[Platforms] Refactor xpu code (vllm-project#10468)

Signed-off-by: MengqingCao <[email protected]>
Signed-off-by: Tyler Michael Smith <[email protected]>

vllm/executor/xpu_executor.py

@@ -1,8 +1,5 @@
 from typing import Callable, List, Optional, Tuple, Type, Union
 
-import torch
-
-from vllm.config import ModelConfig, ParallelConfig
 from vllm.executor.executor_base import ExecutorAsyncBase
 from vllm.executor.gpu_executor import GPUExecutor
 from vllm.logger import init_logger
@@ -23,7 +20,6 @@ def _init_executor(self) -> None:
         assert self.speculative_config is None, (
             "Speculative decoding not yet supported for XPU backend")
 
-        self.model_config = _verify_and_get_model_config(self.model_config)
         GPUExecutor._init_executor(self)
 
     def _get_worker_module_and_class(
@@ -53,26 +49,3 @@ async def execute_model_async(
         output = await make_async(self.driver_worker.execute_model
                                   )(execute_model_req=execute_model_req)
         return output
-
-
-def _verify_and_get_model_config(config: ModelConfig) -> ModelConfig:
-    if config.dtype == torch.bfloat16:
-        logger.warning(
-            "bfloat16 is not fully supported on XPU, casting to float16.")
-        config.dtype = torch.float16
-    if not config.enforce_eager:
-        logger.warning(
-            "CUDA graph is not supported on XPU, fallback to the eager "
-            "mode.")
-        config.enforce_eager = True
-    return config
-
-
-def _verify_and_get_parallel_config(config: ParallelConfig) -> ParallelConfig:
-    if (config.distributed_executor_backend is not None
-            and config.distributed_executor_backend != "ray"):
-        logger.warning(
-            "%s is not supported on XPU, fallback to ray distributed executor "
-            "backend.", config.distributed_executor_backend)
-        config.distributed_executor_backend = "ray"
-    return config

vllm/platforms/xpu.py

@@ -1,9 +1,16 @@
+from typing import TYPE_CHECKING
+
 import torch
 
 from vllm.logger import init_logger
 
 from .interface import DeviceCapability, Platform, PlatformEnum, _Backend
 
+if TYPE_CHECKING:
+    from vllm.config import VllmConfig
+else:
+    VllmConfig = None
+
 logger = init_logger(__name__)
 
 
@@ -34,3 +41,17 @@ def get_device_total_memory(cls, device_id: int = 0) -> int:
     @staticmethod
     def inference_mode():
         return torch.no_grad()
+
+    @classmethod
+    def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
+        # check and update model config
+        model_config = vllm_config.model_config
+        if model_config.dtype == torch.bfloat16:
+            logger.warning(
+                "bfloat16 is not fully supported on XPU, casting to float16.")
+            model_config.dtype = torch.float16
+        if not model_config.enforce_eager:
+            logger.warning(
+                "CUDA graph is not supported on XPU, fallback to the eager "
+                "mode.")
+            model_config.enforce_eager = True