[NPU] refine npu subgraph and clean code (#1902)

* add npu script and tester

* fix npu armv7 so and refine tests

test=develop

* update fix and refine log

test=develop

* refine npu generate api

* refine npu subgraph

* refine npu gen and clean code

* fix model laod

* refine node2rm in subgraph

* refine the build npu functions

test=develop

lite/api/cxx_api.cc

@@ -135,12 +135,6 @@ void Predictor::GenRuntimeProgram() {
   program_generated_ = true;
 }
 
-void Predictor::GenNPURuntimeProgram() {
-  program_ = optimizer_.GenNPURuntimeProgram();
-  CHECK_EQ(exec_scope_, program_->exec_scope());
-  program_generated_ = true;
-}
-
 const lite::Tensor *Predictor::GetTensor(const std::string &name) const {
   auto *var = exec_scope_->FindVar(name);
   return &var->Get<lite::Tensor>();

lite/api/cxx_api.h

@@ -55,8 +55,6 @@ class LITE_API Predictor {
 
   void GenRuntimeProgram();
 
-  void GenNPURuntimeProgram();
-
   // Run the predictor for a single batch of data.
   void Run() {
     if (!program_generated_) {

lite/api/mobilenetv1_int8_test.cc

@@ -26,8 +26,7 @@ namespace paddle {
 namespace lite {
 
 void TestModel(const std::vector<Place>& valid_places,
-               const Place& preferred_place,
-               bool use_npu = false) {
+               const Place& preferred_place) {
   DeviceInfo::Init();
   DeviceInfo::Global().SetRunMode(lite_api::LITE_POWER_HIGH, FLAGS_threads);
   lite::Predictor predictor;
@@ -42,10 +41,6 @@ void TestModel(const std::vector<Place>& valid_places,
     data[i] = 1;
   }
 
-  if (use_npu) {
-    predictor.GenNPURuntimeProgram();
-  }
-
   for (int i = 0; i < FLAGS_warmup; ++i) {
     predictor.Run();
   }

lite/api/mobilenetv1_test.cc

@@ -30,7 +30,6 @@ namespace lite {
 void TestModel(const std::vector<Place>& valid_places,
                const Place& preferred_place,
                const std::string& model_dir = FLAGS_model_dir,
-               bool gen_npu = false,
                bool save_model = false) {
   DeviceInfo::Init();
   DeviceInfo::Global().SetRunMode(lite_api::LITE_POWER_HIGH, FLAGS_threads);
@@ -46,10 +45,6 @@ void TestModel(const std::vector<Place>& valid_places,
     data[i] = 1;
   }
 
-  if (gen_npu) {
-    predictor.GenNPURuntimeProgram();
-  }
-
   for (int i = 0; i < FLAGS_warmup; ++i) {
     predictor.Run();
   }
@@ -116,13 +111,11 @@ TEST(MobileNetV1, test_npu) {
   TestModel(valid_places,
             Place({TARGET(kARM), PRECISION(kFloat)}),
             FLAGS_model_dir,
-            true /* gen_npu */,
             true /* save_model*/);
 
   TestModel(valid_places,
             Place({TARGET(kARM), PRECISION(kFloat)}),
             FLAGS_optimized_model,
-            false /* gen_npu */,
             false /* save model */);
 }
 #endif  // LITE_WITH_NPU

lite/api/mobilenetv2_test.cc

@@ -31,7 +31,6 @@ namespace lite {
 void TestModel(const std::vector<Place>& valid_places,
                const Place& preferred_place,
                const std::string& model_dir = FLAGS_model_dir,
-               bool gen_npu = false,
                bool save_model = false) {
   DeviceInfo::Init();
   DeviceInfo::Global().SetRunMode(lite_api::LITE_POWER_HIGH, FLAGS_threads);
@@ -47,10 +46,6 @@ void TestModel(const std::vector<Place>& valid_places,
     data[i] = 1;
   }
 
-  if (gen_npu) {
-    predictor.GenNPURuntimeProgram();
-  }
-
   for (int i = 0; i < FLAGS_warmup; ++i) {
     predictor.Run();
   }
@@ -116,13 +111,11 @@ TEST(MobileNetV2, test_npu) {
   TestModel(valid_places,
             Place({TARGET(kARM), PRECISION(kFloat)}),
             FLAGS_model_dir,
-            true /* gen_npu */,
             true /* save_model*/);
 
   TestModel(valid_places,
             Place({TARGET(kARM), PRECISION(kFloat)}),
             FLAGS_optimized_model,
-            false /* gen_npu */,
             false /* save model */);
 }
 #endif  // LITE_WITH_NPU

lite/core/device_info.cc

@@ -958,7 +958,7 @@ void DeviceInfo::RequestPowerRandLowMode(int shift_num, int thread_num) {
 
 int DeviceInfo::Setup() {
   core_num_ = get_cpu_num();
-  printf("core number: %d\n", core_num_);
+  LOG(INFO) << " CPU core number: " << core_num_;
   mem_size_ = get_mem_size();
   get_cpu_arch(&archs_, core_num_);
   // set defalut CPU info

lite/core/mir/subgraph/generate_npu_program_pass.cc

@@ -37,127 +37,92 @@ namespace lite {
 namespace mir {
 namespace subgraph {
 
-void GenerateNPUProgramPass::SubgraphSortHelper(
-    Node* node,
-    const std::unordered_set<Node*>& nodes_all,
-    std::unordered_set<const Node*>* visited_nodes,
-    std::vector<Node*>* ret) {
-  for (auto& var_node : node->inlinks) {
-    if (var_node->inlinks.empty()) continue;
-    auto* op_node = var_node->inlinks.front();
-    if (nodes_all.count(op_node) && !visited_nodes->count(op_node)) {
-      SubgraphSortHelper(op_node, nodes_all, visited_nodes, ret);
-    }
+std::shared_ptr<ge::Operator> GenerateNPUProgramPass::CvtVarNode(
+    lite::mir::Node* var_node, const Scope* scope) {
+  CHECK(var_node->IsArg());
+  const auto& arg = var_node->AsArg();
+  VLOG(4) << "Convert var node " << arg.name;
+
+  auto* var = scope->FindVar(arg.name);
+  CHECK(var);
+  auto* tensor = var->GetMutable<lite::Tensor>();
+  CHECK(tensor);
+  auto dims = tensor->dims();
+  if (arg.is_weight) {
+    auto wgt = std::make_shared<ge::op::Const>(arg.name);
+    LOG(INFO) << "in convert const:" << arg.name;
+    VLOG(4) << dims;
+    wgt->set_attr_value(lite::npu::bridge::CvtFromLiteTensor(tensor));
+    return wgt;
+  } else {
+    CHECK_EQ(dims.size(), 4);
+    LOG(INFO) << "in convert data:" << arg.name;
+    LOG(INFO) << dims;
+    // TODO(xxx): support more types and dims size
+    ge::TensorDesc desc(ge::Shape(dims.Vectorize()),
+                        ge::Format::FORMAT_NCHW,
+                        ge::DataType::DT_FLOAT);
+
+    //   auto size = desc.GetShape().GetShapeSize();
+    //  ge::TensorUtils::SetSize(desc, size*sizeof(float));
+    //  ge::TensorUtils::SetRealDimCnt(desc, 4);
+    auto data = std::make_shared<ge::op::Data>(arg.name);
+    data->update_input_desc_x(desc);
+    return data;
   }
-  ret->push_back(node);
-  visited_nodes->insert(node);
+  return nullptr;
 }
 
-void GenerateNPUProgramPass::CvtOpNodes(
+void GenerateNPUProgramPass::CvtAllOpNodes(
     const std::vector<Node*>& nodes2cvt,
-    lite::npu::bridge::node_map_type* cvted_vars) {
+    lite::npu::bridge::node_map_type* converted_vars) {
   const auto& bridges = lite::npu::bridge::Factory::Instance();
   const auto& cvtfunc_map = bridges.AllFunctions();
-  // record all converted vars
-  // op node's inputs must be found in cvted_vars
+  // return record all converted vars
+  // op node's inputs must be found in converted_vars
   for (auto& node : nodes2cvt) {
     lite::npu::bridge::node_map_type node_inputs;
     auto& stmt = node->AsStmt();
     for (auto& var_node : node->inlinks) {
       auto& arg = var_node->AsArg();
-      if (arg.is_weight) continue;
-      auto var_name = arg.name;
-      if (!cvted_vars->count(var_name)) {
-        cvted_vars->insert(std::make_pair(
-            var_name,
-            lite::npu::bridge::CvtNode(var_node, stmt.op()->scope())));
-      }
-      node_inputs.insert(*cvted_vars->find(var_name));
-    }
-    auto node_outputs = cvtfunc_map.at(stmt.op_type())(stmt.op(), node_inputs);
-    cvted_vars->insert(node_outputs.begin(), node_outputs.end());
-  }
-}
-
-void GenerateNPUProgramPass::GetIOVars(
-    const std::vector<Node*>& nodes2cvt,
-    const lite::npu::bridge::node_map_type& cvted_vars,
-    std::unordered_set<const Node*>* nodes2rm,
-    std::vector<Node*>* in_vars,
-    std::vector<Node*>* out_vars,
-    lite::npu::bridge::node_map_type* in_cvted_vars,
-    lite::npu::bridge::node_map_type* out_cvted_vars) {
-  std::unordered_set<Node*> op_nodes_all(nodes2cvt.begin(), nodes2cvt.end());
-  for (auto& op_node : nodes2cvt) {
-    for (auto& in_var : op_node->inlinks) {
-      if (in_var->AsArg().is_weight) continue;
-      auto* pre_op_node = in_var->inlinks.front();
-      if (op_nodes_all.count(pre_op_node)) {
-        nodes2rm->insert(in_var);
+      // weight should be handled in the converter, so skip here
+      if (arg.is_weight) {
         continue;
       }
-      in_vars->push_back(in_var);
-      auto arg_name = in_var->AsArg().name;
-      in_cvted_vars->insert(std::make_pair(arg_name, cvted_vars.at(arg_name)));
-    }
-    for (auto& out_var : op_node->outlinks) {
-      if (out_var->outlinks.empty()) {
-        nodes2rm->insert(out_var);
-        continue;
-      }
-      auto* next_op_node = out_var->outlinks.front();
-
-      if (op_nodes_all.count(next_op_node)) {
-        nodes2rm->insert(out_var);
-        continue;
+      auto var_name = arg.name;
+      if (!converted_vars->count(var_name)) {
+        converted_vars->insert(
+            std::make_pair(var_name, CvtVarNode(var_node, stmt.op()->scope())));
       }
-      out_vars->push_back(out_var);
-      auto arg_name = out_var->AsArg().name;
-      out_cvted_vars->insert(std::make_pair(arg_name, cvted_vars.at(arg_name)));
+      node_inputs.insert(*converted_vars->find(var_name));
     }
+    auto node_outputs = cvtfunc_map.at(stmt.op_type())(stmt.op(), node_inputs);
+    converted_vars->insert(node_outputs.begin(), node_outputs.end());
   }
-  nodes2rm->insert(nodes2cvt.begin(), nodes2cvt.end());
 }
 
-void GenerateNPUProgramPass::GenNPUGraphOpNode(
-    const std::unique_ptr<SSAGraph>& graph,
-    int sub_id,
-    const std::unordered_set<Node*>& nodes_all) {
-  std::unordered_set<const Node*> visited_nodes;
-  std::vector<Node*> ret;
-  for (auto& node : nodes_all) {
-    if (!node->IsStmt()) continue;
-    if (visited_nodes.count(node)) continue;
-    SubgraphSortHelper(node, nodes_all, &visited_nodes, &ret);
-  }
+std::string GenerateNPUProgramPass::BuildNPUGraph(
+    const std::unordered_set<Node*>& op_nodes,
+    const std::unordered_set<Node*>& in_data_vars,
+    const std::unordered_set<Node*>& out_data_vars,
+    int sub_id) {
+  auto ordered_nodes = GetTopologicalOrder(op_nodes);
+  lite::npu::bridge::node_map_type converted_vars;
+  CvtAllOpNodes(ordered_nodes, &converted_vars);
 
-  lite::npu::bridge::node_map_type cvted_vars;
-  CvtOpNodes(ret, &cvted_vars);
-
-  std::unordered_set<const Node*> nodes2rm;
-  std::vector<Node*> in_vars;
-  std::vector<Node*> out_vars;
-  lite::npu::bridge::node_map_type in_cvted_vars;
-  lite::npu::bridge::node_map_type out_cvted_vars;
-  GetIOVars(ret,
-            cvted_vars,
-            &nodes2rm,
-            &in_vars,
-            &out_vars,
-            &in_cvted_vars,
-            &out_cvted_vars);
-
-  std::vector<std::string> in_vars_name;
-  std::vector<std::string> out_vars_name;
+  std::vector<std::string> in_var_names;
+  std::vector<std::string> out_var_names;
   std::vector<ge::Operator> inputs;
   std::vector<ge::Operator> outputs;
-  for (auto i : in_cvted_vars) {
-    in_vars_name.push_back(i.first);
-    inputs.push_back(*i.second);
+  for (auto i : in_data_vars) {
+    auto argname = i->AsArg().name;
+    in_var_names.push_back(argname);
+    inputs.push_back(*converted_vars.at(argname));
   }
-  for (auto i : out_cvted_vars) {
-    out_vars_name.push_back(i.first);
-    outputs.push_back(*i.second);
+  for (auto i : out_data_vars) {
+    auto argname = i->AsArg().name;
+    out_var_names.push_back(argname);
+    outputs.push_back(*converted_vars.at(argname));
   }
 
   std::string model_name("hiai_npu_client_" + std::to_string(sub_id) + ".om");
@@ -165,27 +130,55 @@ void GenerateNPUProgramPass::GenNPUGraphOpNode(
     LOG(FATAL) << "Build NPU failed subgraph " << sub_id;
   }
   LOG(INFO) << "[NPU] Build NPU Client success subgraph " << sub_id;
+  return model_name;
+}
 
+cpp::OpDesc GenerateNPUProgramPass::GenGraphOpDesc(
+    const std::string& model_name,
+    const std::vector<std::string>& in_var_names,
+    const std::vector<std::string>& out_var_names) {
   cpp::OpDesc op_desc;
   op_desc.SetType("graph_op");
+  op_desc.SetInput("Inputs", in_var_names);
+  op_desc.SetOutput("Outputs", out_var_names);
+  op_desc.SetAttr("model_name", model_name);
+  return op_desc;
+}
+
+void GenerateNPUProgramPass::InsertNewNode(
+    const std::unique_ptr<SSAGraph>& graph,
+    const std::string& model_name,
+    Scope* scope,
+    const std::vector<Place>& valid_places,
+    std::unordered_set<Node*> in_data_vars,
+    std::unordered_set<Node*> in_wgt_vars,
+    std::unordered_set<Node*> out_data_vars,
+    std::unordered_set<Node*> out_unused_vars) {
   std::vector<std::string> in_var_names;
+  std::vector<std::string> out_var_names;
+  for (auto i : in_data_vars) {
+    in_var_names.push_back(i->AsArg().name);
+  }
+  for (auto i : out_data_vars) {
+    out_var_names.push_back(i->AsArg().name);
+  }
 
-  op_desc.SetInput("Inputs", in_vars_name);
-  op_desc.SetOutput("Outputs", out_vars_name);
-  op_desc.SetAttr("model_name", model_name);
-  auto graph_op = LiteOpRegistry::Global().Create("graph_op");
+  auto op_desc = GenGraphOpDesc(model_name, in_var_names, out_var_names);
 
-  auto any_op = ret.front()->AsStmt().op();
-  auto* scope = any_op->scope();
+  auto graph_op = LiteOpRegistry::Global().Create("graph_op");
   graph_op->Attach(op_desc, scope);
-
-  auto valid_places = any_op->valid_places();
   auto* new_op_node = graph->GraphCreateInstructNode(graph_op, valid_places);
 
-  for (auto& in_var : in_vars) {
+  for (auto& in_var : in_data_vars) {
+    IR_NODE_LINK_TO(in_var, new_op_node);
+  }
+  for (auto& in_var : in_wgt_vars) {
     IR_NODE_LINK_TO(in_var, new_op_node);
   }
-  for (auto& out_var : out_vars) {
+  for (auto& out_var : out_data_vars) {
+    IR_OP_VAR_LINK(new_op_node, out_var);
+  }
+  for (auto& out_var : out_unused_vars) {
     IR_OP_VAR_LINK(new_op_node, out_var);
   }
 
@@ -193,6 +186,34 @@ void GenerateNPUProgramPass::GenNPUGraphOpNode(
   auto& inst = new_op_node->AsStmt();
   inst.picked_kernel().SetContext(
       ContextScheduler::Global().NewContext(inst.picked_kernel().target()));
+}
+
+void GenerateNPUProgramPass::GenNPUGraphOpNode(
+    const std::unique_ptr<SSAGraph>& graph,
+    const std::unordered_set<Node*>& op_nodes,
+    int sub_id) {
+  std::unordered_set<Node*> in_data_vars;
+  std::unordered_set<Node*> in_wgt_vars;
+  std::unordered_set<Node*> out_data_vars;
+  std::unordered_set<Node*> out_unused_vars;
+  FindInputOutputVars(
+      op_nodes, &in_data_vars, &in_wgt_vars, &out_data_vars, &out_unused_vars);
+
+  auto nodes2rm = GetNode2rm(
+      op_nodes, {in_data_vars, in_wgt_vars, out_data_vars, out_unused_vars});
+
+  auto model_name =
+      BuildNPUGraph(op_nodes, in_data_vars, out_data_vars, sub_id);
+
+  auto any_op = (*op_nodes.begin())->AsStmt().op();
+  InsertNewNode(graph,
+                model_name,
+                any_op->scope(),
+                any_op->valid_places(),
+                in_data_vars,
+                in_wgt_vars,
+                out_data_vars,
+                out_unused_vars);
 
   GraphSafeRemoveNodes(graph.get(), nodes2rm);
 }
@@ -215,7 +236,7 @@ void GenerateNPUProgramPass::ConvertSubgraph(
 
   for (int id = 1; id <= sub_num; ++id) {
     LOG(INFO) << "Converting subgraph_id:" << id;
-    GenNPUGraphOpNode(graph, id, nodes_all.at(id));
+    GenNPUGraphOpNode(graph, nodes_all.at(id), id);
   }
 }
 
@@ -226,14 +247,21 @@ void GenerateNPUProgramPass::Apply(const std::unique_ptr<SSAGraph>& graph) {
   const auto& op_map = bridges.AllFunctions();
   std::vector<std::string> supported_op_types;
   for (auto& i : op_map) {
-    LOG(INFO) << i.first;
+    LOG(INFO) << "Supported type: " << i.first;
     supported_op_types.push_back(i.first);
   }
+
+  try {
     int num_subgraph = FuseSubgraph(graph, supported_op_types);
     LOG(INFO) << "detected " << num_subgraph << " NPU subgraph";
 
     InferOnce(graph);
     ConvertSubgraph(graph, num_subgraph);
+  } catch (...) {
+    // exception = true;
+    LOG(WARNING) << "Build NPU graph failed";
+  }
+
   LOG(INFO) << "After NPU Pass \n" << Visualize(graph.get());
 
   for (auto& item : graph->StmtTopologicalOrder()) {

lite/core/mir/subgraph/generate_npu_program_pass.h

@@ -38,31 +38,35 @@ class GenerateNPUProgramPass : public SubgraphProgramPass {
   std::unique_ptr<RuntimeProgram> GenProgram();
 
  protected:
-  // sort nodes to operational sequence
-  void SubgraphSortHelper(Node* node,
-                          const std::unordered_set<Node*>& nodes_all,
-                          std::unordered_set<const Node*>* visited_nodes,
-                          std::vector<Node*>* ret);
-
   // nodes2cvt: op nodes to convert
-  // cvted_vars: converted var nodes
-  // nodes2rm: op nodes and var nodes that need to be removed
-  void CvtOpNodes(const std::vector<Node*>& nodes2cvt,
+  // return cvted_vars: converted var nodes
+  void CvtAllOpNodes(const std::vector<Node*>& nodes2cvt,
                      lite::npu::bridge::node_map_type* cvted_vars);
 
-  // achieve input and output vars/cvted_vars;
-  // achieve all nodes to remove
-  void GetIOVars(const std::vector<Node*>& nodes2cvt,
-                 const lite::npu::bridge::node_map_type& cvted_vars,
-                 std::unordered_set<const Node*>* nodes2rm,
-                 std::vector<Node*>* in_vars,
-                 std::vector<Node*>* out_vars,
-                 lite::npu::bridge::node_map_type* in_cvted_vars,
-                 lite::npu::bridge::node_map_type* out_cvted_vars);
+  std::shared_ptr<ge::Operator> CvtVarNode(lite::mir::Node* var_node,
+                                           const Scope* scope);
+
+  std::string BuildNPUGraph(const std::unordered_set<Node*>& op_nodes,
+                            const std::unordered_set<Node*>& in_data_vars,
+                            const std::unordered_set<Node*>& out_data_vars,
+                            int sub_id);
+
+  cpp::OpDesc GenGraphOpDesc(const std::string& model_name,
+                             const std::vector<std::string>& in_var_names,
+                             const std::vector<std::string>& out_var_names);
+
+  void InsertNewNode(const std::unique_ptr<SSAGraph>& graph,
+                     const std::string& model_name,
+                     Scope* scope,
+                     const std::vector<Place>& valid_places,
+                     std::unordered_set<Node*> in_data_vars,
+                     std::unordered_set<Node*> in_wgt_vars,
+                     std::unordered_set<Node*> out_data_vars,
+                     std::unordered_set<Node*> out_unused_vars);
 
   void GenNPUGraphOpNode(const std::unique_ptr<SSAGraph>& graph,
-                         int sub_id,
-                         const std::unordered_set<Node*>& nodes_all);
+                         const std::unordered_set<Node*>& nodes_all,
+                         int sub_id);
 
   void ConvertSubgraph(const std::unique_ptr<SSAGraph>& graph, int sub_num);
 

lite/core/mir/subgraph/generate_npu_program_pass_test.cc

@@ -39,8 +39,11 @@ namespace lite {
 void TestModel(lite::Predictor* predictor,
                const std::vector<Place>& valid_places,
                const std::string& model_dir) {
-  predictor->Build(
-      model_dir, "", "", Place{TARGET(kARM), PRECISION(kFloat)}, valid_places);
+  predictor->Build(model_dir,
+                   model_dir + "/model",
+                   model_dir + "/params",
+                   Place{TARGET(kARM), PRECISION(kFloat)},
+                   valid_places);
 
   auto* input_tensor = predictor->GetInput(0);
   input_tensor->Resize(DDim(std::vector<DDim::value_type>(
@@ -51,13 +54,6 @@ void TestModel(lite::Predictor* predictor,
     data[i] = 1;
   }
 
-  if (std::find(valid_places.begin(),
-                valid_places.end(),
-                Place{TARGET(kNPU), PRECISION(kFloat)}) != valid_places.end()) {
-    // TODO(TJ): change if valid npu so try use it, add rollback and move to api
-    predictor->GenNPURuntimeProgram();
-  }
-
   predictor->Run();
   if (model_dir != FLAGS_optimized_model &&
       std::find(valid_places.begin(),

lite/core/mir/subgraph/subgraph_program_pass.cc

@@ -26,6 +26,105 @@ namespace lite {
 namespace mir {
 namespace subgraph {
 
+void SubgraphProgramPass::SortHelper(
+    Node* node,
+    const std::unordered_set<Node*>& nodes_all,
+    std::unordered_set<const Node*>* visited_nodes,
+    std::vector<Node*>* ret) {
+  for (auto& var_node : node->inlinks) {
+    if (var_node->inlinks.empty()) continue;
+    auto* op_node = var_node->inlinks.front();
+    if (nodes_all.count(op_node) && !visited_nodes->count(op_node)) {
+      SortHelper(op_node, nodes_all, visited_nodes, ret);
+    }
+  }
+  ret->push_back(node);
+  visited_nodes->insert(node);
+}
+
+std::vector<Node*> SubgraphProgramPass::GetTopologicalOrder(
+    const std::unordered_set<Node*>& nodes) {
+  std::unordered_set<const Node*> visited;
+  std::vector<Node*> ret;
+  for (auto& node : nodes) {
+    if (!node->IsStmt()) continue;
+    if (visited.count(node)) continue;
+    SortHelper(node, nodes, &visited, &ret);
+  }
+  return ret;
+}
+
+void SubgraphProgramPass::FindInputOutputVars(
+    const std::unordered_set<Node*>& op_nodes,
+    std::unordered_set<Node*>* in_data_vars,
+    std::unordered_set<Node*>* in_wgt_vars,
+    std::unordered_set<Node*>* out_data_vars,
+    std::unordered_set<Node*>* out_unused_vars) {
+  for (auto& op_node : op_nodes) {
+    for (auto& in_var : op_node->inlinks) {
+      if (in_var->AsArg().is_weight) {
+        in_wgt_vars->insert(in_var);
+        continue;
+      }
+      if (!in_var->inlinks.empty()) {
+        // var can only come from one op node, so use front
+        auto* pre_op_node = in_var->inlinks.front();
+        if (op_nodes.count(pre_op_node)) {
+          continue;
+        }
+      }
+      in_data_vars->insert(in_var);
+    }
+    for (auto& out_var : op_node->outlinks) {
+      if (out_var->outlinks.empty()) {
+        // the next op is empty so this var is actually unused
+        out_unused_vars->insert(out_var);
+        continue;
+      }
+      // var can have more than one next op node
+      // so, if any one in the op_nodes then continue
+      bool next_op_in_nodes = false;
+      for (auto& next_op_node : out_var->outlinks) {
+        if (op_nodes.count(next_op_node)) {
+          next_op_in_nodes = true;
+        }
+      }
+      if (next_op_in_nodes) {
+        continue;
+      }
+
+      out_data_vars->insert(out_var);
+    }
+  }
+}
+
+std::unordered_set<const Node*> SubgraphProgramPass::GetNode2rm(
+    const std::unordered_set<Node*>& op_nodes,
+    const std::vector<std::unordered_set<Node*>>& excluded_nodes) {
+  std::unordered_set<const Node*> nodes2rm(op_nodes.begin(), op_nodes.end());
+  for (auto& op_node : op_nodes) {
+    for (auto& in_var : op_node->inlinks) {
+      if (!nodes2rm.count(in_var)) {
+        nodes2rm.insert(in_var);
+      }
+    }
+    for (auto& out_var : op_node->outlinks) {
+      if (!nodes2rm.count(out_var)) {
+        nodes2rm.insert(out_var);
+      }
+    }
+  }
+  // some nodes should not be removed
+  for (auto& e : excluded_nodes) {
+    for (auto& i : e) {
+      if (nodes2rm.count(i)) {
+        nodes2rm.erase(i);
+      }
+    }
+  }
+  return nodes2rm;
+}
+
 void SubgraphProgramPass::InferOnce(const std::unique_ptr<SSAGraph>& graph) {
   for (auto& item : graph->StmtTopologicalOrder()) {
     if (!item->IsStmt()) continue;
@@ -127,13 +226,10 @@ int SubgraphProgramPass::FuseSubgraphID(
         for (auto& j : i->outlinks) {
           if (j->IsStmt()) {
             auto& jstmt = j->AsStmt();
-            // LOG(INFO) << "initial: "<<jstmt.op_type()<<"
-            // ："<<jstmt.subgraph_id();
             if (jstmt.subgraph_id() == 0) inputvar = 1;
           }
         }
       }
-      // LOG(INFO) << "initial: "<<stmt.op_type()<<" ："<<stmt.subgraph_id();
       if (inputvar == 1) {
         for (auto& i : item->outlinks) i_nodes_[sub_id].insert(i);
       }

lite/core/mir/subgraph/subgraph_program_pass.h

@@ -54,7 +54,32 @@ class SubgraphProgramPass : public ProgramPass {
   // std::unique_ptr<SSAGraph>& graph, int sub_num);
   void ChangeAllOutConnectedID(Node* node, int to_id, int from_id = 0);
 
+  // Below function cloud be useful in child classes //
+
+  // Sort and return the topology order of nodes set
+  std::vector<Node*> GetTopologicalOrder(
+      const std::unordered_set<Node*>& nodes);
+
+  // find all input data vars, input weight vars,
+  // output data vars and output vars from the nodes
+  void FindInputOutputVars(const std::unordered_set<Node*>& op_nodes,
+                           std::unordered_set<Node*>* in_data_vars,
+                           std::unordered_set<Node*>* in_wgt_vars,
+                           std::unordered_set<Node*>* out_data_vars,
+                           std::unordered_set<Node*>* out_unused_vars);
+
+  // return the node to remove in the subgraph
+  std::unordered_set<const Node*> GetNode2rm(
+      const std::unordered_set<Node*>& op_nodes,
+      const std::vector<std::unordered_set<Node*>>& excluded_nodes);
+
  private:
+  // sort nodes to operational sequence
+  void SortHelper(Node* node,
+                  const std::unordered_set<Node*>& nodes_all,
+                  std::unordered_set<const Node*>* visited_nodes,
+                  std::vector<Node*>* ret);
+
   // {1: {nodes2rm_in_subgraph1, ...},
   //  2: {nodes2rm_in_subgraph2, ...}}
   // delete nodes

lite/core/optimizer.h

@@ -109,6 +109,28 @@ class Optimizer {
 
   // Generate a new program based on the mir graph.
   std::unique_ptr<RuntimeProgram> GenRuntimeProgram() {
+#ifdef LITE_WITH_NPU
+    if (std::find(valid_places_.begin(),
+                  valid_places_.end(),
+                  Place{TARGET(kNPU), PRECISION(kFloat)}) !=
+        valid_places_.end()) {
+      CheckInputDimsNotEmpty(exec_scope_);
+      auto pass = mir::PassManager::Global()
+                      .LookUp<mir::subgraph::GenerateNPUProgramPass>(
+                          "generate_npu_program_pass");
+      pass->Apply(graph_);
+
+      auto program = pass->GenProgram();
+      if (program) {
+        CHECK(exec_scope_);
+        program->set_exec_scope(exec_scope_);
+        return program;
+      } else {
+        LOG(WARNING) << "Build NPU graph failed.";
+      }
+    }
+
+#endif
     auto pass = mir::PassManager::Global().LookUp<mir::GenerateProgramPass>(
         "generate_program_pass");
     pass->Apply(graph_);
@@ -131,24 +153,6 @@ class Optimizer {
     }
   }
 
-  std::unique_ptr<RuntimeProgram> GenNPURuntimeProgram() {
-#ifdef LITE_WITH_NPU
-    CheckInputDimsNotEmpty(exec_scope_);
-    auto pass = mir::PassManager::Global()
-                    .LookUp<mir::subgraph::GenerateNPUProgramPass>(
-                        "generate_npu_program_pass");
-    pass->Apply(graph_);
-
-    auto program = pass->GenProgram();
-    CHECK(exec_scope_);
-    program->set_exec_scope(exec_scope_);
-    return program;
-#else
-    LOG(WARNING) << "Not compiled with NPU but use it!";
-    return GenRuntimeProgram();
-#endif
-  }
-
   void InitTargetTypeTransformPass() {
     auto* pass =
         mir::PassManager::Global().LookUp<mir::TypeTargetTransformPass>(

lite/model_parser/model_parser.cc

@@ -247,6 +247,7 @@ void LoadModelPb(const std::string &model_dir,
   }
 
 #ifdef LITE_WITH_NPU
+  auto main_block = pb_proto_prog.blocks(0);
   for (auto &op : main_block.ops()) {
     LOG(INFO) << "op type:" << op.type();
     if (op.type() != "graph_op") {

lite/npu/bridge/utils.cc

@@ -113,48 +113,6 @@ ge::TensorPtr CvtFromLiteTensor(lite::Tensor* in_tensor,
   return out_tensor;
 }
 
-std::shared_ptr<ge::Operator> CvtNode(lite::mir::Node* var_node,
-                                      const Scope* scope) {
-  CHECK(var_node->IsArg());
-  const auto& arg = var_node->AsArg();
-  VLOG(4) << "Convert var node " << arg.name;
-
-  auto* var = scope->FindVar(arg.name);
-  CHECK(var);
-  auto* tensor = var->GetMutable<lite::Tensor>();
-  CHECK(tensor);
-  auto dims = tensor->dims();
-  if (arg.is_weight) {
-    auto wgt = std::make_shared<ge::op::Const>(arg.name);
-    LOG(INFO) << "in convert const:" << arg.name;
-    LOG(INFO) << dims;
-    wgt->set_attr_value(CvtFromLiteTensor(tensor));
-
-    auto odesc = wgt->GetOutputDesc(0);
-    LOG(INFO) << "const ----";
-    for (auto i : odesc.GetShape().GetDims()) {
-      LOG(INFO) << ";;;;;;;;;------: " << i;
-    }
-    return wgt;
-  } else {
-    CHECK_EQ(dims.size(), 4);
-    LOG(INFO) << "in convert data:" << arg.name;
-    LOG(INFO) << dims;
-    // TODO(TJ): support more types and dims size
-    ge::TensorDesc desc(ge::Shape(dims.Vectorize()),
-                        ge::Format::FORMAT_NCHW,
-                        ge::DataType::DT_FLOAT);
-
-    //   auto size = desc.GetShape().GetShapeSize();
-    //  ge::TensorUtils::SetSize(desc, size*sizeof(float));
-    //  ge::TensorUtils::SetRealDimCnt(desc, 4);
-    auto data = std::make_shared<ge::op::Data>(arg.name);
-    data->update_input_desc_x(desc);
-    return data;
-  }
-  return nullptr;
-}
-
 bool HasInputArg(const OpInfo* op_info,
                  const Scope* scope,
                  const std::string& argname) {

lite/npu/bridge/utils.h

@@ -84,11 +84,6 @@ ge::TensorPtr CreateTensorAndFillData(T value,
   return CreateTensorAndFillData(data, shape, format);
 }
 
-std::shared_ptr<ge::Operator> CvtNode2Tensor(const lite::mir::Node* arg_node);
-
-std::shared_ptr<ge::Operator> CvtNode(lite::mir::Node* var_node,
-                                      const Scope* scope);
-
 bool HasInputArg(const OpInfo* op_info,
                  const Scope* scope,
                  const std::string& argname);

lite/tools/build_npu.sh

@@ -62,6 +62,7 @@ function cmake_npu {
         -DWITH_LITE=ON \
         -DLITE_WITH_CUDA=OFF \
         -DLITE_WITH_X86=OFF \
+        -DLITE_BUILD_EXTRA=ON \
         -DLITE_WITH_ARM=ON \
         -DWITH_ARM_DOTPROD=ON   \
         -DLITE_WITH_LIGHT_WEIGHT_FRAMEWORK=ON \