[Misc] Clean up type annotation for SupportsMultiModal (#14794)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/model_executor/models/qwen2_audio.py

@@ -37,8 +37,7 @@ from vllm.config import VllmConfig
 from vllm.model_executor.layers.sampler import SamplerOutput, get_sampler
 from vllm.model_executor.sampling_metadata import SamplingMetadata
 from vllm.multimodal import MULTIMODAL_REGISTRY
-from vllm.multimodal.inputs import (MultiModalFieldConfig, MultiModalKwargs,
-                                    NestedTensors)
+from vllm.multimodal.inputs import MultiModalFieldConfig, MultiModalKwargs
 from vllm.multimodal.parse import (AudioProcessorItems, MultiModalDataItems,
                                    MultiModalDataParser)
 from vllm.multimodal.processing import (BaseMultiModalProcessor,
@@ -47,7 +46,7 @@ from vllm.multimodal.processing import (BaseMultiModalProcessor,
 from vllm.multimodal.profiling import BaseDummyInputsBuilder, ProcessorInputs
 from vllm.sequence import IntermediateTensors
 
-from .interfaces import SupportsMultiModal, SupportsPP
+from .interfaces import MultiModalEmbeddings, SupportsMultiModal, SupportsPP
 from .utils import (AutoWeightsLoader, init_vllm_registered_model,
                     maybe_prefix, merge_multimodal_embeddings)
 
@@ -357,8 +356,7 @@ class Qwen2AudioForConditionalGeneration(nn.Module, SupportsMultiModal,
                            audio_output_lengths.flatten().tolist())
 
     def get_multimodal_embeddings(
-        self, **kwargs
-    ) -> Union[list[torch.Tensor], torch.Tensor, tuple[torch.Tensor, ...]]:
+            self, **kwargs: object) -> Optional[MultiModalEmbeddings]:
         audio_input = self._parse_and_validate_audio_input(**kwargs)
         if audio_input is None:
             return None
@@ -368,7 +366,7 @@ class Qwen2AudioForConditionalGeneration(nn.Module, SupportsMultiModal,
     def get_input_embeddings(
         self,
         input_ids: torch.Tensor,
-        multimodal_embeddings: Optional[NestedTensors] = None,
+        multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
         if multimodal_embeddings is not None: