!15985 [GraphKernel] Clean code warning.

From: @wenfangpei
Reviewed-by: @gaoxiong1,@ckey_dou
Signed-off-by: @ckey_dou

mindspore/ccsrc/backend/optimizer/graph_kernel/graph_kernel_expander.h

@@ -44,7 +44,7 @@ class GraphKernelExpander : public Pass {
  public:
   GraphKernelExpander() : Pass("graph_kernel_expander") {}
   ~GraphKernelExpander() override = default;
-  bool Run(const FuncGraphPtr &func_graph);
+  bool Run(const FuncGraphPtr &func_graph) override;
 
  private:
   ExpanderPtr GetExpander(const AnfNodePtr &node);

mindspore/ccsrc/backend/optimizer/graph_kernel/graph_kernel_optimization.cc

@@ -45,7 +45,7 @@
 
 namespace mindspore {
 namespace opt {
-PassManagerPtr GraphKernelOptimizer::PreProcess() {
+PassManagerPtr GraphKernelOptimizer::PreProcess() const {
   auto pm = std::make_shared<PassManager>("graphkernel_stage1_preprocess");
   // Change Assign(p, a, U) to Assign(Depend(p, U), a)
   pm->AddPass(std::make_shared<SplitAssign>());
@@ -60,7 +60,7 @@ PassManagerPtr GraphKernelOptimizer::PreProcess() {
   return pm;
 }
 
-PassManagerPtr GraphKernelOptimizer::Cluster() {
+PassManagerPtr GraphKernelOptimizer::Cluster() const {
   auto pm = std::make_shared<PassManager>("graphkernel_stage2_cluster");
   // Expand complex basic kernels to composite kernels
   pm->AddPass(std::make_shared<GraphKernelExpander>());
@@ -73,7 +73,7 @@ PassManagerPtr GraphKernelOptimizer::Cluster() {
   return pm;
 }
 
-PassManagerPtr GraphKernelOptimizer::HighLevelOpt1() {
+PassManagerPtr GraphKernelOptimizer::HighLevelOpt1() const {
   auto pm = std::make_shared<PassManager>("graphkernel_stage3_highlevelopt1");
   // Reorder Cast and Type-insensitive node
   pm->AddPass(std::make_shared<ReorderOps>());
@@ -98,7 +98,7 @@ PassManagerPtr GraphKernelOptimizer::HighLevelOpt1() {
   return pm;
 }
 
-PassManagerPtr GraphKernelOptimizer::Split() {
+PassManagerPtr GraphKernelOptimizer::Split() const {
   auto pm = std::make_shared<PassManager>("graphkernel_stage4_split");
 
   // Move the non-scalar tensor (in composite node) to parameter list
@@ -126,7 +126,7 @@ PassManagerPtr GraphKernelOptimizer::Split() {
   return pm;
 }
 
-PassManagerPtr GraphKernelOptimizer::HighLevelOpt2() {
+PassManagerPtr GraphKernelOptimizer::HighLevelOpt2() const {
   auto pm = std::make_shared<PassManager>("graphkernel_stage5_highlevelopt2");
   // Enable atomic add
   pm->AddPass(std::make_shared<AtomicCleanInsertter>());
@@ -136,7 +136,7 @@ PassManagerPtr GraphKernelOptimizer::HighLevelOpt2() {
   return pm;
 }
 
-PassManagerPtr GraphKernelOptimizer::Combine() {
+PassManagerPtr GraphKernelOptimizer::Combine() const {
   auto pm = std::make_shared<PassManager>("graphkernel_stage6_combine");
   // Enable parallel fusion
   if (is_gpu && context::GraphKernelFlags::GetInstance().enable_parallel_fusion) {
@@ -146,7 +146,7 @@ PassManagerPtr GraphKernelOptimizer::Combine() {
   return pm;
 }
 
-PassManagerPtr GraphKernelOptimizer::PostProcess() {
+PassManagerPtr GraphKernelOptimizer::PostProcess() const {
   auto pm = std::make_shared<PassManager>("graphkernel_stage7_postprocess");
   // Add the new tensors to the kernel_graph
   pm->AddPass(std::make_shared<BindValueToGraph>());

mindspore/ccsrc/backend/optimizer/graph_kernel/graph_kernel_optimization.h

@@ -30,19 +30,19 @@ class GraphKernelOptimizer {
 
  private:
   // Pre-process
-  PassManagerPtr PreProcess();
+  PassManagerPtr PreProcess() const;
   // Cluster kernels
-  PassManagerPtr Cluster();
+  PassManagerPtr Cluster() const;
   // High level optimize 1
-  PassManagerPtr HighLevelOpt1();
+  PassManagerPtr HighLevelOpt1() const;
   // Split kernels
-  PassManagerPtr Split();
+  PassManagerPtr Split() const;
   // High level optimize 2
-  PassManagerPtr HighLevelOpt2();
+  PassManagerPtr HighLevelOpt2() const;
   // Combine kernels
-  PassManagerPtr Combine();
+  PassManagerPtr Combine() const;
   // Post-process
-  PassManagerPtr PostProcess();
+  PassManagerPtr PostProcess() const;
 
   bool is_gpu{false};
   bool is_ascend{false};

mindspore/ccsrc/backend/optimizer/graph_kernel/parallel_fusion.cc

@@ -17,6 +17,7 @@
 #include "backend/optimizer/graph_kernel/parallel_fusion.h"
 
 #include <algorithm>
+#include <cstddef>
 #include <list>
 #include <map>
 #include <memory>
@@ -454,10 +455,10 @@ std::vector<std::vector<AnfNodePtrList>> ParallelOpFusion::SearchParallelGroups(
 }
 
 std::tuple<AnfNodePtrList, std::vector<int>> ParallelOpFusion::GetAvaliableNodesByOffset(
-  int start, const std::vector<int> &offsets, const std::vector<bool> &used, const AnfNodePtrList &nodes,
+  int start, const std::vector<size_t> &offsets, const std::vector<bool> &used, const AnfNodePtrList &nodes,
   const std::set<int> &excludes) {
   // Get unused nodes by offset index, the result will contain the node with start index.
-  int node_limit = nodes.size();
+  int node_limit = static_cast<int>(nodes.size());
   if (start >= node_limit) {
     MS_LOG(EXCEPTION) << "Index offset is exceed the limit of given nodes.";
   }
@@ -469,7 +470,7 @@ std::tuple<AnfNodePtrList, std::vector<int>> ParallelOpFusion::GetAvaliableNodes
       unused.push_back(i);
     }
   }
-  int limit = unused.size();
+  size_t limit = unused.size();
   for (auto offset : offsets) {
     if (offset >= limit) {
       MS_LOG(EXCEPTION) << "Index offset is exceed the limit of unused nodes.";
@@ -520,7 +521,7 @@ std::tuple<std::vector<bool>, std::vector<ParallelInfo>> ParallelOpFusion::DoSea
     size_t begin = 1, end = unused_num;
     while (begin <= end) {
       size_t mid = (begin + end) / 2;
-      std::vector<int> tc(mid);
+      std::vector<size_t> tc(mid);
       std::iota(tc.begin(), tc.end(), 1);
       AnfNodePtrList other_candidates;
       std::tie(other_candidates, std::ignore) =
@@ -535,7 +536,7 @@ std::tuple<std::vector<bool>, std::vector<ParallelInfo>> ParallelOpFusion::DoSea
     }
 
     if (begin > 1) {
-      std::vector<int> tc(begin - 1);
+      std::vector<size_t> tc(begin - 1);
       std::iota(tc.begin(), tc.end(), 1);
       AnfNodePtrList other_candidates;
       std::tie(other_candidates, std::ignore) =
@@ -560,7 +561,7 @@ std::tuple<std::vector<bool>, std::vector<ParallelInfo>> ParallelOpFusion::DoSea
 
   // Current nodes is not suitable to fuse, so pop first node to try other fusion possibility.
   if (parallel_infos.size() == 0) {
-    origin_candidates_used[get_index(origin_indices, candidates[0])] = true;
+    origin_candidates_used[get_index(origin_indices, candidates[parallel_infos.size()])] = true;
   }
 
   return std::make_tuple(origin_candidates_used, parallel_infos);

mindspore/ccsrc/backend/optimizer/graph_kernel/parallel_fusion.h

@@ -68,7 +68,7 @@ class ParallelConfig {
   explicit ParallelConfig(size_t max_n) : max_num_for_fuse_(max_n) {}
   explicit ParallelConfig(const ParallelConfig &obj) { max_num_for_fuse_ = obj.max_num_for_fuse_; }
   ~ParallelConfig() = default;
-  size_t max_num_for_fuse() { return max_num_for_fuse_; }
+  size_t max_num_for_fuse() const { return max_num_for_fuse_; }
 
  private:
   size_t max_num_for_fuse_{10};  // Too many nodes to fuse together may produce bad result.
@@ -90,7 +90,7 @@ class ParallelOpFusion : public Pass {
   bool Run(const FuncGraphPtr &graph) override;
 
  private:
-  std::tuple<AnfNodePtrList, std::vector<int>> GetAvaliableNodesByOffset(int start, const std::vector<int> &offsets,
+  std::tuple<AnfNodePtrList, std::vector<int>> GetAvaliableNodesByOffset(int start, const std::vector<size_t> &offsets,
                                                                          const std::vector<bool> &used,
                                                                          const AnfNodePtrList &nodes,
                                                                          const std::set<int> &excludes);

mindspore/ccsrc/backend/optimizer/graph_kernel/raise_reduction_precision.cc

@@ -32,11 +32,12 @@
 
 namespace mindspore {
 namespace opt {
-bool RaiseReductionPrecision::IsFp16ReduceSum(const AnfNodePtr &node) {
+bool RaiseReductionPrecision::IsFp16ReduceSum(const AnfNodePtr &node) const {
   return IsPrimitiveCNode(node, prim::kPrimReduceSum) && AnfAlgo::GetInputDeviceDataType(node, 0) == kNumberTypeFloat16;
 }
 
-AnfNodePtr RaiseReductionPrecision::CreateCast(const AnfNodePtr &input, const TypePtr &dst_type, std::string format) {
+AnfNodePtr RaiseReductionPrecision::CreateCast(const AnfNodePtr &input, const TypePtr &dst_type,
+                                               const std::string &format) const {
   auto func_graph = input->func_graph();
   MS_EXCEPTION_IF_NULL(func_graph);
   AnfNodePtrList inputs = {NewValueNode(prim::kPrimCast), input};
@@ -45,7 +46,7 @@ AnfNodePtr RaiseReductionPrecision::CreateCast(const AnfNodePtr &input, const Ty
   return cnode;
 }
 
-AnfNodePtr RaiseReductionPrecision::CreateReduceSum(const AnfNodePtr &node, const AnfNodePtr &input) {
+AnfNodePtr RaiseReductionPrecision::CreateReduceSum(const AnfNodePtr &node, const AnfNodePtr &input) const {
   auto cnode = node->cast<CNodePtr>();
   MS_EXCEPTION_IF_NULL(cnode);
   cnode->set_input(1, input);
@@ -62,17 +63,19 @@ AnfNodePtr RaiseReductionPrecision::CreateReduceSum(const AnfNodePtr &node, cons
   return node;
 }
 
-void RaiseReductionPrecision::ReplaceNode(const AnfNodePtr &reduce_node, const AnfNodePtr &cast_node) {
+void RaiseReductionPrecision::ReplaceNode(const AnfNodePtr &reduce_node, const AnfNodePtr &cast_node) const {
   auto mng = reduce_node->func_graph()->manager();
   MS_EXCEPTION_IF_NULL(mng);
   // use a copy of user, since the following `mng->Replace` will change the original users of reduce_node.
   auto users = mng->node_users()[reduce_node];
   for (const auto &user : users) {
     auto user_node = user.first;
-    auto user_index = user.second;
+    size_t user_index = static_cast<size_t>(user.second);
     if (IsPrimitiveCNode(user_node, prim::kPrimCast) &&
         AnfAlgo::GetOutputDeviceDataType(user_node, 0) == kNumberTypeFloat32) {
-      mng->Replace(user_node, reduce_node);
+      if (!(mng->Replace(user_node, reduce_node))) {
+        MS_LOG(ERROR) << "Something happened error, when replacing nodes.";
+      }
     } else {
       if (user_node->isa<CNode>()) {
         user_node->cast<CNodePtr>()->set_input(user_index, cast_node);

mindspore/ccsrc/backend/optimizer/graph_kernel/raise_reduction_precision.h

@@ -25,14 +25,14 @@ class RaiseReductionPrecision : public Pass {
  public:
   RaiseReductionPrecision() : Pass("raise_reduction_precision") {}
   ~RaiseReductionPrecision() override = default;
-  bool Run(const FuncGraphPtr &func_graph);
+  bool Run(const FuncGraphPtr &func_graph) override;
 
  private:
-  bool IsFp16ReduceSum(const AnfNodePtr &node);
+  bool IsFp16ReduceSum(const AnfNodePtr &node) const;
   bool Process(const FuncGraphPtr &func_graph);
-  AnfNodePtr CreateCast(const AnfNodePtr &input, const TypePtr &dst_type, std::string format);
-  AnfNodePtr CreateReduceSum(const AnfNodePtr &node, const AnfNodePtr &input);
-  void ReplaceNode(const AnfNodePtr &src_node, const AnfNodePtr &dst_node);
+  AnfNodePtr CreateCast(const AnfNodePtr &input, const TypePtr &dst_type, const std::string &format) const;
+  AnfNodePtr CreateReduceSum(const AnfNodePtr &node, const AnfNodePtr &input) const;
+  void ReplaceNode(const AnfNodePtr &src_node, const AnfNodePtr &dst_node) const;
 };
 }  // namespace opt
 }  // namespace mindspore