[MoE] Move xpu moe to fused_moe/experts/ (#40568)

Signed-off-by: Jackmin801 <ongjackm@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Kunshang Ji <kunshang.ji@intel.com>

.github/mergify.yml

@@ -262,7 +262,7 @@ pull_request_rules:
       - files~=^docker/Dockerfile.xpu
       - files~=^\\.buildkite/intel_jobs/
       - files=\.buildkite/ci_config_intel.yaml
-      - files=vllm/model_executor/layers/fused_moe/xpu_fused_moe.py
+      - files=vllm/model_executor/layers/fused_moe/experts/xpu_moe.py
       - files=vllm/model_executor/kernels/linear/mixed_precision/xpu.py
       - files=vllm/model_executor/kernels/linear/mxfp8/xpu.py
       - files=vllm/model_executor/kernels/linear/scaled_mm/xpu.py

vllm/model_executor/layers/fused_moe/__init__.py

@@ -85,6 +85,11 @@ if HAS_TRITON:
     from vllm.model_executor.layers.fused_moe.experts.deep_gemm_moe import (
         DeepGemmExperts,
     )
+    from vllm.model_executor.layers.fused_moe.experts.xpu_moe import (
+        XPUExperts,
+        XPUExpertsFp8,
+        XPUExpertsMXFp4,
+    )
     from vllm.model_executor.layers.fused_moe.fused_batched_moe import (
         BatchedTritonExperts,
     )
@@ -106,10 +111,6 @@ if HAS_TRITON:
     from vllm.model_executor.layers.fused_moe.triton_deep_gemm_moe import (
         TritonOrDeepGemmExperts,
     )
-    from vllm.model_executor.layers.fused_moe.xpu_fused_moe import (
-        XPUExperts,
-        XPUExpertsFp8,
-    )
 
     __all__ += [
         "AiterExperts",
@@ -129,6 +130,7 @@ if HAS_TRITON:
         "TritonOrDeepGemmExperts",
         "XPUExperts",
         "XPUExpertsFp8",
+        "XPUExpertsMXFp4",
     ]
 else:
     # Some model classes directly use the custom ops. Add placeholders

vllm/model_executor/layers/fused_moe/oracle/fp8.py

@@ -180,7 +180,7 @@ def backend_to_kernel_cls(
         return [CutlassBatchedExpertsFp8]
 
     elif backend == Fp8MoeBackend.XPU:
-        from vllm.model_executor.layers.fused_moe.xpu_fused_moe import (
+        from vllm.model_executor.layers.fused_moe.experts.xpu_moe import (
             XPUExpertsFp8,
         )
 
@@ -470,7 +470,7 @@ def convert_to_fp8_moe_kernel_format(
             is_trtllm=(fp8_backend == Fp8MoeBackend.FLASHINFER_TRTLLM),
         )
     elif fp8_backend == Fp8MoeBackend.XPU:
-        from vllm.model_executor.layers.fused_moe.xpu_fused_moe import (
+        from vllm.model_executor.layers.fused_moe.experts.xpu_moe import (
             prepare_fp8_moe_layer_for_xpu,
         )
 

vllm/model_executor/layers/fused_moe/oracle/mxfp4.py

@@ -141,7 +141,7 @@ def backend_to_kernel_cls(
         return [AiterExperts]
 
     elif backend == Mxfp4MoeBackend.XPU:
-        from vllm.model_executor.layers.fused_moe.xpu_fused_moe import XPUExpertsMXFp4
+        from vllm.model_executor.layers.fused_moe.experts.xpu_moe import XPUExpertsMXFp4
 
         return [XPUExpertsMXFp4]
 

vllm/model_executor/layers/fused_moe/oracle/unquantized.py

@@ -121,7 +121,7 @@ def backend_to_kernel_cls(
         return BatchedTritonExperts
 
     elif backend == UnquantizedMoeBackend.XPU:
-        from vllm.model_executor.layers.fused_moe.xpu_fused_moe import XPUExperts
+        from vllm.model_executor.layers.fused_moe.experts.xpu_moe import XPUExperts
 
         return XPUExperts