-VL | T + I<sup>E+</sup> + V<sup>E+</sup> | `Qwen/Qwen2.5-VL-3B-Instruct`, `Qwen/Qwen2.5-VL-72B-Instruct`, etc. | ✅︎ | ✅︎ | ✅︎ |
-| `Qwen2_5OmniThinkerForConditionalGeneration` | Qwen2.5-Omni | T + I<sup>E+</sup> + V<sup>E+</sup> + A<sup>+</sup> | `Qwen/Qwen2.5-Omni-7B` | | ✅︎ | ✅︎ |
+| `Qwen2_5OmniThinkerForConditionalGeneration` | Qwen2.5-Omni | T + I<sup>E+</sup> + V<sup>E+</sup> + A<sup>+</sup> | `Qwen/Qwen2.5-Omni-3B`, `Qwen/Qwen2.5-Omni-7B` | ✅︎ | ✅︎ | ✅︎ |
 | `RForConditionalGeneration` | R-VL-4B | T + I<sup>E+</sup> | `YannQi/R-4B` | | ✅︎ | ✅︎ |
 | `SkyworkR1VChatModel` | Skywork-R1V-38B | T + I | `Skywork/Skywork-R1V-38B` | | ✅︎ | ✅︎ |
 | `SmolVLMForConditionalGeneration` | SmolVLM2 | T + I | `SmolVLM2-2.2B-Instruct` | ✅︎ | | ✅︎ |

vllm/model_executor/models/qwen2_5_omni_thinker.py

@@ -41,6 +41,7 @@
 from vllm.config import VllmConfig
 from vllm.logger import init_logger
 from vllm.model_executor.layers.rotary_embedding import MRotaryEmbedding
+from vllm.model_executor.models.module_mapping import MultiModelKeys
 from vllm.model_executor.models.qwen2_5_vl import (
     Qwen2_5_VisionTransformer, Qwen2_5_VLImageEmbeddingInputs,
     Qwen2_5_VLImageInputs, Qwen2_5_VLImagePixelInputs,
@@ -66,7 +67,8 @@
 from vllm.sequence import IntermediateTensors
 from vllm.transformers_utils.tokenizer import decode_tokens, encode_tokens
 
-from .interfaces import MultiModalEmbeddings, SupportsMultiModal, SupportsPP
+from .interfaces import (MultiModalEmbeddings, SupportsLoRA,
+                         SupportsMultiModal, SupportsPP)
 from .utils import (AutoWeightsLoader, WeightsMapper,
                     init_vllm_registered_model, maybe_prefix,
                     merge_multimodal_embeddings)
@@ -705,7 +707,7 @@ def _process_video_input(
     dummy_inputs=Qwen2_5OmniThinkerDummyInputsBuilder,
 )
 class Qwen2_5OmniThinkerForConditionalGeneration(
-        nn.Module, SupportsMultiModal, SupportsPP,
+        nn.Module, SupportsMultiModal, SupportsPP, SupportsLoRA,
         Qwen2_5OmniConditionalGenerationMixin):
     hf_to_vllm_mapper = WeightsMapper(
         orig_to_new_prefix={
@@ -798,6 +800,15 @@ def _parse_and_validate_multimodal_inputs(self, **kwargs: object) -> dict:
     def get_language_model(self) -> torch.nn.Module:
         return self.language_model
 
+    def get_mm_mapping(self) -> MultiModelKeys:
+        """Get module prefix for multimodal models to filter LoRA modules."""
+        return MultiModelKeys.from_string_field(
+            language_model="language_model",
+            connector=[],  # No explicit connector in this model
+            tower_model=["visual",
+                         "audio_tower"],  # Exclude vision and audio towers
+        )
+
     def get_multimodal_embeddings(self,
                                   **kwargs: object) -> MultiModalEmbeddings: