[XPU] bump up xpu-kernel v0.1.5, transpose moe weights (#38342)

Signed-off-by: mayuyuace <qiming1.zhang@intel.com>
Signed-off-by: Qiming Zhang <qiming1.zhang@intel.com>
Signed-off-by: Kunshang Ji <kunshang.ji@intel.com>
Co-authored-by: Kunshang Ji <kunshang.ji@intel.com>

requirements/xpu.txt

@@ -15,4 +15,4 @@ torch==2.10.0+xpu
 torchaudio
 torchvision
 
-vllm_xpu_kernels @ https://github.com/vllm-project/vllm-xpu-kernels/releases/download/v0.1.4/vllm_xpu_kernels-0.1.4-cp38-abi3-manylinux_2_28_x86_64.whl
+vllm_xpu_kernels @ https://github.com/vllm-project/vllm-xpu-kernels/releases/download/v0.1.5/vllm_xpu_kernels-0.1.5-cp38-abi3-manylinux_2_28_x86_64.whl

vllm/model_executor/layers/fused_moe/unquantized_fused_moe_method.py

@@ -222,6 +222,18 @@ class UnquantizedFusedMoEMethod(FusedMoEMethodBase, CustomOp):
                     self.cpu_fused_moe = cpu_fused_moe.CPUFusedMOE(layer)
             else:
                 self.cpu_fused_moe = cpu_fused_moe.CPUFusedMOE(layer)
+        elif current_platform.is_xpu():
+            w13 = layer.w13_weight
+            w2 = layer.w2_weight
+
+            w13.data = w13.transpose(-1, -2).contiguous()
+            w2.data = w2.transpose(-1, -2).contiguous()
+
+            self._setup_kernel(
+                layer=layer,
+                w13=w13,
+                w2=w2,
+            )
         else:
             self._setup_kernel(
                 layer=layer,

vllm/model_executor/layers/quantization/fp8.py

@@ -1028,6 +1028,10 @@ class Fp8OnlineMoEMethod(Fp8MoEMethod):
                 layer.w2_weight[expert, :, :]
             )
 
+        if current_platform.is_xpu():
+            w13.data = w13.transpose(-1, -2).contiguous()
+            w2.data = w2.transpose(-1, -2).contiguous()
+
         # Shuffle weights to runtime format and setup kernel.
         self._setup_kernel(
             layer,