[Bugfix] Defunctionalize TRTLLM AR+Norm op for avoiding extra clone kernel before it (#29631)

Signed-off-by: elvischenv <219235043+elvischenv@users.noreply.github.com>
Signed-off-by: Luka Govedič <ProExpertProg@users.noreply.github.com>
Co-authored-by: Luka Govedič <ProExpertProg@users.noreply.github.com>

vllm/compilation/fix_functionalization.py

@@ -103,6 +103,18 @@ class FixFunctionalizationPass(VllmInductorPass):
             ]:
                 mutated_args = {1: "result"}
                 self.defunctionalize(graph, node, mutated_args)
+            elif (
+                at_target
+                == torch.ops.vllm.flashinfer_trtllm_fused_allreduce_norm.default
+            ):
+                mutated_args = {
+                    1: "allreduce_in",
+                    2: "residual",
+                    3: "norm_out",
+                    4: "quant_out",
+                    5: "scale_out",
+                }
+                self.defunctionalize(graph, node, mutated_args)
             # For some reason we need to specify the args for both
             # silu_and_mul and silu_and_mul_quant. The kwargs
             # pathway gets the wrong answer.

vllm/compilation/fx_utils.py

@@ -75,8 +75,8 @@ def find_op_nodes(
         return
 
     assert isinstance(op, OpOverload)
-    if not op._schema.is_mutable:
-        yield from graph.find_nodes(op="call_function", target=op)
+
+    yield from graph.find_nodes(op="call_function", target=op)
 
     for n in graph.find_nodes(op="call_function", target=auto_functionalized):
         if n.args[0] == op: