[Frontend] CompilationConfig overhaul (#20283): deprecate use_inductor in favor of backend, simplify custom_ops (#26113)

Signed-off-by: morrison-turnansky <mturnans@redhat.com>
Signed-off-by: Morrison Turnansky <mturnans@redhat.com>
Signed-off-by: Luka Govedič <ProExpertProg@users.noreply.github.com>
Co-authored-by: Luka Govedič <ProExpertProg@users.noreply.github.com>
Co-authored-by: Jiangyun Zhu <riverclouds.zhu@qq.com>

vllm/config/compilation.py

@@ -180,10 +180,11 @@ class CompilationConfig:
     """The directory to store the compiled graph, to accelerate Inductor
     compilation. By default, it will use model-related information to generate
     a cache directory."""
-    backend: str = ""
+    backend: str = "inductor"
     """The backend for compilation. It needs to be a string:
 
-    - "" (empty string): use the default backend.
+    - "" (empty string): use the default backend ("inductor" on CUDA-alike
+    platforms).
     - "eager"/"openxla"/...: use the specified backend registered in PyTorch.
     - "full.module.name": a qualified name which can be used to import the
 
@@ -192,7 +193,11 @@ class CompilationConfig:
     distributed setting. When the compilation level is 1 or 2, the backend is
     used for the compilation directly (it sees the whole graph). When the
     compilation level is 3, the backend is used for the piecewise compilation
-    (it sees a part of the graph)."""
+    (it sees a part of the graph). The backend can not be custom for compilation
+    level 3. Furthermore, compilation is only piecewise if splitting ops is set
+    accordingly and use_inductor_cudagraphs_partition is off. Note that the
+    default options for splitting ops are sufficient for piecewise compilation.
+    """
     custom_ops: list[str] = field(default_factory=list)
     """Fine-grained control over which custom ops to enable/disable. Use 'all'
     to enable all, 'none' to disable all. Also specify a list of custom op
@@ -210,8 +215,12 @@ class CompilationConfig:
     compilation."""
 
     # Inductor capture
-    use_inductor: bool = True
-    """Whether to use inductor compilation:
+    use_inductor: Optional[bool] = None
+    """
+    Whether to use inductor compilation.
+
+    This flag is deprecated and will be removed.
+    Please use the 'backend' option instead.
 
     - False: inductor compilation is not used. graph runs in eager
         (custom_ops enabled by default).
@@ -219,7 +228,11 @@ class CompilationConfig:
         One graph for symbolic shape and one graph per size in compile_sizes
         are compiled using configurations in inductor_compile_config.
 
-    This setting is ignored if level<PIECEWISE."""
+    This setting is ignored if level<PIECEWISE.
+
+    For future compatibility:
+    If use_inductor is True, backend="inductor" otherwise backend="eager".
+    """
     compile_sizes: Optional[list[Union[int, str]]] = None
     """Sizes to compile for inductor. In addition
     to integers, it also supports "cudagraph_capture_sizes" to
@@ -523,7 +536,43 @@ class CompilationConfig:
                     "(where 'op' is the registered op name)"
                 )
 
+        # Currently only eager and inductor backend are supported.
+        # for piecewise compilation. Custom backends are not suppported for
+        # piecewise compilation. Update when more backends are supported.
+        if self.level == CompilationLevel.PIECEWISE and self.backend not in [
+            "",
+            "eager",
+            "inductor",
+        ]:
+            raise ValueError(
+                f"Invalid backend for piecewise compilation: {self.backend}"
+            )
+
+        if self.use_inductor is not None:
+            logger.warning_once(
+                "The 'use_inductor' flag is deprecated and will be\
+                    removed in a future release."
+                "Please use the 'backend' option instead.",
+            )
+            self.backend = "inductor" if self.use_inductor else "eager"
+
+        if self.backend == "":
+            self.backend = "inductor"
+
     def init_backend(self, vllm_config: "VllmConfig") -> Union[str, Callable]:
+        """
+        Initialize the backend for the compilation config from a vllm config.
+        Arguments:
+            vllm_config: The vllm config to initialize the backend from.
+        Returns:
+            The backend for the compilation config.
+        """
+        if self.level is None:
+            raise ValueError(
+                "No compilation level is set. This method should only be \
+                called via vllm config where the level is set if none is \
+                provided."
+            )
         if self.level == CompilationLevel.NO_COMPILATION:
             raise ValueError("No compilation level is set.")
 
@@ -531,15 +580,15 @@ class CompilationConfig:
 
         torch_backends = list_backends(exclude_tags=tuple())
         if self.level in [CompilationLevel.DYNAMO_AS_IS, CompilationLevel.DYNAMO_ONCE]:
-            if self.backend == "":
-                return "eager"
             if self.backend in torch_backends:
                 return self.backend
             return resolve_obj_by_qualname(self.backend)
 
-        # TODO: pass user-specified backend to piecewise compilation
-        # merge with the config use_inductor
         assert self.level == CompilationLevel.PIECEWISE
+        if self.backend not in ["eager", "inductor"]:
+            raise ValueError(
+                f"Invalid backend for piecewise compilation: {self.backend}"
+            )
 
         from vllm.compilation.backends import VllmBackend
 
@@ -692,7 +741,7 @@ class CompilationConfig:
         )
 
         inductor_used = (
-            self.level == CompilationLevel.PIECEWISE and self.use_inductor
+            self.level == CompilationLevel.PIECEWISE and self.backend == "inductor"
         ) or (
             self.level >= CompilationLevel.DYNAMO_AS_IS and self.backend == "inductor"
         )