polish graph

paddle/fluid/framework/details/broadcast_op_handle_test.cc

@@ -96,7 +96,7 @@ struct TestBroadcastOpHandle {
     }
     param_scopes_[input_scope_idx]->Var("input");
 
-    std::unique_ptr<ir::Node> n(new ir::Node());
+    std::unique_ptr<ir::Node> n(new ir::Node("node0"));
     if (use_gpu_) {
 #ifdef PADDLE_WITH_CUDA
       op_handle_.reset(new BroadcastOpHandle(n.get(), local_scopes_, gpu_list_,
@@ -114,7 +114,7 @@ struct TestBroadcastOpHandle {
 #endif
     }
 
-    std::unique_ptr<ir::Node> v(new ir::Node());
+    std::unique_ptr<ir::Node> v(new ir::Node("node1"));
     auto* in_var_handle = new VarHandle(v.get(), 1, input_scope_idx, "input",
                                         gpu_list_[input_scope_idx]);
     vars_.emplace_back(in_var_handle);
@@ -122,7 +122,7 @@ struct TestBroadcastOpHandle {
 
     // add dummy var
 
-    std::unique_ptr<ir::Node> v2(new ir::Node());
+    std::unique_ptr<ir::Node> v2(new ir::Node("node2"));
     vars_.emplace_back(new DummyVarHandle(v2.get()));
     DummyVarHandle* dummy_var_handle =
         static_cast<DummyVarHandle*>(vars_.back().get());
@@ -133,7 +133,7 @@ struct TestBroadcastOpHandle {
       if (!use_gpu_) {
         op_handle_->SetDeviceContext(gpu_list_[j], ctxs_[j].get());
       }
-      std::unique_ptr<ir::Node> v3(new ir::Node());
+      std::unique_ptr<ir::Node> v3(new ir::Node("node3"));
       VarHandle* out_var_handle =
           new VarHandle(v3.get(), 2, j, "out", gpu_list_[j]);
       vars_.emplace_back(out_var_handle);
@@ -141,7 +141,7 @@ struct TestBroadcastOpHandle {
     }
 
     // add dummy var
-    std::unique_ptr<ir::Node> v4(new ir::Node());
+    std::unique_ptr<ir::Node> v4(new ir::Node("node4"));
     vars_.emplace_back(new DummyVarHandle(v4.get()));
     DummyVarHandle* out_dummy_var_handle =
         static_cast<DummyVarHandle*>(vars_.back().get());

paddle/fluid/framework/details/computation_op_handle.cc

@@ -19,10 +19,10 @@
 namespace paddle {
 namespace framework {
 namespace details {
-ComputationOpHandle::ComputationOpHandle(ir::Node *node, const OpDesc &op_desc,
-                                         Scope *scope, platform::Place place)
+ComputationOpHandle::ComputationOpHandle(ir::Node *node, Scope *scope,
+                                         platform::Place place)
     : OpHandleBase(node),
-      op_(framework::OpRegistry::CreateOp(op_desc)),
+      op_(framework::OpRegistry::CreateOp(*node->Op())),
       scope_(scope),
       place_(place) {}
 

paddle/fluid/framework/details/computation_op_handle.h

@@ -28,8 +28,7 @@ namespace framework {
 namespace details {
 struct ComputationOpHandle : public OpHandleBase {
  public:
-  ComputationOpHandle(ir::Node *node, const OpDesc &op_desc, Scope *scope,
-                      platform::Place place);
+  ComputationOpHandle(ir::Node *node, Scope *scope, platform::Place place);
 
   std::string Name() const override;
 

paddle/fluid/framework/details/gather_op_handle_test.cc

@@ -82,13 +82,13 @@ struct TestGatherOpHandle {
     }
     param_scopes_[input_scope_idx]->Var("out");
 
-    nodes.emplace_back(new ir::Node());
+    nodes.emplace_back(new ir::Node("node"));
     op_handle_.reset(
         new GatherOpHandle(nodes.back().get(), local_scopes_, gpu_list_));
     // add input
     for (size_t j = 0; j < gpu_list_.size(); ++j) {
       op_handle_->SetDeviceContext(gpu_list_[j], ctxs_[j].get());
-      nodes.emplace_back(new ir::Node());
+      nodes.emplace_back(new ir::Node("node1"));
       auto* in_var_handle =
           new VarHandle(nodes.back().get(), 1, j, "input", gpu_list_[j]);
       vars_.emplace_back(in_var_handle);
@@ -96,7 +96,7 @@ struct TestGatherOpHandle {
     }
 
     // add dummy var
-    nodes.emplace_back(new ir::Node());
+    nodes.emplace_back(new ir::Node("node2"));
     vars_.emplace_back(new DummyVarHandle(nodes.back().get()));
     DummyVarHandle* in_dummy_var_handle =
         static_cast<DummyVarHandle*>(vars_.back().get());
@@ -104,14 +104,14 @@ struct TestGatherOpHandle {
     op_handle_->AddInput(in_dummy_var_handle);
 
     // add output
-    nodes.emplace_back(new ir::Node());
+    nodes.emplace_back(new ir::Node("node3"));
     auto* out_var_handle = new VarHandle(nodes.back().get(), 2, input_scope_idx,
                                          "out", gpu_list_[input_scope_idx]);
     vars_.emplace_back(out_var_handle);
     op_handle_->AddOutput(out_var_handle);
 
     // add dummy var
-    nodes.emplace_back(new ir::Node());
+    nodes.emplace_back(new ir::Node("node4"));
     vars_.emplace_back(new DummyVarHandle(nodes.back().get()));
     DummyVarHandle* dummy_var_handle =
         static_cast<DummyVarHandle*>(vars_.back().get());

paddle/fluid/framework/details/multi_devices_graph_builder.cc

@@ -90,7 +90,7 @@ std::vector<std::string> MultiDevSSAGraphBuilder::FindDistTrainSendVars(
   // since parameters are all in block 0,
   // it's enough to only scan send ops in block 0
   for (auto &node : nodes) {
-    if (!node->Op()) continue;
+    if (node->NodeType() != ir::Node::Type::kOperation) continue;
     OpDesc *op = node->Op();
     // TODO(Yancey1989): use a graceful method to find send op,
     // instead of the the hard code string
@@ -108,7 +108,7 @@ std::vector<std::string> MultiDevSSAGraphBuilder::FindDistTrainRecvVars(
     const std::vector<std::unique_ptr<ir::Node>> &nodes) const {
   std::vector<std::string> recv_vars;
   for (auto &node : nodes) {
-    if (!node->Op()) continue;
+    if (node->NodeType() != ir::Node::Type::kOperation) continue;
     OpDesc *op = node->Op();
     // TODO(Yancey1989): use a graceful method to find recv op,
     // instead of the hard code string
@@ -149,10 +149,10 @@ bool MultiDevSSAGraphBuilder::IsDistTrainOp(
   std::vector<std::string> input_var_names;
   std::vector<std::string> output_var_names;
   for (ir::Node *input : node->inputs) {
-    input_var_names.push_back(input->Var()->Name());
+    input_var_names.push_back(input->Name());
   }
   for (ir::Node *output : node->outputs) {
-    output_var_names.push_back(output->Var()->Name());
+    output_var_names.push_back(output->Name());
   }
 
   return checker(output_var_names, send_vars) ||
@@ -181,13 +181,13 @@ size_t MultiDevSSAGraphBuilder::GetAppropriateDeviceID(
 
 std::unique_ptr<Graph> MultiDevSSAGraphBuilder::Apply(
     std::unique_ptr<Graph> graph) const {
+  // Rebuild the graph structure.
   auto nodes = std::move(graph->nodes);
   graph->nodes.clear();
-  LOG(ERROR) << "origin nodes count " << nodes.size();
 
   for (auto &node : nodes) {
-    if (node->Var()) {
-      all_vars_.emplace(node->Var()->Name(), node->Var());
+    if (node->NodeType() == ir::Node::Type::kVariable) {
+      all_vars_.emplace(node->Name(), node->Var());
     }
   }
 
@@ -212,7 +212,7 @@ std::unique_ptr<Graph> MultiDevSSAGraphBuilder::Apply(
 
   // TODO(panyx0718): FIXME: nodes should be sorted by "program" order.
   for (auto &node : nodes) {
-    if (!node->Op()) continue;
+    if (node->NodeType() != ir::Node::Type::kOperation) continue;
     if (boost::get<int>(
             node->Op()->GetAttr(OpProtoAndCheckerMaker::OpRoleAttrName())) ==
         static_cast<int>(OpRole::kRPC)) {
@@ -235,7 +235,7 @@ std::unique_ptr<Graph> MultiDevSSAGraphBuilder::Apply(
       if (op_dev_id != -1) {  // This op only runs on one specific device.
         CreateComputationalOp(&result, node.get(), op_dev_id);
         for (ir::Node *n : node->outputs) {
-          var_name_on_devices_.emplace(n->Var()->Name(), op_dev_id);
+          var_name_on_devices_.emplace(n->Name(), op_dev_id);
         }
       } else {
         // This op runs on all devices, and its output may have parameter's
@@ -351,10 +351,10 @@ void MultiDevSSAGraphBuilder::CreateBroadcastOp(Graph *result,
                                                 const std::string &p_name,
                                                 size_t src_dev_id) const {
 #ifdef PADDLE_WITH_CUDA
-  auto *op_handle = new BroadcastOpHandle(result->CreateOpNode(nullptr),
+  auto *op_handle = new BroadcastOpHandle(result->CreateEmptyNode("broadcast"),
                                           local_scopes_, places_, nccl_ctxs_);
 #else
-  auto *op_handle = new BroadcastOpHandle(result->CreateOpNode(nullptr),
+  auto *op_handle = new BroadcastOpHandle(result->CreateEmptyNode("broadcast"),
                                           local_scopes_, places_);
 #endif
   result->Get<GraphOps>("ops").emplace_back(op_handle);
@@ -367,8 +367,8 @@ void MultiDevSSAGraphBuilder::CreateBroadcastOp(Graph *result,
     auto &p = places_[i];
     SetCommunicationContext(op_handle, p);
     auto &vars = result->Get<GraphVars>("vars").at(i).at(p_name);
-    auto *out_var =
-        new VarHandle(result->CreateVarNode(p_name), vars.size(), i, p_name, p);
+    auto *out_var = new VarHandle(result->CreateEmptyNode(p_name), vars.size(),
+                                  i, p_name, p);
     vars.emplace_back(out_var);
     op_handle->AddOutput(out_var);
   }
@@ -378,7 +378,7 @@ void MultiDevSSAGraphBuilder::CreateComputationalOp(Graph *result,
                                                     ir::Node *node,
                                                     int dev_id) const {
   result->Get<GraphOps>("ops").emplace_back(
-      new ComputationOpHandle(result->CreateOpNode(node->Op()), *node->Op(),
+      new ComputationOpHandle(result->CreateOpNode(node->Op()),
                               local_scopes_[dev_id], places_[dev_id]));
   CreateOpHandleIOs(result, node, dev_id);
 }
@@ -386,11 +386,12 @@ void MultiDevSSAGraphBuilder::CreateComputationalOp(Graph *result,
 void MultiDevSSAGraphBuilder::InsertAllReduceOp(Graph *result,
                                                 const std::string &og) const {
 #ifdef PADDLE_WITH_CUDA
-  result->Get<GraphOps>("ops").emplace_back(new AllReduceOpHandle(
-      result->CreateOpNode(nullptr), local_scopes_, places_, nccl_ctxs_));
+  result->Get<GraphOps>("ops").emplace_back(
+      new AllReduceOpHandle(result->CreateEmptyNode("allreduce"), local_scopes_,
+                            places_, nccl_ctxs_));
 #else
   result->Get<GraphOps>("ops").emplace_back(new AllReduceOpHandle(
-      result->CreateOpNode(nullptr), local_scopes_, places_));
+      result->CreateEmptyNode("allreduce"), local_scopes_, places_));
 #endif
   auto *op_handle = result->Get<GraphOps>("ops").back().get();
 
@@ -402,7 +403,8 @@ void MultiDevSSAGraphBuilder::InsertAllReduceOp(Graph *result,
     auto &prev_grad = vars.back();
     op_handle->AddInput(prev_grad.get());
 
-    auto var = new VarHandle(result->CreateVarNode(og), vars.size(), i, og, p);
+    auto var =
+        new VarHandle(result->CreateEmptyNode(og), vars.size(), i, og, p);
     vars.emplace_back(var);
     op_handle->AddOutput(var);
   }
@@ -411,11 +413,12 @@ void MultiDevSSAGraphBuilder::InsertAllReduceOp(Graph *result,
 void MultiDevSSAGraphBuilder::InsertDataBalanceOp(
     Graph *result, const std::vector<std::string> &datas) const {
 #ifdef PADDLE_WITH_CUDA
-  result->Get<GraphOps>("ops").emplace_back(new DataBalanceOpHandle(
-      result->CreateOpNode(nullptr), local_scopes_, places_, nccl_ctxs_));
+  result->Get<GraphOps>("ops").emplace_back(
+      new DataBalanceOpHandle(result->CreateEmptyNode("data_balance"),
+                              local_scopes_, places_, nccl_ctxs_));
 #else
   result->Get<GraphOps>("ops").emplace_back(new DataBalanceOpHandle(
-      result->CreateOpNode(nullptr), local_scopes_, places_));
+      result->CreateEmptyNode("data_balance"), local_scopes_, places_));
 #endif
   auto *op_handle = result->Get<GraphOps>("ops").back().get();
   for (size_t i = 0; i < places_.size(); ++i) {
@@ -425,7 +428,7 @@ void MultiDevSSAGraphBuilder::InsertDataBalanceOp(
       auto &vars = result->Get<GraphVars>("vars")[i][d_name];
       PADDLE_ENFORCE(!vars.empty());
       op_handle->AddInput(vars.back().get());
-      auto var = new VarHandle(result->CreateVarNode(d_name), vars.size(), i,
+      auto var = new VarHandle(result->CreateEmptyNode(d_name), vars.size(), i,
                                d_name, p);
       vars.emplace_back(var);
       op_handle->AddOutput(var);
@@ -455,12 +458,12 @@ int MultiDevSSAGraphBuilder::GetOpDeviceID(ir::Node *node) const {
     return -1;
   }
   auto param_grad = boost::get<std::vector<std::string>>(
-      node->Op()->.GetAttr(OpProtoAndCheckerMaker::OpRoleVarAttrName()));
+      node->Op()->GetAttr(OpProtoAndCheckerMaker::OpRoleVarAttrName()));
 
   PADDLE_ENFORCE_EQ(param_grad.size(), 2U);
   int dev_id = GetVarDeviceID(param_grad[1]);
-  PADDLE_ENFORCE_NE(dev_id, -1, "dev_id should not be -1.[%s, %s]", op.Type(),
-                    param_grad[0]);
+  PADDLE_ENFORCE_NE(dev_id, -1, "dev_id should not be -1.[%s, %s]",
+                    node->Op()->Type(), param_grad[0]);
   return dev_id;
 }
 
@@ -481,8 +484,8 @@ void MultiDevSSAGraphBuilder::CreateScaleLossGradOp(Graph *result) const {
         platform::DeviceContextPool::Instance().Get(platform::CPUPlace());
 #endif
     auto *op_handle = new ScaleLossGradOpHandle(
-        result->CreateOpNode(nullptr), local_scopes_.size(), local_scopes_[i],
-        places_[i], communication_dev_ctx);
+        result->CreateEmptyNode("scale_loss_grad"), local_scopes_.size(),
+        local_scopes_[i], places_[i], communication_dev_ctx);
     result->Get<GraphOps>("ops").emplace_back(op_handle);
 
     // FIXME: Currently ScaleLossGradOp only use device_count as scale
@@ -495,7 +498,7 @@ void MultiDevSSAGraphBuilder::CreateScaleLossGradOp(Graph *result) const {
     const std::string grad_var_name = GradVarName(loss_var_name_);
     auto &vars = result->Get<GraphVars>("vars")[i][grad_var_name];
     size_t version = vars.size();
-    auto var = new VarHandle(result->CreateVarNode(grad_var_name), version, i,
+    auto var = new VarHandle(result->CreateEmptyNode(grad_var_name), version, i,
                              grad_var_name, places_[i]);
     vars.emplace_back(var);
     op_handle->AddOutput(var);
@@ -508,8 +511,8 @@ void MultiDevSSAGraphBuilder::CreateComputationalOps(Graph *result,
   for (size_t scope_idx = 0; scope_idx < num_places; ++scope_idx) {
     auto p = places_[scope_idx];
     auto s = local_scopes_[scope_idx];
-    result->Get<GraphOps>("ops").emplace_back(new ComputationOpHandle(
-        result->CreateOpNode(node->Op()), *node->Op(), s, p));
+    result->Get<GraphOps>("ops").emplace_back(
+        new ComputationOpHandle(result->CreateOpNode(node->Op()), s, p));
     CreateOpHandleIOs(result, node, scope_idx);
   }
 }
@@ -519,10 +522,10 @@ VarHandle *MultiDevSSAGraphBuilder::CreateReduceOp(Graph *result,
                                                    int dst_dev_id) const {
 #ifdef PADDLE_WITH_CUDA
   result->Get<GraphOps>("ops").emplace_back(new ReduceOpHandle(
-      result->CreateOpNode(nullptr), local_scopes_, places_, nccl_ctxs_));
+      result->CreateEmptyNode("reduce"), local_scopes_, places_, nccl_ctxs_));
 #else
   result->Get<GraphOps>("ops").emplace_back(new ReduceOpHandle(
-      result->CreateOpNode(nullptr), local_scopes_, places_));
+      result->CreateEmptyNode("reduce"), local_scopes_, places_));
 #endif
   auto *op_handle = result->Get<GraphOps>("ops").back().get();
 
@@ -535,7 +538,7 @@ VarHandle *MultiDevSSAGraphBuilder::CreateReduceOp(Graph *result,
     op_handle->AddInput(prev_grad.get());
   }
   auto &vars = result->Get<GraphVars>("vars")[dst_dev_id][og];
-  auto var = new VarHandle(result->CreateVarNode(og), vars.size(), dst_dev_id,
+  auto var = new VarHandle(result->CreateEmptyNode(og), vars.size(), dst_dev_id,
                            og, places_[dst_dev_id]);
   vars.emplace_back(var);
   op_handle->AddOutput(var);
@@ -548,7 +551,7 @@ void MultiDevSSAGraphBuilder::ConnectOp(Graph *result, OpHandleBase *op,
                                         const std::string &prev_op_name) const {
   for (auto &prev_op : result->Get<GraphOps>("ops")) {
     if (prev_op->Name() == prev_op_name) {
-      auto *dep_var = new DummyVarHandle(result->CreateVarNode("dummy"));
+      auto *dep_var = new DummyVarHandle(result->CreateEmptyNode("dummy"));
       prev_op->AddOutput(dep_var);
       result->Get<GraphDepVars>("dep_vars").emplace(dep_var);
       op->AddInput(dep_var);
@@ -562,10 +565,10 @@ void MultiDevSSAGraphBuilder::CreateDistTrainOp(Graph *result,
   std::vector<std::string> input_var_names;
   std::vector<std::string> output_var_names;
   for (ir::Node *input : node->inputs) {
-    input_var_names.push_back(input->Var()->Name());
+    input_var_names.push_back(input->Name());
   }
   for (ir::Node *output : node->outputs) {
-    output_var_names.push_back(output->Var()->Name());
+    output_var_names.push_back(output->Name());
   }
 
   if (node->Op()->Type() == "split_byref" ||
@@ -606,16 +609,16 @@ void MultiDevSSAGraphBuilder::CreateDistTrainOp(Graph *result,
 void MultiDevSSAGraphBuilder::CreateRPCOp(Graph *result, ir::Node *node) const {
   int op_dev_id = -1;
   if (node->Op()->Type() == "send") {
-    op_dev_id = GetVarDeviceID(node->inputs[0]->Var()->Name());
+    op_dev_id = GetVarDeviceID(node->inputs[0]->Name());
     // the variable name which contains .block means it was splited by
     // split_byref op
     // so that we can balance the variable blocks to all the pserver
     // instances.
     if (strategy_.reduce_ == BuildStrategy::ReduceStrategy::kAllReduce &&
-        node->inputs[0]->Var()->Name().find(".block") == std::string::npos) {
+        node->inputs[0]->Name().find(".block") == std::string::npos) {
       std::vector<std::string> input_var_names;
       for (ir::Node *n : node->inputs) {
-        input_var_names.push_back(n->Var()->Name());
+        input_var_names.push_back(n->Name());
       }
       op_dev_id = GetAppropriateDeviceID(input_var_names);
       for (auto &varname : input_var_names) {
@@ -625,7 +628,7 @@ void MultiDevSSAGraphBuilder::CreateRPCOp(Graph *result, ir::Node *node) const {
   } else if (node->Op()->Type() == "recv") {
     std::vector<std::string> output_var_names;
     for (ir::Node *n : node->outputs) {
-      output_var_names.push_back(n->Var()->Name());
+      output_var_names.push_back(n->Name());
     }
     op_dev_id = GetAppropriateDeviceID(output_var_names);
     for (auto &varname : output_var_names) {

paddle/fluid/framework/details/reduce_op_handle_test.cc

@@ -97,7 +97,7 @@ struct TestReduceOpHandle {
     }
     param_scopes_[out_scope_idx]->Var("out");
 
-    nodes.emplace_back(new ir::Node());
+    nodes.emplace_back(new ir::Node("node"));
     if (use_gpu_) {
 #ifdef PADDLE_WITH_CUDA
       op_handle_.reset(new ReduceOpHandle(nodes.back().get(), local_scopes_,
@@ -121,7 +121,7 @@ struct TestReduceOpHandle {
       if (!use_gpu_) {
         op_handle_->SetDeviceContext(gpu_list_[j], ctxs_[j].get());
       }
-      nodes.emplace_back(new ir::Node());
+      nodes.emplace_back(new ir::Node("node1"));
       auto *in_var_handle =
           new VarHandle(nodes.back().get(), 1, j, "input", gpu_list_[j]);
       in_var_handle->ClearGeneratedOp();
@@ -137,7 +137,7 @@ struct TestReduceOpHandle {
     op_handle_->AddInput(in_dummy_var_handle);
 
     // add output
-    nodes.emplace_back(new ir::Node());
+    nodes.emplace_back(new ir::Node("node2"));
     auto *out_var_handle = new VarHandle(nodes.back().get(), 2, out_scope_idx,
                                          "out", gpu_list_[out_scope_idx]);
     vars_.emplace_back(out_var_handle);

paddle/fluid/framework/details/ssa_graph_builder.cc

@@ -37,7 +37,7 @@ void SSAGraphBuilder::PolishGraphToSupportDataHazards(Graph *graph) {
             continue;
           }
 
-          auto *dep_var = new DummyVarHandle(graph->CreateVarNode("dummy"));
+          auto *dep_var = new DummyVarHandle(graph->CreateEmptyNode("dummy"));
           read_op->AddOutput(dep_var);
           write_op->AddInput(dep_var);
           graph->Get<GraphDepVars>("dep_vars").emplace(dep_var);
@@ -51,11 +51,16 @@ VarHandle *SSAGraphBuilder::CreateOrGetLatestVarHandle(
     Graph *graph, ir::Node *node, const platform::Place &place,
     size_t place_offset) {
   auto &var_holders = graph->Get<GraphVars>("vars")[place_offset];
-  auto &var_holder = var_holders[node->Var()->Name()];
+  auto &var_holder = var_holders[node->Name()];
   VarHandle *var = nullptr;
   if (var_holder.empty()) {
-    var = new VarHandle(graph->CreateVarNode(node->Var()), 0, place_offset,
-                        node->Var()->Name(), place);
+    if (node->NodeType() == ir::Node::Type::kVariable) {
+      var = new VarHandle(graph->CreateVarNode(node->Var()), 0, place_offset,
+                          node->Name(), place);
+    } else {
+      var = new VarHandle(graph->CreateEmptyNode(node->Name()), 0, place_offset,
+                          node->Name(), place);
+    }
     var_holder.emplace_back(var);
   } else {
     var = var_holder.rbegin()->get();
@@ -67,10 +72,10 @@ void SSAGraphBuilder::CreateOpOutput(Graph *graph, OpHandleBase *op_handle,
                                      ir::Node *node,
                                      const platform::Place &place,
                                      size_t place_offset) {
-  auto &vars = graph->Get<GraphVars>("vars")[place_offset][node->Var()->Name()];
+  auto &vars = graph->Get<GraphVars>("vars")[place_offset][node->Name()];
   size_t version = vars.size();
   auto var = new VarHandle(graph->CreateVarNode(node->Var()), version,
-                           place_offset, node->Var()->Name(), place);
+                           place_offset, node->Name(), place);
   vars.emplace_back(var);
   op_handle->AddOutput(var);
 }
@@ -82,7 +87,7 @@ void SSAGraphBuilder::AddOutputToLeafOps(Graph *graph) {
     if (!op->Outputs().empty()) {
       continue;
     }
-    auto *dummy_leaf = new DummyVarHandle(graph->CreateVarNode("dummy"));
+    auto *dummy_leaf = new DummyVarHandle(graph->CreateEmptyNode("dummy"));
     graph->Get<GraphDepVars>("dep_vars").emplace(dummy_leaf);
     op->AddOutput(dummy_leaf);
   }

paddle/fluid/framework/details/threaded_ssa_graph_executor.cc

@@ -173,7 +173,7 @@ void ThreadedSSAGraphExecutor::InsertFetchOps(
     auto &var_name = fetch_tensors[i];
     auto &vars = fetched_vars.at(var_name);
 
-    ir::Node *fetch_n = new ir::Node(ir::Node::Type::kOperation);
+    ir::Node *fetch_n = new ir::Node("fetch");
     auto *op = new FetchOpHandle(fetch_n, fetch_data, i, &local_scopes_);
     temp_nodes->emplace_back(fetch_n);
     fetch_ops->emplace_back(op);
@@ -186,7 +186,7 @@ void ThreadedSSAGraphExecutor::InsertFetchOps(
       op->AddInput(var);
     }
 
-    ir::Node *dummy_n = new ir::Node(ir::Node::Type::kVariable);
+    ir::Node *dummy_n = new ir::Node("fetch");
     auto *fetch_dummy = new DummyVarHandle(dummy_n);
     op->AddOutput(fetch_dummy);
     fetch_dependencies->emplace(fetch_dummy);

paddle/fluid/framework/ir/graph.cc

@@ -35,19 +35,15 @@ std::unique_ptr<Graph> ProgramToGraph(const ProgramDesc &program) {
       if (all_vars.count(each_var_name) != 0) {
         var = graph->CreateVarNode(all_vars.at(each_var_name));
       } else {
-        var = graph->CreateVarNode(each_var_name);
+        LOG(ERROR) << "input var not in all_var list: " << each_var_name;
+        var = graph->CreateEmptyNode(each_var_name);
       }
       node->inputs.push_back(var);
       var->outputs.push_back(node);
     }
 
     for (auto &each_var_name : op->OutputArgumentNames()) {
-      ir::Node *var = nullptr;
-      if (all_vars.count(each_var_name) != 0) {
-        var = graph->CreateVarNode(all_vars.at(each_var_name));
-      } else {
-        var = graph->CreateVarNode(each_var_name);
-      }
+      ir::Node *var = graph->CreateVarNode(all_vars.at(each_var_name));
       node->outputs.push_back(var);
       var->inputs.push_back(node);
     }

paddle/fluid/framework/ir/graph.h

@@ -72,16 +72,14 @@ class Graph {
   }
 
   // TODO(panyx0718): Need to handle CreateOpNode(nullptr).
-  ir::Node* CreateVarNode(const std::string& var_name) {
-    var_descs_.emplace_back(new VarDesc(var_name));
-    nodes.emplace_back(new ir::Node(var_descs_.back().get()));
+  ir::Node* CreateEmptyNode(const std::string& name) {
+    nodes.emplace_back(new ir::Node(name));
     return nodes.back().get();
   }
 
   std::vector<ir::Node*> inputs;
   std::vector<ir::Node*> outputs;
   std::vector<std::unique_ptr<ir::Node>> nodes;
-  std::vector<std::unique_ptr<VarDesc>> var_descs_;
 
  private:
   // NOTE: program_ shouldn't be exposed to user.

paddle/fluid/framework/ir/node.h

@@ -32,51 +32,43 @@ namespace ir {
 
 class Node {
  public:
-  enum class Type { kNone = -1, kOperation, kVariable };
+  enum class Type { kNone, kOperation, kVariable };
+  explicit Node(const std::string& name)
+      : name_(name),
+        var_desc_(nullptr),
+        op_desc_(nullptr),
+        type_(Type::kNone) {}
 
-  Node() : type_(Type::kNone) {}
-
-  explicit Node(Type type) : type_(type) {}
+  explicit Node(VarDesc* var_desc)
+      : name_(var_desc->Name()),
+        var_desc_(var_desc),
+        op_desc_(nullptr),
+        type_(Type::kVariable) {}
 
-  virtual ~Node() {
-    for (auto& attr : attrs_) {
-      if (attr_dels_.find(attr.first) != attr_dels_.end()) {
-        attr_dels_[attr.first]();
-      }
-    }
-    attr_dels_.clear();
-    attrs_.clear();
-  }
+  explicit Node(OpDesc* op_desc)
+      : name_(op_desc->Type()),
+        var_desc_(nullptr),
+        op_desc_(op_desc),
+        type_(Type::kOperation) {}
 
   Type NodeType() const { return type_; }
 
-  template <typename AttrType>
-  void Set(const std::string& name, AttrType attr) {
-    attrs_[name] = attr;
-  }
+  std::string Name() const { return name_; }
 
-  template <typename AttrType>
-  void Set(const std::string& name, AttrType* attr,
-           std::function<void(void)> attr_del) {
-    attrs_[name] = attr;
-    attr_dels_[name] = attr_del;
+  VarDesc* Var() {
+    PADDLE_ENFORCE(type_ == Type::kVariable);
+    return var_desc_;
+  }
+  OpDesc* Op() {
+    PADDLE_ENFORCE(type_ == Type::kOperation);
+    return op_desc_;
   }
-
-  VarDesc* Var() { return var_desc_; }
-  OpDesc* Op() { return op_desc_; }
-
-  explicit Node(VarDesc* var_desc)
-      : var_desc_(var_desc), op_desc_(nullptr), type_(Type::kVariable) {}
-
-  explicit Node(OpDesc* op_desc)
-      : var_desc_(nullptr), op_desc_(op_desc), type_(Type::kOperation) {}
 
   std::vector<Node*> inputs;
   std::vector<Node*> outputs;
 
  protected:
-  std::map<std::string, boost::any> attrs_;
-  std::map<std::string, std::function<void(void)>> attr_dels_;
+  const std::string name_;
   VarDesc* var_desc_;
   OpDesc* op_desc_;
   Type type_;

python/paddle/fluid/parallel_executor.py

@@ -148,7 +148,6 @@ class ParallelExecutor(object):
                 lambda var: var.persistable and var.type != core.VarDesc.VarType.RAW,
                 main.list_vars())
         ]
-        sys.stderr.write('!!!!!!!!before\n')
 
         self.executor = core.ParallelExecutor(
             self._places,
@@ -159,7 +158,6 @@ class ParallelExecutor(object):
             set(self.persistable_vars), main.desc, loss_name
             if loss_name else '', scope, local_scopes, exec_strategy,
             build_strategy, num_trainers, trainer_id)
-        sys.stderr.write('!!!!!!!!after\n')
         self.scope = scope
 
     def run(self, fetch_list, feed=None, feed_dict=None, return_numpy=True):