clean code (#4020)

custom_ops/gpu_ops/moe/fused_moe_helper.h

@@ -236,7 +236,7 @@ public:
                                                num_experts, k, stream);
     }
 
-    topk_gating_softmax_kernelLauncher<float, int>::run(
+    topk_gating_softmax_kernelLauncher<float, int>(
         gating_output, nullptr, expert_scales_float, softmax_out_,
         expert_for_source_row, source_rows_, softmax_max_prob, num_rows,
         num_experts, k, group_moe, stream);
@@ -248,7 +248,7 @@ public:
                 permuted_experts_, source_rows_, permuted_rows_, k * num_rows,
                 false, stream);
 
-    initialize_moe_routing_kernelLauncher<T>::run(
+    initialize_moe_routing_kernelLauncher(
         input_activations, permuted_data_, permuted_rows_, nullptr, nullptr,
         expanded_source_row_to_expanded_dest_row, num_rows, num_rows,
         hidden_size, k, stream);
@@ -335,14 +335,14 @@ public:
             num_experts, down_proj_quant_args, stream);
       }
 
-      finalize_moe_routing_kernelLauncher<T>::run(
+      finalize_moe_routing_kernelLauncher(
           fc2_result, output_, fc2_expert_biases,
           reinterpret_cast<float *>(expert_scales_float),
           expanded_source_row_to_expanded_dest_row, expert_for_source_row,
           num_rows, hidden_size, k, static_cast<int>(1), norm_topk_prob,
           routed_scaling_factor, stream);
     } else {
-      finalize_moe_routing_kernelLauncher<T>::run(
+      finalize_moe_routing_kernelLauncher(
           // fc2_result,
           fc1_out, output_,
           fc1_expert_biases, // fc2_expert_biases,

custom_ops/gpu_ops/moe/fused_moe_op.h

@@ -1139,9 +1139,7 @@ void topk_gating_softmax_launcher_helper(const T* input,
 }
 
 template <typename T, typename IdxT = int>
-struct topk_gating_softmax_kernelLauncher{
-
-static void run(const T* input,
+void topk_gating_softmax_kernelLauncher(const T* input,
                                         const T* gating_correction_bias,
                                         T* output,
                                         T* softmax,
@@ -1221,7 +1219,6 @@ static void run(const T* input,
     }
   }
 }
-};
 
 // ========================== Permutation things
 // =======================================
@@ -1316,9 +1313,7 @@ __global__ void initialize_moe_routing_kernel(
 }
 
 template <typename T, typename OutT = T>
-struct initialize_moe_routing_kernelLauncher{
-
-static void run(
+void initialize_moe_routing_kernelLauncher(
     const T* unpermuted_input,
     OutT* permuted_output,
     const int* expanded_dest_row_to_expanded_source_row,
@@ -1361,7 +1356,6 @@ static void run(
             num_rows * k);
   }
 }
-};
 
 // ============================== Infer GEMM sizes
 // =================================
@@ -1472,8 +1466,7 @@ __global__ void finalize_moe_routing_kernel(
 }
 
 template <typename T>
-struct finalize_moe_routing_kernelLauncher{
-static void run(
+void finalize_moe_routing_kernelLauncher(
     const T* expanded_permuted_rows,
     T* reduced_unpermuted_output,
     const T* bias,
@@ -1505,5 +1498,4 @@ static void run(
             routed_scaling_factor,
             num_rows);
 }
-};
 }  // namespace phi

custom_ops/gpu_ops/moe/moe_dispatch.cu

@@ -100,7 +100,7 @@ void MoeDispatchKernel(
     softmax_out_ = nullptr;
   }
 
-  topk_gating_softmax_kernelLauncher<float, int>::run(
+  topk_gating_softmax_kernelLauncher(
       gating_output.data<float>(),
       gating_correction_bias ? gating_correction_bias.get().data<float>()
                              : nullptr,
@@ -114,13 +114,13 @@ void MoeDispatchKernel(
 
   if (w4a8_in_scale) {
     if (permute_input->dtype() == paddle::DataType::INT8) {
-      initialize_moe_routing_kernelLauncher<data_t, int8_t>::run(
+      initialize_moe_routing_kernelLauncher(
         input.data<data_t>(), permute_input->data<int8_t>(), permuted_rows_,
         expert_idx_per_token->data<int32_t>(), w4a8_in_scale->data<float>(),
         permute_indices_per_token->data<int32_t>(), num_rows, num_rows,
         hidden_size, moe_topk, stream);
     } else if (permute_input->dtype() == paddle::DataType::FLOAT8_E4M3FN) {
-      initialize_moe_routing_kernelLauncher<data_t, float8_e4m3fn>::run(
+      initialize_moe_routing_kernelLauncher(
         input.data<data_t>(), permute_input->data<float8_e4m3fn>(),
         permuted_rows_, expert_idx_per_token->data<int32_t>(),
         w4a8_in_scale->data<float>(),
@@ -128,7 +128,7 @@ void MoeDispatchKernel(
         hidden_size, moe_topk, stream);
     }
   } else {
-    initialize_moe_routing_kernelLauncher<data_t>::run(
+    initialize_moe_routing_kernelLauncher(
         input.data<data_t>(), permute_input->data<data_t>(), permuted_rows_,
         expert_idx_per_token->data<int32_t>(), nullptr,
         permute_indices_per_token->data<int32_t>(), num_rows, num_rows,

custom_ops/gpu_ops/moe/moe_reduce.cu

@@ -36,7 +36,7 @@ void MoeReduceKernel(const paddle::Tensor &ffn_out,
   typedef typename traits_::data_t data_t;
   auto stream = ffn_out.stream();
 
-  finalize_moe_routing_kernelLauncher<data_t>::run(
+  finalize_moe_routing_kernelLauncher(
       ffn_out.data<data_t>(), output->data<data_t>(),
       down_proj_bias ? down_proj_bias->data<data_t>() : nullptr,
       top_k_weight.data<float>(), permute_indices_per_token.data<int32_t>(),