Update comment doc (#4731)

### What this PR does / why we need it?

Translate remaining Chinese comments in the `dispatch_ffn_combine` code
to English and update the installation guide to remind users to
initialize submodules when building from source.

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: mojave2 <chenchen145@huawei.com>
Signed-off-by: Chen Chen <0109chenchen@gmail.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>

csrc/dispatch_ffn_combine/op_host/aclnn_dispatch_ffn_combine.h

@@ -22,19 +22,22 @@ extern "C" {
 #endif
 
 /**
- * 算子功能：实现分布式MoE从InitRouting到Unpermute全部算子的融合
- * @brief aclnnDispatchFFNCombine的第一段接口，根据具体的计算流程，计算workspace大小。
+ * Operator function: fuse all distributed MoE ops from InitRouting through Unpermute.
+ * @brief First-stage interface of aclnnDispatchFFNCombine that calculates workspace size based on the specific compute flow.
  * @domain aclnn_ops_infer
- * @param [in] a: matmul左矩阵，数据类型支持：float16, bf16。
- * @param [in] b: matmul右矩阵，数据类型支持：float16, bf16。
- * @param [in] bias: 偏置，数据类型支持：float16, bf16。
- * @param [in] group: 标识通信域名称的字符串。
- * @param [in] worldsize: 通信域size，支持2/4/8卡。
- * @param [in] epRankId: ep本卡Id。取值范围[0, worldSize)，各卡的rankId不能重复
- * @param [out] c: 计算+通信的结果，数据类型：同输入。
- * @param [out] workspaceSize: 返回需要在npu device侧申请的workspace大小。
- * @param [out] executor: 返回op执行器，包含了算子计算流程。
- * @return aclnnStatus: 返回状态码
+ * @param [in] x: The input tensor.
+ * @param [in] weight1: The first weight tensor.
+ * @param [in] weight2: The second weight tensor.
+ * @param [in] expertId: The expert ID tensor.
+ * @param [in] scale1: The first scale tensor.
+ * @param [in] scale2: The second scale tensor.
+ * @param [in] probs: The probabilities tensor.
+ * @param [in] group: string identifying the communication domain name.
+ * @param [in] maxOutputSize: The maximum output size.
+ * @param [out] out: result of computation + communication; same dtype as input.
+ * @param [out] workspaceSize: workspace size to allocate on the NPU device side.
+ * @param [out] executor: op executor containing the operator compute flow.
+ * @return aclnnStatus: status code.
  */
 __attribute__((visibility("default"))) aclnnStatus aclnnDispatchFFNCombineGetWorkspaceSize(const aclTensor* x, const aclTensor* weight1, const aclTensor* weight2,
                                                                                         const aclTensor* expertId, const aclTensor* scale1, const aclTensor* scale2,
@@ -44,12 +47,12 @@ __attribute__((visibility("default"))) aclnnStatus aclnnDispatchFFNCombineGetWor
                                                                                         uint64_t* workspaceSize, aclOpExecutor** executor);
 
 /**
- * @brief aclnnDispatchGmmCombine的第二段接口，用于执行计算。
- * @param [in] workspace: 在npu device侧申请的workspace内存起址。
- * @param [in] workspace_size: 在npu device侧申请的workspace大小，由第一段接口aclnnDispatchFFNCombineGetWorkspaceSize获取。
- * @param [in] exector: op执行器，包含了算子计算流程。
- * @param [in] stream: acl stream流。
- * @return aclnnStatus: 返回状态码
+ * @brief Second-stage interface of aclnnDispatchFFNCombine to execute computation.
+ * @param [in] workspace: workspace memory address allocated on the NPU device side.
+ * @param [in] workspace_size: workspace size allocated on the NPU device side, obtained from aclnnDispatchFFNCombineGetWorkspaceSize.
+ * @param [in] executor: op executor containing the operator compute flow.
+ * @param [in] stream: acl stream.
+ * @return aclnnStatus: status code.
  */
 __attribute__((visibility("default"))) aclnnStatus aclnnDispatchFFNCombine(void* workspace, uint64_t workspaceSize, aclOpExecutor* executor,
                                            aclrtStream stream);
@@ -58,4 +61,4 @@ __attribute__((visibility("default"))) aclnnStatus aclnnDispatchFFNCombine(void*
 }
 #endif
 
-#endif  // OP_API_INC_GMM_ALLTOALLV_
+#endif  // OP_API_INC_DISPATCH_FFN_COMBINE_

csrc/dispatch_ffn_combine/op_host/dispatch_ffn_combine_def.cpp

@@ -56,7 +56,7 @@ class DispatchFFNCombine : public OpDef {
         .Format({ge::FORMAT_ND, ge::FORMAT_ND, ge::FORMAT_ND})
         .UnknownShapeFormat({ge::FORMAT_ND, ge::FORMAT_ND, ge::FORMAT_ND});
 
-    // 输出
+    // Output
     this->Output("out")
         .ParamType(REQUIRED)
         .DataType({ge::DT_FLOAT16, ge::DT_BF16, ge::DT_BF16})

csrc/dispatch_ffn_combine/op_host/dispatch_ffn_combine_tiling.cpp

@@ -27,7 +27,7 @@ using namespace AscendC;
 using namespace ge;
 
 namespace {
-    // 1. 常量定义
+    // 1. Constant definitions
     const char *K_INNER_DEBUG = "DispatchFFNCombine Tiling Debug";
     constexpr uint32_t ATTR_GROUP_INDEX = 0;
     constexpr uint32_t ATTR_MAX_OUTPUT_SIZE_INDEX = 1;
@@ -54,13 +54,13 @@ static int32_t CeilDev(int32_t num, int32_t div)
     return (num + div - 1) / div;
 }
 
-// 解析并校验 rankId, group, worldSize, isTransB 属性值
+// Parse and validate rankId, group, worldSize, and isTransB attributes
 static ge::graphStatus DispatchFFNCombineCheckAttrAndSetTiling(gert::TilingContext *context, DispatchFFNCombineInfo& info)
 {
     auto attrs = context->GetAttrs();
     OP_TILING_CHECK(attrs == nullptr, OP_LOGE(K_INNER_DEBUG, "attrs is null."), return ge::GRAPH_FAILED);
 
-    // todo：Attr相关tilingdata的设置、校验、打印
+    // TODO: set, validate, and print tiling data related to attributes
     auto groupPtr = attrs->GetAttrPointer<char>(static_cast<int>(ATTR_GROUP_INDEX));
     auto maxOutputSizePtr = attrs->GetAttrPointer<int>(ATTR_MAX_OUTPUT_SIZE_INDEX);
     auto is_trans_b = attrs->GetAttrPointer<bool>(ATTR_IS_TRANS_B);
@@ -87,7 +87,7 @@ static ge::graphStatus DispatchFFNCombineCheckAttrAndSetTiling(gert::TilingConte
     return ge::GRAPH_SUCCESS;
 }
 
-// 提取输入张量 A 和 B 的形状，计算出 M、K、N 值
+// Extract shapes of input tensors A and B to compute M, K, N
 static ge::graphStatus DispatchFFNCombineCheckShapeAndSetTiling(gert::TilingContext *context, DispatchFFNCombineInfo &info)
 {
     const char *nodeName = context->GetNodeName();
@@ -116,7 +116,7 @@ static ge::graphStatus DispatchFFNCombineCheckShapeAndSetTiling(gert::TilingCont
     return ge::GRAPH_SUCCESS;
 }
 
-// 获取当前芯片平台的 AI Core 数目、UB 容量等硬件信息。
+// Get hardware info such as AI Core count and UB capacity for the current chip platform.
 static ge::graphStatus DispatchFFNCombineGetPlatformInfoAndSetTiling(gert::TilingContext *context, DispatchFFNCombineInfo& info)
 {
     auto ascendcPlatform = platform_ascendc::PlatformAscendC(context->GetPlatformInfo());
@@ -146,9 +146,9 @@ void SetTilingData(CoCTiling &cocTilingData, DispatchFFNCombineInfo &info)
     cocTilingData.lenPerLoop = cocTilingData.m0 * cocTilingData.n0 / 2;
 }
 
-// 主调度函数：
-// 获取 tilingData ➝ 检查 Attr ➝ 检查 Shape ➝ 获取平台信息 
-// ➝ 调用 SetTilingData（根据rank数目） ➝ 设置 blockDim ➝ 设置 tilingKey ➝ 设置 workspace ➝ 配置通信参数
+// Main scheduling function:
+// Get tilingData ➝ check Attr ➝ check Shape ➝ get platform info 
+// ➝ call SetTilingData (based on rank count) ➝ set blockDim ➝ set tilingKey ➝ set workspace ➝ configure communication parameters
 
 static ge::graphStatus DispatchFFNCombineTilingFuncImpl(gert::TilingContext *context)
 {
@@ -262,4 +262,4 @@ ge::graphStatus TilingParseForDispatchFFNCombine(gert::TilingParseContext *conte
 IMPL_OP_OPTILING(DispatchFFNCombine)
     .Tiling(DispatchFFNCombineTilingFunc)
     .TilingParse<DispatchFFNCombineCompileInfo>(TilingParseForDispatchFFNCombine);
-} // namespace optiling
+} // namespace optiling

csrc/dispatch_ffn_combine/op_host/hcom_topo_info.h

@@ -64,8 +64,8 @@ class HcomTopoInfo {
   ~HcomTopoInfo() = default;
   std::unordered_map<std::string, TopoInfo> rank_info_;
   std::mutex mutex_;
-  std::unordered_map<std::string, void*> group_to_ordered_stream_; // 通信域保序流
-  std::unordered_map<int32_t, std::unordered_map<std::string, void*>> device_id_to_group_to_ordered_stream_; // 通信域保序流
+  std::unordered_map<std::string, void*> group_to_ordered_stream_; // Ordered stream for the communication domain
+  std::unordered_map<int32_t, std::unordered_map<std::string, void*>> device_id_to_group_to_ordered_stream_; // Ordered stream for the communication domain
 };
 }