[BugFix][Fusion] Fix graph fusion failure problem

vllm_ascend/compilation/compiler_interface.py

@@ -26,6 +26,7 @@
 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
 from vllm_ascend.utils import COMPILATION_PASS_KEY
@@ -47,13 +48,13 @@ def fusion_pass_compile(
     graph: fx.GraphModule,
     example_inputs: list[Any],
     compiler_config: dict[str, Any],
-    runtime_shape: Optional[int] = None,
+    compile_range: Range,
     key: Optional[str] = None,
 ) -> tuple[Optional[Callable], Optional[Any]]:
 
     def compile_inner(graph, example_inputs):
         current_pass_manager = compiler_config[COMPILATION_PASS_KEY]
-        graph = current_pass_manager(graph, runtime_shape)
+        graph = current_pass_manager(graph)
         return graph
 
     decompositions = select_decomp_table()
@@ -72,7 +73,7 @@ def npugraph_ex_compile(
     graph: fx.GraphModule,
     example_inputs: list[Any],
     compiler_config: dict[str, Any],
-    runtime_shape: Optional[int] = None,
+    compile_range: Range,
     key: Optional[str] = None,
 ) -> tuple[Optional[Callable], Optional[Any]]:
     # When currently using the FULL_DECODE_ONLY mode,
@@ -125,14 +126,14 @@ def compile(
         graph: fx.GraphModule,
         example_inputs: list[Any],
         compiler_config: dict[str, Any],
-        runtime_shape: Optional[int] = None,
+        compile_range: Range,
         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,
-                                       runtime_shape, key)
+                                       compile_range, key)
         else:
             return fusion_pass_compile(graph, example_inputs, compiler_config,
-                                       runtime_shape, key)
+                                       compile_range, key)

vllm_ascend/compilation/graph_fusion_pass_manager.py

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

vllm_ascend/compilation/passes/norm_quant_fusion_pass.py

@@ -20,6 +20,7 @@
 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
 
 
@@ -308,7 +309,7 @@ def __call__(self, graph: torch.fx.Graph):
         logger.debug("Replaced %s patterns", self.matched_count)
         self.end_and_log()
 
-    def is_applicable(self, runtime_shape: int | None = None) -> bool:
+    def is_applicable_for_range(self, compile_range: Range) -> bool:
         """
         Check if the pass is applicable for the current configuration.
         """

vllm_ascend/compilation/passes/qknorm_rope_fusion_pass.py

@@ -22,6 +22,7 @@
 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
 
 
@@ -283,7 +284,7 @@ def __call__(self, graph: torch.fx.Graph):
                 pattern_idx += 1
         self.end_and_log()
 
-    def is_applicable(self, runtime_shape):
+    def is_applicable_for_range(self, compile_range: Range) -> bool:
         """
         Check if the pass is applicable for the current configuration.
         """

vllm_ascend/patch/__init__.py

@@ -106,20 +106,6 @@
 #    Future Plan:
 #       Remove this patch when vLLM merge the PR.
 #
-# ** 7. File: platform/patch_compile_backend.py**
-# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#   1. `vllm.compilation.backends.PiecewiseCompileInterpreter`
-#      `vllm.compilation.piecewise_backend.PiecewiseBackend`
-#    Why:
-#       vllm removed the compile graph for general shape, which caused operator fusion to fail.
-#       This issue affects the performance of model inference on Ascend.
-#    How：
-#       recover the compiled graph for dynamic_shape in PiecewiseBackend.
-#    Related PR (if no, explain why):
-#       https://github.com/vllm-project/vllm/pull/24252
-#    Future Plan:
-#       Remove this patch when fix the problem.
-#
 # * Worker Patch:
 # ===============
 #

vllm_ascend/patch/platform/__init__.py

@@ -16,7 +16,6 @@
 
 import os
 
-import vllm_ascend.patch.platform.patch_compile_backend  # noqa
 import vllm_ascend.patch.platform.patch_distributed  # noqa
 import vllm_ascend.patch.platform.patch_ec_connector  # noqa
 import vllm_ascend.patch.platform.patch_mamba_config  # noqa