Sync v2.0 version of code to github repo

custom_ops/gpu_ops/moe/deepgemm_preprocess.cu

@@ -0,0 +1,61 @@
+// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "helper.h"
+#include "paddle/extension.h"
+
+template <typename scalar_t>
+__global__ void
+cuda_kernel(const scalar_t *__restrict__ topk_ids, int32_t *__restrict__ res,
+            int32_t *__restrict__ res_padded, size_t numel, int num_experts) {
+
+  extern __shared__ int32_t tokens_per_ep[];
+
+  for (size_t i = threadIdx.x; i < num_experts; i += blockDim.x) {
+    tokens_per_ep[i] = 0;
+  }
+  __syncthreads();
+
+  for (size_t i = threadIdx.x; i < numel; i += blockDim.x) {
+    int32_t expert_id = topk_ids[i];
+    if(expert_id >= 0) atomicAdd(&tokens_per_ep[expert_id], 1);
+  }
+
+  __syncthreads();
+
+  for (size_t i = threadIdx.x; i < num_experts; i += blockDim.x) {
+    res[i] = tokens_per_ep[i];
+    res_padded[i] = (res[i] + 127) / 128 * 128;
+  }
+}
+
+paddle::Tensor count_tokens_per_expert_func(const paddle::Tensor &topk_ids,
+                                            int64_t num_experts) {
+
+  int topk_ids_numel = topk_ids.shape()[0] * topk_ids.shape()[1];
+
+  auto token_nums_per_expert = paddle::empty(
+      {2, num_experts}, paddle::DataType::INT32, topk_ids.place());
+
+  auto stream = topk_ids.stream();
+  using scalar_t = int64_t;
+
+  cuda_kernel<<<1, 1024, num_experts * sizeof(int32_t), stream>>>(
+      topk_ids.data<scalar_t>(), token_nums_per_expert.data<int32_t>(),
+      token_nums_per_expert.data<int32_t>() + num_experts, topk_ids_numel,
+      num_experts);
+  return token_nums_per_expert;
+}
+
+