[Core] Allow specifying custom Executor (#6557)

vllm/executor/ray_xpu_executor.py

@@ -35,6 +35,8 @@ USE_RAY_COMPILED_DAG = envs.VLLM_USE_RAY_COMPILED_DAG
 
 class RayXPUExecutor(DistributedGPUExecutor):
 
+    uses_ray: bool = True
+
     def __init__(
         self,
         model_config: ModelConfig,
@@ -107,6 +109,13 @@ class RayXPUExecutor(DistributedGPUExecutor):
 
         return num_gpu_blocks, num_cpu_blocks
 
+    def _get_worker_wrapper_args(self) -> Dict[str, Any]:
+        return dict(
+            worker_module_name="vllm.worker.xpu_worker",
+            worker_class_name="XPUWorker",
+            trust_remote_code=self.model_config.trust_remote_code,
+        )
+
     def _init_workers_ray(self, placement_group: "PlacementGroup",
                           **ray_remote_kwargs):
         if self.parallel_config.tensor_parallel_size == 1:
@@ -124,6 +133,7 @@ class RayXPUExecutor(DistributedGPUExecutor):
 
         # Create the workers.
         driver_ip = get_ip()
+        worker_wrapper_kwargs = self._get_worker_wrapper_args()
         for bundle_id, bundle in enumerate(placement_group.bundle_specs):
             if not bundle.get("GPU", 0):
                 continue
@@ -137,22 +147,14 @@ class RayXPUExecutor(DistributedGPUExecutor):
                 num_gpus=num_gpus,
                 scheduling_strategy=scheduling_strategy,
                 **ray_remote_kwargs,
-            )(RayWorkerWrapper).remote(
-                worker_module_name="vllm.worker.xpu_worker",
-                worker_class_name="XPUWorker",
-                trust_remote_code=self.model_config.trust_remote_code,
-            )
+            )(RayWorkerWrapper).remote(**worker_wrapper_kwargs)
 
             worker_ip = ray.get(worker.get_node_ip.remote())
             if worker_ip == driver_ip and self.driver_dummy_worker is None:
                 # If the worker is on the same node as the driver, we use it
                 # as the resource holder for the driver process.
                 self.driver_dummy_worker = worker
-                self.driver_worker = RayWorkerWrapper(
-                    worker_module_name="vllm.worker.xpu_worker",
-                    worker_class_name="XPUWorker",
-                    trust_remote_code=self.model_config.trust_remote_code,
-                )
+                self.driver_worker = RayWorkerWrapper(**worker_wrapper_kwargs)
             else:
                 # Else, added to the list of workers.
                 self.workers.append(worker)
@@ -337,7 +339,7 @@ class RayXPUExecutor(DistributedGPUExecutor):
                              f"required, but found {current_version}")
 
         from ray.dag import InputNode, MultiOutputNode
-        assert self.parallel_config.distributed_executor_backend == "ray"
+        assert self.parallel_config.use_ray
 
         # Right now, compiled DAG requires at least 1 arg. We send
         # a dummy value for now. It will be fixed soon.