提交vllm0.11.0开发分支

vllm_kunlun/patches/eval_frame.py

@@ -98,12 +98,10 @@ cached_backends: Dict[int, CompilerFn] = {}
 unset = Unset.token
 
 from torch._C._dynamo.eval_frame import set_eval_frame
-
-
 def _maybe_set_eval_frame(callback: DynamoCallback):
     # A wrapper on set_eval_frame that is guarded by a Justknob.
     # Users can disable torchDynamo by setting the JK to False.
-    # from torch._C._dynamo.eval_frame import set_eval_frame
+    #from torch._C._dynamo.eval_frame import set_eval_frame
 
     if not justknobs_check("pytorch/compiler:enable_compiler_set_eval_frame"):
         torch._dynamo.utils.warn_once(
@@ -130,7 +128,7 @@ DONT_WRAP_FILES = {
 
 
 def _debug_get_cache_entry_list(
-    code: Union[types.CodeType, Callable[..., Any]],
+    code: Union[types.CodeType, Callable[..., Any]]
 ) -> List[CacheEntry]:
     """
     Given a code object or a callable object, retrieve the cache entries
@@ -373,9 +371,9 @@ class _TorchDynamoContext:
         # add context containing GraphModule to any GraphModule forward functions
         if isinstance(fn, GraphModule):
             # add context containing GraphModule to any GraphModule forward functions
-            code_context.get_context(fn.forward.__code__)["orig_graphmodule"] = (
-                weakref.ref(fn)
-            )
+            code_context.get_context(fn.forward.__code__)[
+                "orig_graphmodule"
+            ] = weakref.ref(fn)
 
         # Optimize the forward method of torch.nn.Module object
         if isinstance(fn, torch.nn.Module):
@@ -789,11 +787,9 @@ def _optimize(
         hooks,
         backend_ctx_ctor,
         dynamic=dynamic,
-        compiler_config=(
-            backend.get_compiler_config()
-            if hasattr(backend, "get_compiler_config")
-            else None
-        ),
+        compiler_config=backend.get_compiler_config()
+        if hasattr(backend, "get_compiler_config")
+        else None,
         rebuild_ctx=rebuild_ctx,
     )
 
@@ -907,11 +903,9 @@ class FlattenInputOutputSignature(torch.fx.interpreter.Transformer):
                         flat_args[i],
                         symbolic_context=StatelessSymbolicContext(
                             dynamic_sizes=[
-                                (
-                                    DimDynamic.DYNAMIC
-                                    if d in flat_args_dynamic_dims[i]
-                                    else DimDynamic.STATIC
-                                )
+                                DimDynamic.DYNAMIC
+                                if d in flat_args_dynamic_dims[i]
+                                else DimDynamic.STATIC
                                 for d in range(len(flat_args[i].shape))
                             ],
                             constraint_sizes=[None] * len(flat_args[i].shape),