!2750 Clean review bot warning.

Merge pull request !2750 from TronZhang/clean_bot

mindspore/ccsrc/kernel/akg/akg_kernel_build.cc

@@ -618,6 +618,5 @@ size_t AkgKernelBuild::GetOutputTensorIdxInc() {
   size_t idx = output_tensor_idx_++;
   return idx;
 }
-
 }  // namespace kernel
 }  // namespace mindspore

mindspore/ccsrc/kernel/akg/akg_kernel_build.h

@@ -70,7 +70,6 @@ void SetTensorName(const std::string &tag, const std::string &new_name, const st
                    nlohmann::json *const node_json);
 std::string GetTensorName(const nlohmann::json &node_json, const std::string &tag,
                           const std::pair<size_t, size_t> &position);
-
 }  // namespace kernel
 }  // namespace mindspore
 

mindspore/ccsrc/kernel/akg/ascend/akg_ascend_kernel_build.cc

@@ -35,7 +35,6 @@
 
 namespace mindspore {
 namespace kernel {
-
 constexpr int32_t PARALLEL_ARGS_SIZE = 3;
 constexpr int32_t PROCESS_NUM = 16;
 constexpr int32_t TIME_OUT = 300;
@@ -48,76 +47,9 @@ constexpr auto kOutputDesc = "output_desc";
 constexpr auto kTensorName = "tensor_name";
 constexpr auto kCompileAkgKernelParallelFunc = "compile_akg_kernel_parallel";
 constexpr auto kMultiProcModule = "mindspore._extends.parallel_compile.akg_compiler.multi_process_compiler";
-
-bool AkgAscendKernelBuilder::CollectJson(const AnfNodePtr &anf_node) {
-  MS_EXCEPTION_IF_NULL(anf_node);
-  std::string op_name = AnfAlgo::GetCNodeName(anf_node);
-  MS_LOG(INFO) << "AKG start compile, op[" << op_name << "], device[" << AkgKernelBuild::GetProcessor(anf_node) << "]";
-  auto it = kAkgKernelAttrsProcessMap.find(op_name);
-  if (it != kAkgKernelAttrsProcessMap.end()) {
-    it->second(anf_node);
-  }
-  MS_LOG(INFO) << "Akg start compile, op[" << op_name << "], device[" << AkgKernelBuild::GetProcessor(anf_node) << "]";
-  nlohmann::json node_json;
-  if (!GenerateSingleKernelJson(anf_node, op_name, &node_json)) {
-    MS_LOG(ERROR) << "Op[" << op_name << "] create single kernel json failed.";
-  }
-
-  kernel_json_ = node_json.dump();
-
-  if (!GetIOSize(node_json, &input_size_list_, &output_size_list_)) {
-    MS_LOG(ERROR) << "Cal mem size failed.";
-    return false;
-  }
-
-  return true;
-}
-
-bool AkgAscendKernelBuilder::CollectFusedJson(const std::vector<AnfNodePtr> &anf_nodes,
-                                              const std::vector<AnfNodePtr> &input_list,
-                                              const std::vector<AnfNodePtr> &output_list) {
-  if (anf_nodes.empty() || input_list.empty()) {
-    MS_LOG(ERROR) << "Invalid input size, anf_nodes [" << anf_nodes.size() << "], input_list [" << input_list.size()
-                  << "].";
-    return false;
-  }
-  MS_LOG(INFO) << "anf_nodes [" << output_list.size() << "], input_list [" << anf_nodes.size() << "], output_list ["
-               << input_list.size() << "].";
-
-  std::map<AnfNodePtr, nlohmann::json> node_json_map;
-
-  for (auto const &anf_node : anf_nodes) {
-    MS_EXCEPTION_IF_NULL(anf_node);
-    std::string op_name = AnfAlgo::GetCNodeName(anf_node);
-    if (!AnfAlgo::IsRealKernel(anf_node)) {
-      MS_LOG(ERROR) << "Invalid anf node to build [" << anf_node->fullname_with_scope() << "].";
-      return false;
-    }
-    auto it = kAkgKernelAttrsProcessMap.find(op_name);
-    if (it != kAkgKernelAttrsProcessMap.end()) {
-      it->second(anf_node);
-    }
-
-    nlohmann::json node_json;
-    if (!GenerateSingleKernelJson(anf_node, op_name, &node_json)) {
-      MS_LOG(ERROR) << "Op [" << op_name << "] create single kernel json failed.";
-      return false;
-    }
-    // No need for composite op.
-    node_json.erase("id");
-    node_json.erase("op");
-    node_json.erase("composite");
-
-    auto primitive = AnfAlgo::GetCNodePrimitive(anf_node);
-    MS_EXCEPTION_IF_NULL(primitive);
-
-    if (primitive->GetAttr("fusion") != nullptr) {
-      node_json["fusion"] = primitive->GetAttr("fusion")->ToString();
-    }
-
-    node_json_map[anf_node] = node_json;
-  }
-
+namespace {
+void UpdateTensorNameInJson(const std::vector<AnfNodePtr> &anf_nodes,
+                            std::map<AnfNodePtr, nlohmann::json> *node_json_map) {
   for (auto const &anf_node : anf_nodes) {
     std::vector<int> dyn_input_sizes;
     auto primitive = AnfAlgo::GetCNodePrimitive(anf_node);
@@ -134,11 +66,11 @@ bool AkgAscendKernelBuilder::CollectFusedJson(const std::vector<AnfNodePtr> &anf
       size_t input_tensor_num = is_dynamic_input ? IntToSize(dyn_input_sizes[i]) : 1;
       for (size_t j = 0; j < input_tensor_num; ++j) {
         auto tmp_input = GetKernelInput(anf_node, real_input_index);
-        std::string tensor_name = GetTensorName(node_json_map[anf_node], kInputDesc, std::make_pair(i, j));
-        if (node_json_map.find(tmp_input.first) != node_json_map.end()) {
+        std::string tensor_name = GetTensorName((*node_json_map)[anf_node], kInputDesc, std::make_pair(i, j));
+        if (node_json_map->find(tmp_input.first) != node_json_map->end()) {
           std::string new_tensor_name =
-            GetTensorName(node_json_map[tmp_input.first], kOutputDesc, std::make_pair(0, tmp_input.second));
-          SetTensorName(kInputDesc, new_tensor_name, std::make_pair(i, j), &(node_json_map[anf_node]));
+            GetTensorName((*node_json_map)[tmp_input.first], kOutputDesc, std::make_pair(0, tmp_input.second));
+          SetTensorName(kInputDesc, new_tensor_name, std::make_pair(i, j), &((*node_json_map)[anf_node]));
           MS_LOG(DEBUG) << "Update [" << real_input_index << "] input [" << tensor_name << "] of ["
                         << anf_node->fullname_with_scope() << "] to [" << tmp_input.second << "] output ["
                         << new_tensor_name << "] of [" << tmp_input.first->fullname_with_scope() << "].";
@@ -150,13 +82,10 @@ bool AkgAscendKernelBuilder::CollectFusedJson(const std::vector<AnfNodePtr> &anf
       }
     }
   }
+}
 
-  nlohmann::json fused_node_json;
-  std::vector<nlohmann::json> node_json_desc;
-  std::transform(anf_nodes.begin(), anf_nodes.end(), std::back_inserter(node_json_desc),
-                 [&node_json_map](const AnfNodePtr &anf_node) { return node_json_map[anf_node]; });
-  fused_node_json[kOpDesc] = node_json_desc;
-
+nlohmann::json GetInputsJson(const std::vector<AnfNodePtr> &anf_nodes, const std::vector<AnfNodePtr> &input_list,
+                             std::map<AnfNodePtr, nlohmann::json> *node_json_map) {
   nlohmann::json inputs_json;
   auto input_index = GetInputIndex(anf_nodes, input_list);
   for (size_t i = 0; i < input_index.size(); ++i) {
@@ -164,13 +93,18 @@ bool AkgAscendKernelBuilder::CollectFusedJson(const std::vector<AnfNodePtr> &anf
     auto type_id = AnfAlgo::GetInputDeviceDataType(tmp_input.first, tmp_input.second.first);
     std::string dtype = TypeId2String(type_id);
     nlohmann::json input_desc_json;
-    input_desc_json[kTensorName] = GetTensorName(node_json_map[tmp_input.first], kInputDesc, tmp_input.second);
+    input_desc_json[kTensorName] = GetTensorName((*node_json_map)[tmp_input.first], kInputDesc, tmp_input.second);
     input_desc_json[kDataType] = dtype;
     input_desc_json[kShape] = AnfAlgo::GetInputDeviceShape(tmp_input.first, tmp_input.second.first);
     inputs_json.emplace_back(std::vector<nlohmann::json>{input_desc_json});
   }
-  fused_node_json[kInputDesc] = inputs_json;
 
+  return inputs_json;
+}
+
+nlohmann::json GetOutputsJson(const std::vector<AnfNodePtr> &anf_nodes, const std::vector<AnfNodePtr> &input_list,
+                              const std::vector<AnfNodePtr> &output_list, const nlohmann::json &inputs_json,
+                              std::map<AnfNodePtr, nlohmann::json> *node_json_map) {
   nlohmann::json outputs_json;
   auto output_index = GetOutputIndex(anf_nodes, input_list, output_list);
   for (size_t i = 0; i < output_index.size(); ++i) {
@@ -188,7 +122,7 @@ bool AkgAscendKernelBuilder::CollectFusedJson(const std::vector<AnfNodePtr> &anf
       auto type_id = AnfAlgo::GetOutputDeviceDataType(tmp_output.first, tmp_output.second);
       std::string dtype = TypeId2String(type_id);
       output_desc_json[kTensorName] =
-        GetTensorName(node_json_map[tmp_output.first], kOutputDesc, std::make_pair(0, tmp_output.second));
+        GetTensorName((*node_json_map)[tmp_output.first], kOutputDesc, std::make_pair(0, tmp_output.second));
       output_desc_json[kDataType] = dtype;
       auto output_shape = AnfAlgo::GetOutputDeviceShape(tmp_output.first, tmp_output.second);
       if (output_shape.empty()) {
@@ -198,7 +132,166 @@ bool AkgAscendKernelBuilder::CollectFusedJson(const std::vector<AnfNodePtr> &anf
     }
     outputs_json.emplace_back(output_desc_json);
   }
-  fused_node_json[kOutputDesc] = outputs_json;
+
+  return outputs_json;
+}
+
+std::pair<std::vector<std::string>, std::vector<std::pair<AkgAscendKernelBuilder, AnfNodePtr>>> PreProcessJsonForBuild(
+  const std::vector<std::pair<AkgAscendKernelBuilder, AnfNodePtr>> &build_args) {
+  // Remove cached nodes, gether unique nodes, and collect repeated nodes which need postprecess.
+  std::vector<std::string> jsons;
+  std::vector<std::pair<AkgAscendKernelBuilder, AnfNodePtr>> repeat_nodes;
+  std::unordered_set<std::string> json_name_set;
+  for (const auto &[builder, anf_node] : build_args) {
+    MS_EXCEPTION_IF_NULL(anf_node);
+    auto json_name = builder.json_name();
+    MS_LOG(DEBUG) << "Akg start compile op: " << json_name;
+    auto cached_kernel_pack = tbe::TbeUtils::SearchCache(json_name, AkgKernelBuild::GetProcessor(anf_node));
+    if (cached_kernel_pack != nullptr) {
+      MS_LOG(DEBUG) << "Use cached kernel, json_name_[" << json_name << "], fullname_with_scope["
+                    << anf_node->fullname_with_scope() << "].";
+      auto kernel_mod_ptr = std::make_shared<AkgKernelMod>(cached_kernel_pack);
+      kernel_mod_ptr->SetInputSizeList(builder.input_size_list());
+      kernel_mod_ptr->SetOutputSizeList(builder.output_size_list());
+      AnfAlgo::SetKernelMod(kernel_mod_ptr, anf_node.get());
+      continue;
+    }
+
+    if (json_name_set.count(json_name) != 0) {
+      repeat_nodes.push_back({builder, anf_node});
+      continue;
+    }
+    json_name_set.insert(json_name);
+    auto node_json = builder.kernel_json();
+    kernel::SaveJsonInfo(json_name, node_json);
+    jsons.push_back(node_json);
+  }
+
+  return std::make_pair(jsons, repeat_nodes);
+}
+
+bool PostProcessAfterCompile(const std::vector<std::pair<AkgAscendKernelBuilder, AnfNodePtr>> &build_args,
+                             const std::vector<std::pair<AkgAscendKernelBuilder, AnfNodePtr>> &repeat_nodes) {
+  for (const auto &[builder, anf_node] : build_args) {
+    auto json_name = builder.json_name();
+    auto new_kernel_pack = tbe::TbeUtils::InsertCache(json_name, AkgKernelBuild::GetProcessor(anf_node));
+    if (new_kernel_pack == nullptr) {
+      MS_LOG(ERROR) << "Insert to cache failed, json_name_[" << json_name << "], fullname_with_scope["
+                    << anf_node->fullname_with_scope() << "].";
+      return false;
+    }
+    auto kernel_mod_ptr = std::make_shared<AkgKernelMod>(new_kernel_pack);
+    kernel_mod_ptr->SetInputSizeList(builder.input_size_list());
+    kernel_mod_ptr->SetOutputSizeList(builder.output_size_list());
+    AnfAlgo::SetKernelMod(kernel_mod_ptr, anf_node.get());
+    MS_LOG(DEBUG) << "Akg compile " << json_name << " kernel and insert cache successfully!";
+  }
+
+  for (const auto &[builder, anf_node] : repeat_nodes) {
+    auto node_json = builder.kernel_json();
+    auto json_name = builder.json_name();
+    auto cached_kernel_pack = tbe::TbeUtils::SearchCache(json_name, AkgKernelBuild::GetProcessor(anf_node));
+    if (cached_kernel_pack == nullptr) {
+      return false;
+    }
+    MS_LOG(INFO) << "Use just compiled kernel, json_name_[" << json_name << "], fullname_with_scope["
+                 << anf_node->fullname_with_scope() << "].";
+    auto kernel_mod_ptr = std::make_shared<AkgKernelMod>(cached_kernel_pack);
+    kernel_mod_ptr->SetInputSizeList(builder.input_size_list());
+    kernel_mod_ptr->SetOutputSizeList(builder.output_size_list());
+    AnfAlgo::SetKernelMod(kernel_mod_ptr, anf_node.get());
+  }
+
+  return true;
+}
+}  // namespace
+
+bool AkgAscendKernelBuilder::CollectJson(const AnfNodePtr &anf_node) {
+  MS_EXCEPTION_IF_NULL(anf_node);
+  std::string op_name = AnfAlgo::GetCNodeName(anf_node);
+  MS_LOG(INFO) << "AKG start compile, op[" << op_name << "], device[" << AkgKernelBuild::GetProcessor(anf_node) << "]";
+  auto it = kAkgKernelAttrsProcessMap.find(op_name);
+  if (it != kAkgKernelAttrsProcessMap.end()) {
+    it->second(anf_node);
+  }
+  MS_LOG(INFO) << "Akg start compile, op[" << op_name << "], device[" << AkgKernelBuild::GetProcessor(anf_node) << "]";
+  nlohmann::json node_json;
+  if (!GenerateSingleKernelJson(anf_node, op_name, &node_json)) {
+    MS_LOG(ERROR) << "Op[" << op_name << "] create single kernel json failed.";
+  }
+
+  kernel_json_ = node_json.dump();
+
+  if (!GetIOSize(node_json, &input_size_list_, &output_size_list_)) {
+    MS_LOG(ERROR) << "Cal mem size failed.";
+    return false;
+  }
+
+  return true;
+}
+
+bool AkgAscendKernelBuilder::GenJsonAndPreprocess4Fused(const std::vector<AnfNodePtr> &anf_nodes,
+                                                        std::map<AnfNodePtr, nlohmann::json> *node_json_map) {
+  for (auto const &anf_node : anf_nodes) {
+    MS_EXCEPTION_IF_NULL(anf_node);
+    std::string op_name = AnfAlgo::GetCNodeName(anf_node);
+    if (!AnfAlgo::IsRealKernel(anf_node)) {
+      MS_LOG(ERROR) << "Invalid anf node to build [" << anf_node->fullname_with_scope() << "].";
+      return false;
+    }
+    auto it = kAkgKernelAttrsProcessMap.find(op_name);
+    if (it != kAkgKernelAttrsProcessMap.end()) {
+      it->second(anf_node);
+    }
+
+    nlohmann::json node_json;
+    if (!GenerateSingleKernelJson(anf_node, op_name, &node_json)) {
+      MS_LOG(ERROR) << "Op [" << op_name << "] create single kernel json failed.";
+      return false;
+    }
+    // No need for composite op.
+    node_json.erase("id");
+    node_json.erase("op");
+    node_json.erase("composite");
+
+    auto primitive = AnfAlgo::GetCNodePrimitive(anf_node);
+    MS_EXCEPTION_IF_NULL(primitive);
+
+    if (primitive->GetAttr("fusion") != nullptr) {
+      node_json["fusion"] = primitive->GetAttr("fusion")->ToString();
+    }
+
+    (*node_json_map)[anf_node] = node_json;
+  }
+  return true;
+}
+
+bool AkgAscendKernelBuilder::CollectFusedJson(const std::vector<AnfNodePtr> &anf_nodes,
+                                              const std::vector<AnfNodePtr> &input_list,
+                                              const std::vector<AnfNodePtr> &output_list) {
+  if (anf_nodes.empty() || input_list.empty()) {
+    MS_LOG(ERROR) << "Invalid input size, anf_nodes [" << anf_nodes.size() << "], input_list [" << input_list.size()
+                  << "].";
+    return false;
+  }
+  MS_LOG(INFO) << "anf_nodes [" << output_list.size() << "], input_list [" << anf_nodes.size() << "], output_list ["
+               << input_list.size() << "].";
+
+  std::map<AnfNodePtr, nlohmann::json> node_json_map;
+  if (!GenJsonAndPreprocess4Fused(anf_nodes, &node_json_map)) {
+    return false;
+  }
+
+  UpdateTensorNameInJson(anf_nodes, &node_json_map);
+
+  nlohmann::json fused_node_json;
+  std::vector<nlohmann::json> node_json_desc;
+  std::transform(anf_nodes.begin(), anf_nodes.end(), std::back_inserter(node_json_desc),
+                 [&node_json_map](const AnfNodePtr &anf_node) { return node_json_map[anf_node]; });
+  fused_node_json[kOpDesc] = node_json_desc;
+  fused_node_json[kInputDesc] = GetInputsJson(anf_nodes, input_list, &node_json_map);
+  fused_node_json[kOutputDesc] =
+    GetOutputsJson(anf_nodes, input_list, output_list, fused_node_json[kInputDesc], &node_json_map);
 
   size_t hash_id = std::hash<std::string>()(fused_node_json.dump());
   json_name_ = "Fused_";
@@ -243,36 +336,7 @@ void GenParallelCompileFuncArgs(const std::vector<std::string> &kernel_jsons, Py
 }
 
 bool AkgOpParallelBuild(const std::vector<std::pair<AkgAscendKernelBuilder, AnfNodePtr>> &build_args) {
-  // Remove cached nodes, gether unique nodes, and collect repeated nodes which need postprecess.
-  std::vector<std::string> jsons;
-  std::unordered_set<std::string> json_name_set;
-  std::vector<std::pair<AkgAscendKernelBuilder, AnfNodePtr>> repeat_nodes;
-  for (const auto &[builder, anf_node] : build_args) {
-    MS_EXCEPTION_IF_NULL(anf_node);
-    auto json_name = builder.json_name();
-    MS_LOG(DEBUG) << "Akg start compile op: " << json_name;
-    auto cached_kernel_pack = tbe::TbeUtils::SearchCache(json_name, AkgKernelBuild::GetProcessor(anf_node));
-    if (cached_kernel_pack != nullptr) {
-      MS_LOG(DEBUG) << "Use cached kernel, json_name_[" << json_name << "], fullname_with_scope["
-                    << anf_node->fullname_with_scope() << "].";
-      auto kernel_mod_ptr = std::make_shared<AkgKernelMod>(cached_kernel_pack);
-      kernel_mod_ptr->SetInputSizeList(builder.input_size_list());
-      kernel_mod_ptr->SetOutputSizeList(builder.output_size_list());
-      AnfAlgo::SetKernelMod(kernel_mod_ptr, anf_node.get());
-      continue;
-    }
-
-    if (json_name_set.count(json_name) != 0) {
-      repeat_nodes.push_back({builder, anf_node});
-      continue;
-    }
-    json_name_set.insert(json_name);
-    auto node_json = builder.kernel_json();
-    kernel::SaveJsonInfo(json_name, node_json);
-    jsons.push_back(node_json);
-  }
-
-  // No nodes need to be compiled!
+  auto [jsons, repeat_nodes] = PreProcessJsonForBuild(build_args);
   if (jsons.empty()) {
     return true;
   }
@@ -307,34 +371,8 @@ bool AkgOpParallelBuild(const std::vector<std::pair<AkgAscendKernelBuilder, AnfN
     return false;
   }
 
-  // All unique done here, cache them and set kernel.
-  for (const auto &[builder, anf_node] : build_args) {
-    auto json_name = builder.json_name();
-    auto new_kernel_pack = tbe::TbeUtils::InsertCache(json_name, AkgKernelBuild::GetProcessor(anf_node));
-    if (new_kernel_pack == nullptr) {
-      MS_LOG(ERROR) << "Insert to cache failed, json_name_[" << json_name << "], fullname_with_scope["
-                    << anf_node->fullname_with_scope() << "].";
-      return false;
-    }
-    auto kernel_mod_ptr = std::make_shared<AkgKernelMod>(new_kernel_pack);
-    kernel_mod_ptr->SetInputSizeList(builder.input_size_list());
-    kernel_mod_ptr->SetOutputSizeList(builder.output_size_list());
-    AnfAlgo::SetKernelMod(kernel_mod_ptr, anf_node.get());
-    MS_LOG(DEBUG) << "Akg compile " << json_name << " kernel and insert cache successfully!";
-  }
-
-  // Handle repeated nodes.
-  for (const auto &[builder, anf_node] : repeat_nodes) {
-    auto node_json = builder.kernel_json();
-    auto json_name = builder.json_name();
-    auto cached_kernel_pack = tbe::TbeUtils::SearchCache(json_name, AkgKernelBuild::GetProcessor(anf_node));
-    if (cached_kernel_pack == nullptr) return false;
-    MS_LOG(INFO) << "Use just compiled kernel, json_name_[" << json_name << "], fullname_with_scope["
-                 << anf_node->fullname_with_scope() << "].";
-    auto kernel_mod_ptr = std::make_shared<AkgKernelMod>(cached_kernel_pack);
-    kernel_mod_ptr->SetInputSizeList(builder.input_size_list());
-    kernel_mod_ptr->SetOutputSizeList(builder.output_size_list());
-    AnfAlgo::SetKernelMod(kernel_mod_ptr, anf_node.get());
+  if (!PostProcessAfterCompile(build_args, repeat_nodes)) {
+    return false;
   }
 
   return true;
@@ -380,6 +418,5 @@ bool AkgAscendKernelParallelBuild(const std::vector<AnfNodePtr> &anf_nodes) {
 
   return AkgOpParallelBuild(json_and_node);
 }
-
 }  // namespace kernel
 }  // namespace mindspore

mindspore/ccsrc/kernel/akg/ascend/akg_ascend_kernel_build.h

@@ -20,6 +20,7 @@
 #include <string>
 #include <memory>
 #include <vector>
+#include <map>
 #include "ir/anf.h"
 #include "kernel/kernel.h"
 #include "kernel/akg/akg_kernel_build.h"
@@ -40,6 +41,9 @@ class AkgAscendKernelBuilder : public AkgKernelBuild {
   const std::vector<size_t> &output_size_list() const { return output_size_list_; }
 
  private:
+  bool GenJsonAndPreprocess4Fused(const std::vector<AnfNodePtr> &anf_nodes,
+                                  std::map<AnfNodePtr, nlohmann::json> *node_json_map);
+
   std::string kernel_json_;
   std::vector<size_t> input_size_list_;
   std::vector<size_t> output_size_list_;

mindspore/ccsrc/kernel/akg/ascend/akg_ascend_kernel_mod.cc

@@ -55,7 +55,7 @@ const std::vector<size_t> &AkgKernelMod::GetWorkspaceSizeList() const { return w
 
 bool AkgKernelMod::Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &,
                           const std::vector<AddressPtr> &outputs, void *stream_ptr) {
-  if (stream_ptr == 0) {
+  if (stream_ptr == nullptr) {
     MS_LOG(ERROR) << "stream_ptr should not be nullptr.";
     return false;
   }