[Refactor] Remove unused param (#39750)

Signed-off-by: yewentao256 <zhyanwentao@126.com>

vllm/model_executor/models/qwen2_5_omni_thinker.py

@@ -952,8 +952,6 @@ class Qwen2_5OmniConditionalGenerationMixin:
     def _process_audio_input(
         self,
         audio_input: Qwen2_5OmniAudioFeatureInputs,
-        audio_hashes: list[str] | None = None,
-        cached_audio_features: torch.Tensor | None = None,
     ) -> torch.Tensor:
         input_features = audio_input["input_features"]
         audio_feature_lengths = audio_input["audio_feature_lengths"]
@@ -990,8 +988,6 @@ class Qwen2_5OmniConditionalGenerationMixin:
     def _process_video_input(
         self,
         video_input: Qwen2_5_VLVideoInputs,
-        video_hashes: list[str] = None,
-        cached_video_embeds: torch.Tensor = None,
     ) -> torch.Tensor:
         if video_input["type"] == "video_embeds":
             return video_input["video_embeds"].type(self.visual.dtype)

vllm/model_executor/models/qwen3_asr.py

@@ -363,8 +363,6 @@ class Qwen3ASRForConditionalGeneration(
     def _process_audio_input(
         self,
         audio_input: Qwen2_5OmniAudioFeatureInputs,
-        audio_hashes: list[str] | None = None,
-        cached_audio_features: torch.Tensor | None = None,
     ) -> torch.Tensor:
         input_features = audio_input["input_features"]
         audio_feature_lengths = audio_input["audio_feature_lengths"]

vllm/model_executor/models/qwen3_omni_moe_thinker.py

@@ -1646,8 +1646,6 @@ class Qwen3OmniMoeConditionalGenerationMixin(Qwen2_5OmniConditionalGenerationMix
     def _process_audio_input(
         self,
         audio_input: Qwen2_5OmniAudioFeatureInputs,
-        audio_hashes: list[str] | None = None,
-        cached_audio_features: torch.Tensor | None = None,
     ) -> tuple[torch.Tensor, ...]:
         input_features = audio_input["input_features"]
         audio_feature_lengths = audio_input["audio_feature_lengths"]

vllm/v1/engine/async_llm.py

@@ -77,7 +77,6 @@ class AsyncLLM(EngineClient):
         log_stats: bool,
         usage_context: UsageContext = UsageContext.ENGINE_CONTEXT,
         mm_registry: MultiModalRegistry = MULTIMODAL_REGISTRY,
-        use_cached_outputs: bool = False,
         log_requests: bool = True,
         start_engine_loop: bool = True,
         stat_loggers: list[StatLoggerFactory] | None = None,
@@ -95,7 +94,6 @@ class AsyncLLM(EngineClient):
             log_stats: Whether to log stats.
             usage_context: Usage context of the LLM.
             mm_registry: Multi-modal registry.
-            use_cached_outputs: Whether to use cached outputs.
             log_requests: Whether to log requests.
             start_engine_loop: Whether to start the engine loop.
             stat_loggers: customized stat loggers for the engine.

vllm/v1/engine/llm_engine.py

@@ -56,7 +56,6 @@ class LLMEngine:
         usage_context: UsageContext = UsageContext.ENGINE_CONTEXT,
         stat_loggers: list[StatLoggerFactory] | None = None,
         mm_registry: MultiModalRegistry = MULTIMODAL_REGISTRY,
-        use_cached_outputs: bool = False,
         multiprocess_mode: bool = False,
     ) -> None:
         self.vllm_config = vllm_config