[KVConnector] Always call connector clear_metadata() at end of step (#20756)

Signed-off-by: Nick Hill <nhill@redhat.com>
Co-authored-by: David Ben-David <sdavidbd@gmail.com>

vllm/distributed/kv_transfer/kv_connector/v1/base.py

@@ -57,7 +57,7 @@ class KVConnectorRole(enum.Enum):
     WORKER = 1
 
 
-class KVConnectorMetadata:
+class KVConnectorMetadata(ABC):  # noqa: B024
     """
     Abstract Metadata used to communicate between the
     Scheduler KVConnector and Worker KVConnector.
@@ -71,7 +71,7 @@ class KVConnectorBase_V1(ABC):
         logger.warning(
             "Initializing KVConnectorBase_V1. This API is experimental and "
             "subject to change in the future as we iterate the design.")
-        self._connector_metadata = KVConnectorMetadata()
+        self._connector_metadata: Optional[KVConnectorMetadata] = None
         self._vllm_config = vllm_config
         self._role = role
 
@@ -102,7 +102,7 @@ class KVConnectorBase_V1(ABC):
         This function should be called by the model runner every time 
         after the model execution.
         """
-        self._connector_metadata = KVConnectorMetadata()
+        self._connector_metadata = None
 
     def _get_connector_metadata(self) -> KVConnectorMetadata:
         """Get the connector metadata.
@@ -112,6 +112,9 @@ class KVConnectorBase_V1(ABC):
         Returns:
             ConnectorMetadata: the connector metadata.
         """
+
+        # Should only be called while set to valid metadata.
+        assert self._connector_metadata is not None
         return self._connector_metadata
 
     def register_kv_caches(self, kv_caches: dict[str, torch.Tensor]):

vllm/v1/executor/multiproc_executor.py

@@ -250,28 +250,24 @@ class MultiprocExecutor(Executor):
             self, outputs: list[ModelRunnerOutput]) -> ModelRunnerOutput:
         # aggregate finished_sending, finished_recving from all workers
 
+        def update_finished_set(req_ids: Optional[set[str]],
+                                remaining_count_dict: dict[str, int],
+                                finished_set: set[str]) -> None:
+            for req_id in req_ids or ():
+                new_count = remaining_count_dict[req_id] - 1
+                if new_count == 0:
+                    finished_set.add(req_id)
+                    del remaining_count_dict[req_id]
+                else:
+                    remaining_count_dict[req_id] = new_count
+
         finished_sending = set[str]()
         finished_recving = set[str]()
         for output in outputs:
-            # update finished_sending
+            update_finished_set(output.finished_sending,
-            for req_id in output.finished_sending or []:
+                                self._send_remaining_count, finished_sending)
-                new_count = self._send_remaining_count[req_id] - 1
+            update_finished_set(output.finished_recving,
-                if new_count == 0:
+                                self._recv_remaining_count, finished_recving)
-                    # got response from all workers, report back to scheduler
-                    finished_sending.add(req_id)
-                    del self._send_remaining_count[req_id]
-                else:
-                    self._send_remaining_count[req_id] = new_count
-
-            # update finished_recving
-            for req_id in output.finished_recving or []:
-                new_count = self._recv_remaining_count[req_id] - 1
-                if new_count == 0:
-                    # got response from all workers, report back to scheduler
-                    finished_recving.add(req_id)
-                    del self._recv_remaining_count[req_id]
-                else:
-                    self._recv_remaining_count[req_id] = new_count
 
         # select output of the worker specified by output_rank
         output = outputs[self.output_rank]

vllm/v1/worker/gpu_model_runner.py

@@ -1539,10 +1539,6 @@ class GPUModelRunner(LoRAModelRunnerMixin):
                 attn_metadata,
             )
 
-        # Clear KVConnector state after all KVs are generated.
-        if has_kv_transfer_group():
-            get_kv_transfer_group().clear_connector_metadata()
-
         self.eplb_step()
 
         return ModelRunnerOutput(

vllm/v1/worker/gpu_worker.py

@@ -338,6 +338,10 @@ class Worker(WorkerBase):
                     output = copy.copy(EMPTY_MODEL_RUNNER_OUTPUT)
                 output.finished_sending = finished_sending
                 output.finished_recving = finished_recving
+
+            # Clear KVConnector state for this step.
+            get_kv_transfer_group().clear_connector_metadata()
+
             # with a connector, the scheduler expects output from all workers
             return output