[BugFix][torch.compile] Fix fused_scaled_matmul_reduce_scatter signature for PyTorch 2.8 (#26038)

Signed-off-by: jasonlizhengjian <jasonlizhengjian@gmail.com>
Signed-off-by: <>
Signed-off-by: Luka Govedič <ProExpertProg@users.noreply.github.com>
Co-authored-by: Luka Govedič <ProExpertProg@users.noreply.github.com>

.buildkite/test-pipeline.yaml

@@ -400,8 +400,6 @@ steps:
     - pytest -v -s compile/test_fusion_attn.py
     - pytest -v -s compile/test_functionalization.py
     - pytest -v -s compile/test_silu_mul_quant_fusion.py
-    - pytest -v -s compile/test_sequence_parallelism.py
-    - pytest -v -s compile/test_async_tp.py
     - pytest -v -s compile/test_fusion_all_reduce.py
     - pytest -v -s compile/test_decorator.py
     - pytest -v -s compile/test_noop_elimination.py
@@ -1093,6 +1091,8 @@ steps:
   working_dir: "/vllm-workspace/"
   num_gpus: 2
   commands:
+    - pytest -v -s tests/compile/test_async_tp.py
+    - pytest -v -s tests/compile/test_sequence_parallelism.py
     - pytest -v -s tests/distributed/test_context_parallel.py
     - CUDA_VISIBLE_DEVICES=1,2 VLLM_ALL2ALL_BACKEND=deepep_high_throughput VLLM_USE_DEEP_GEMM=1 VLLM_LOGGING_LEVEL=DEBUG python3 examples/offline_inference/data_parallel.py --model Qwen/Qwen1.5-MoE-A2.7B --tp-size=1  --dp-size=2 --max-model-len 2048
 

vllm/compilation/collective_fusion.py

@@ -169,15 +169,23 @@ class ScaledMMReduceScatterPattern(BasePattern):
             scale_a: torch.Tensor,
             scale_b: torch.Tensor,
         ) -> torch.Tensor:
+            # Calculate output shape: input @ mat2 with scatter_dim reduced
+            output_shape = [*input.shape[:-1], mat2.shape[1]]
+            scatter_dim = 0
             gemm_rs = torch.ops.symm_mem.fused_scaled_matmul_reduce_scatter(
                 input,
                 mat2,
                 scale_a,
                 scale_b,
                 "avg",
-                scatter_dim=0,
+                scatter_dim,  # orig_scatter_dim
-                out_dtype=self.dtype,
+                scatter_dim,  # scatter_dim_after_maybe_reshape
-                group_name=self.tp.device_group.group_name,
+                self.tp.device_group.group_name,
+                output_shape,
+                None,  # bias
+                None,  # result_scale
+                self.dtype,  # out_dtype
+                False,  # use_fast_accum
             )
 
             return gemm_rs
@@ -296,15 +304,23 @@ class CutlassScaledMMReduceScatterPattern(BasePattern):
             scale_b: torch.Tensor,
             cutlass_mm_output: torch.Tensor,
         ) -> torch.Tensor:
+            # Calculate output shape: input @ mat2 with scatter_dim reduced
+            output_shape = [*input.shape[:-1], mat2.shape[1]]
+            scatter_dim = 0
             gemm_rs = torch.ops.symm_mem.fused_scaled_matmul_reduce_scatter(
                 input,
                 mat2,
                 scale_a,
                 scale_b,
                 "avg",
-                scatter_dim=0,
+                scatter_dim,  # orig_scatter_dim
-                out_dtype=self.dtype,
+                scatter_dim,  # scatter_dim_after_maybe_reshape
-                group_name=self.tp.device_group.group_name,
+                self.tp.device_group.group_name,
+                output_shape,
+                None,  # bias
+                None,  # result_scale
+                self.dtype,  # out_dtype
+                False,  # use_fast_accum
             )
 
             return gemm_rs