Revert "[BugFix][Fusion] Fix graph fusion failure problem (#5253)" (#5667)

### What this PR does / why we need it?

Revert PR 5253 to fix the smoking problem

### Does this PR introduce _any_ user-facing change?

Does not.

### How was this patch tested?

It was tested in the failure case.

Signed-off-by: Rifa <865071616@qq.com>

vllm_ascend/compilation/compiler_interface.py

@@ -26,7 +26,6 @@ from torch._inductor.compile_fx import (graph_returns_tuple,
 from torch._inductor.decomposition import select_decomp_table
 from torch.fx import GraphModule
 from vllm.compilation.compiler_interface import CompilerInterface
-from vllm.config.utils import Range
 
 from vllm_ascend.ascend_config import get_ascend_config
 
@@ -47,13 +46,13 @@ def fusion_pass_compile(
     graph: fx.GraphModule,
     example_inputs: list[Any],
     compiler_config: dict[str, Any],
-    compile_range: Range,
+    runtime_shape: Optional[int] = None,
     key: Optional[str] = None,
 ) -> tuple[Optional[Callable], Optional[Any]]:
 
     def compile_inner(graph, example_inputs):
         current_pass_manager = compiler_config["graph_fusion_manager"]
-        graph = current_pass_manager(graph, compile_range)
+        graph = current_pass_manager(graph, runtime_shape)
         return graph
 
     decompositions = select_decomp_table()
@@ -72,7 +71,7 @@ def npugraph_ex_compile(
     graph: fx.GraphModule,
     example_inputs: list[Any],
     compiler_config: dict[str, Any],
-    compile_range: Range,
+    runtime_shape: Optional[int] = None,
     key: Optional[str] = None,
 ) -> tuple[Optional[Callable], Optional[Any]]:
     # When currently using the FULL_DECODE_ONLY mode,
@@ -125,14 +124,14 @@ class AscendCompiler(CompilerInterface):
         graph: fx.GraphModule,
         example_inputs: list[Any],
         compiler_config: dict[str, Any],
-        compile_range: Range,
+        runtime_shape: Optional[int] = None,
         key: Optional[str] = None,
     ) -> tuple[Optional[Callable], Optional[Any]]:
 
         ascend_config = get_ascend_config()
         if ascend_config.enable_npugraph_ex:
             return npugraph_ex_compile(graph, example_inputs, compiler_config,
-                                       compile_range, key)
+                                       runtime_shape, key)
         else:
             return fusion_pass_compile(graph, example_inputs, compiler_config,
-                                       compile_range, key)
+                                       runtime_shape, key)

vllm_ascend/compilation/graph_fusion_pass_manager.py

@@ -17,7 +17,6 @@
 #
 
 from torch import fx as fx
-from vllm.compilation.inductor_pass import get_pass_context
 from vllm.compilation.vllm_inductor_pass import VllmInductorPass
 from vllm.config import VllmConfig
 
@@ -33,13 +32,10 @@ class GraphFusionPassManager:
     def __init__(self):
         self.passes: list[VllmInductorPass] = []
 
-    def __call__(self, graph: fx.Graph, compile_range) -> fx.Graph:
-        compile_range = get_pass_context().compile_range
-
+    def __call__(self, graph: fx.Graph, runtime_shape) -> fx.Graph:
         for pass_ in self.passes:
-            if pass_.is_applicable_for_range(compile_range):
+            if pass_.is_applicable(runtime_shape):
                 pass_(graph)
-        graph.recompile()
         return graph
 
     def add(self, pass_: VllmInductorPass):

vllm_ascend/compilation/passes/norm_quant_fusion_pass.py

@@ -20,7 +20,6 @@ import torch._inductor.pattern_matcher as pm
 from torch._inductor.pattern_matcher import PatternMatcherPass
 from vllm.compilation.vllm_inductor_pass import VllmInductorPass
 from vllm.config import VllmConfig
-from vllm.config.compilation import Range
 from vllm.logger import logger
 
 
@@ -309,7 +308,7 @@ class AddRMSNormQuantFusionPass(VllmInductorPass):
         logger.debug("Replaced %s patterns", self.matched_count)
         self.end_and_log()
 
-    def is_applicable_for_range(self, compile_range: Range) -> bool:
+    def is_applicable(self, runtime_shape: int | None = None) -> bool:
         """
         Check if the pass is applicable for the current configuration.
         """

vllm_ascend/compilation/passes/qknorm_rope_fusion_pass.py

@@ -22,7 +22,6 @@ from torch._inductor.pattern_matcher import (PatternMatcherPass,
 from vllm.attention.layer import Attention
 from vllm.compilation.vllm_inductor_pass import VllmInductorPass
 from vllm.config import VllmConfig, get_layers_from_vllm_config
-from vllm.config.compilation import Range
 from vllm.logger import logger
 
 
@@ -284,7 +283,7 @@ class QKNormRopeFusionPass(VllmInductorPass):
                 pattern_idx += 1
         self.end_and_log()
 
-    def is_applicable_for_range(self, compile_range: Range) -> bool:
+    def is_applicable(self, runtime_shape):
         """
         Check if the pass is applicable for the current configuration.
         """