[fix] fix CI warnings

Signed-off-by: Jingxin Pan <[email protected]>
vllm-project · Dec 30, 2024 · e56a741 · e56a741
1 parent 7a43c65
commit e56a741
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Showing 2 changed files with 5 additions and 5 deletions.
diff --git a/vllm/worker/model_runner.py b/vllm/worker/model_runner.py
@@ -436,7 +436,7 @@ def reset_cached_inter_data(self):
     def __init__(self,
                  runner: "GPUModelRunnerBase",
                  finished_requests_ids: Optional[List[str]] = None,
-                 kv_caches: Optional[List[torch.Tensor]] = []):
+                 kv_caches: Optional[List[torch.Tensor]] = None):
         super().__init__()
         # Compute functions for each sequence in a sequence group.
         # WARNING: The order of the functions matters!
@@ -1246,7 +1246,7 @@ def _prepare_model_input_tensors(
         self,
         seq_group_metadata_list: List[SequenceGroupMetadata],
         finished_requests_ids: Optional[List[str]] = None,
-        kv_caches: Optional[List[torch.Tensor]] = [],
+        kv_caches: Optional[List[torch.Tensor]] = None,
     ) -> TModelInputForGPU:
         """Helper method to prepare the model input based on a given sequence
         group. Prepares metadata needed for the base model forward pass but not
@@ -1621,7 +1621,7 @@ def prepare_model_input(
         seq_group_metadata_list: List[SequenceGroupMetadata],
         virtual_engine: int = 0,
         finished_requests_ids: Optional[List[str]] = None,
-        kv_caches: Optional[List[torch.Tensor]] = [],
+        kv_caches: Optional[List[torch.Tensor]] = None,
     ) -> ModelInputForGPUWithSamplingMetadata:
         """Prepare the model input based on a given sequence group, including
         metadata for the sampling step.

diff --git a/vllm/worker/worker_base.py b/vllm/worker/worker_base.py
@@ -259,7 +259,7 @@ def _get_worker_input_from_broadcast(
 
     def _get_driver_input_and_broadcast(
         self, execute_model_req: ExecuteModelRequest, 
-        kv_caches: Optional[List[torch.Tensor]] = [],
+        kv_caches: Optional[List[torch.Tensor]] = None,
     ) -> Tuple[BroadcastableModelInput, WorkerInput, Dict[str, torch.Tensor]]:
         """ Get the driver input and broadcast it to other workers.  """
         assert self.is_driver_worker
@@ -291,7 +291,7 @@ def _get_driver_input_and_broadcast(
     def prepare_input(
         self,
         execute_model_req: Optional[ExecuteModelRequest] = None,
-        kv_caches: Optional[List[torch.Tensor]] = [],
+        kv_caches: Optional[List[torch.Tensor]] = None,
     ) -> Optional[Tuple[BroadcastableModelInput, WorkerInput, Dict[
             str, torch.Tensor]]]:
         """