[platforms] absorb worker cls difference into platforms folder (#10555)

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

vllm/worker/worker_base.py

 import dataclasses
-import importlib
 import os
 import time
 from abc import ABC, abstractmethod
-from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Type, Union
+from typing import Any, Dict, List, Optional, Set, Tuple, Type, Union
 
 import torch
 
@@ -15,7 +14,7 @@ from vllm.model_executor.layers.sampler import SamplerOutput
 from vllm.platforms import current_platform
 from vllm.sequence import ExecuteModelRequest, IntermediateTensors
 from vllm.utils import (enable_trace_function_call_for_thread,
-                        update_environment_variables)
+                        resolve_obj_by_qualname, update_environment_variables)
 from vllm.worker.model_runner_base import (BroadcastableModelInput,
                                            ModelRunnerBase,
                                            ModelRunnerInputBase)
@@ -411,23 +410,14 @@ class WorkerWrapperBase:
     We first instantiate the WorkerWrapper, which remembers the worker module
     and class name. Then, when we call `update_environment_variables`, and the
     real initialization happens in `init_worker`.
-
-    If worker_class_fn is specified, it will be executed to get the worker
-    class.
-    Otherwise, the worker class will be obtained by dynamically importing it
-    using worker_module_name and worker_class_name.
     """
 
     def __init__(
         self,
-        worker_module_name: str,
-        worker_class_name: str,
-        trust_remote_code: bool = False,
-        worker_class_fn: Optional[Callable[[],
-                                           Type[WorkerBase]]] = None) -> None:
-        self.worker_module_name = worker_module_name
-        self.worker_class_name = worker_class_name
-        self.worker_class_fn = worker_class_fn
+        vllm_config: VllmConfig,
+    ) -> None:
+        self.vllm_config = vllm_config
+        trust_remote_code = vllm_config.model_config.trust_remote_code
         self.worker: Optional[WorkerBase] = None
         if trust_remote_code:
             # note: lazy import to avoid importing torch before initializing
@@ -456,12 +446,8 @@ class WorkerWrapperBase:
         from vllm.plugins import load_general_plugins
         load_general_plugins()
 
-        if self.worker_class_fn:
-            worker_class = self.worker_class_fn()
-        else:
-            mod = importlib.import_module(self.worker_module_name)
-            worker_class = getattr(mod, self.worker_class_name)
-
+        worker_class = resolve_obj_by_qualname(
+            self.vllm_config.parallel_config.worker_cls)
         self.worker = worker_class(*args, **kwargs)
         assert self.worker is not None