Merge branch 'main' of https://github.com/InfiniTensor/InfiniCore into p800-add

src/infiniop/ops/swiglu/kunlun/kernel.h

+#ifndef __SWIGLU_KUNLUN_KERNEL_H__
+#define __SWIGLU_KUNLUN_KERNEL_H__
+
+namespace op::swiglu::kunlun {
+
+/// @brief SwiGLU op kernel
+typedef struct SwiGLUOp {
+private:
+    template <typename T>
+    inline __device__ T sigmoid(T x) const {
+        return 1.0f / (1.0f + exp(-x));
+    }
+    // float version of sigmoid
+    inline __device__ float sigmoidf(float x) const {
+        return 1.0f / (1.0f + exp(-x));
+    }
+
+public:
+    // This static number must be set in other Ops
+    static constexpr int num_inputs = 2;
+    template <typename T>
+    inline __device__ T operator()(const T *inputs) const {
+        T up = inputs[0];
+        T gate = inputs[1];
+        T out = gate * sigmoid(gate) * up;
+        return out;
+    }
+    // bfloat16 特化版本（使用 float 计算精度）
+    inline __device__ bfloat16_t operator()(const bfloat16_t *inputs) const {
+        float up_f = __bfloat162float(inputs[0]);
+        float gate_f = __bfloat162float(inputs[1]);
+
+        float out_f = gate_f * sigmoidf(gate_f) * up_f;
+        return __float2bfloat16(out_f);
+    }
+} SwiGLUOp;
+} // namespace op::swiglu::kunlun
+
+#endif // __SWIGLU_KUNLUN_KERNEL_H__

src/infiniop/ops/swiglu/kunlun/swiglu_kunlun.xpu

 #include "../../../elementwise/kunlun/elementwise_kunlun.h"
+#include "kernel.h"
 #include "swiglu_kunlun.h"
 
 namespace op::elementwise::kunlun {
 
-/// @brief SwiGLU op kernel
-typedef struct SwiGLUOp {
-private:
-    template <typename T>
-    inline __device__ T sigmoid(T x) const {
-        return 1.0f / (1.0f + exp(-x));
-    }
-    // float version of sigmoid
-    inline __device__ float sigmoidf(float x) const {
-        return 1.0f / (1.0f + exp(-x));
-    }
-
-public:
-    // This static number must be set in other Ops
-    static constexpr int num_inputs = 2;
-    template <typename T>
-    inline __device__ T operator()(const T *inputs) const {
-        T up = inputs[0];
-        T gate = inputs[1];
-        T out = gate * sigmoid(gate) * up;
-        return out;
-    }
-    // bfloat16 特化版本（使用 float 计算精度）
-    inline __device__ bfloat16_t operator()(const bfloat16_t *inputs) const {
-        float up_f = __bfloat162float(inputs[0]);
-        float gate_f = __bfloat162float(inputs[1]);
-
-        float out_f = gate_f * sigmoidf(gate_f) * up_f;
-        return __float2bfloat16(out_f);
-    }
-} SwiGLUOp;
+using SwiGLUOp = op::swiglu::kunlun::SwiGLUOp;
 
 // __global__ template function instantiation
 INSTANTIATE_ELEMENTWISE_KERNEL(SwiGLUOp::num_inputs, SwiGLUOp, float);
@@ -82,11 +53,11 @@ infiniStatus_t Descriptor::calculate(
 
     switch (_dtype) {
     case INFINI_DTYPE_F32:
-        return _device_info->calculate<8, op::elementwise::kunlun::SwiGLUOp, float>(_info, workspace, output, inputs, stream);
+        return _device_info->calculate<8, SwiGLUOp, float>(_info, workspace, output, inputs, stream);
     case INFINI_DTYPE_F16:
-        return _device_info->calculate<8, op::elementwise::kunlun::SwiGLUOp, half>(_info, workspace, output, inputs, stream);
+        return _device_info->calculate<8, SwiGLUOp, half>(_info, workspace, output, inputs, stream);
     case INFINI_DTYPE_BF16:
-        return _device_info->calculate<8, op::elementwise::kunlun::SwiGLUOp, bfloat16_t>(_info, workspace, output, inputs, stream);
+        return _device_info->calculate<8, SwiGLUOp, bfloat16_t>(_info, workspace, output, inputs, stream);
     default:
         return INFINI_STATUS_BAD_TENSOR_DTYPE;
     }