NewVar to GetOrCreateVar

doc/design/block.md

@@ -243,7 +243,7 @@ class SymbolTable {
   // TODO determine whether name is generated by python or C++.
   // Currently assume that a unique name will be generated by C++ if the
   // argument name is left default.
-  VarDesc* NewVar(const string& name="");
+  VarDesc* GetOrCreateVar(const string& name="");
 
   // find a VarDesc by name, if recursive is true, find parent's SymbolTable
   // recursively.

doc/design/scope.md

@@ -37,7 +37,7 @@ Scope is an association of a name to variable. All variables belong to `Scope`.
 ```cpp
 class Scope {
  public:
-  Variable* NewVar(const std::string& name);
+  Variable* GetOrCreateVar(const std::string& name);
   const Variable* FindVar(const std::string& name) const;
 
  private:
@@ -98,7 +98,7 @@ class Scope {
   Variable* FindVar(const std::string& name) const;
 
   // return if already contains same name variable.
-  Variable* NewVar(const std::string& name);
+  Variable* GetOrCreateVar(const std::string& name);
 
  private:
   std::shared_ptr<Scope> parent_;
@@ -107,7 +107,7 @@ class Scope {
 ```
 ## Only scope can create a variable
 
-To ensure `only scope can create a variable`, we should mark `Variable`'s constructor as a private member function, and Scope is a friend class of Variable. And then only `NewVar` can construct `Variable`.
+To ensure `only scope can create a variable`, we should mark `Variable`'s constructor as a private member function, and Scope is a friend class of Variable. And then only `GetOrCreateVar` can construct `Variable`.
 
 ## When scope destroyed, all variables inside this scope should be destroyed together
 
@@ -121,4 +121,4 @@ Also, as the parent scope is a `shared_ptr`, we can only `Create()` a scope shar
 
 ## Orthogonal interface
 
-`FindVar` will return `nullptr` when `name` is not found. It can be used as `Contains` method. `NewVar` will return an `Error` when there is a name conflict locally. Combine `FindVar` and `NewVar`, we can implement `NewVar` easily.
+`FindVar` will return `nullptr` when `name` is not found. It can be used as `Contains` method. `GetOrCreateVar` will return an `Error` when there is a name conflict locally. Combine `FindVar` and `GetOrCreateVar`, we can implement `GetOrCreateVar` easily.

doc/design/tensor_array.md

@@ -161,7 +161,7 @@ class TensorArray:
         @name: str
             the name of the variable to output.
         '''
-        tensor = NewVar(name)
+        tensor = GetOrCreateVar(name)
         tensor_array_stack(self.name, tensor)
         return tensor
 

paddle/framework/block_desc.cc

@@ -18,7 +18,7 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 
-VarDescBind *BlockDescBind::NewVar(const std::string &name) {
+VarDescBind *BlockDescBind::GetOrCreateVar(const std::string &name) {
   need_update_ = true;
   auto it = vars_.find(name);
   PADDLE_ENFORCE(it == vars_.end(), "Duplicated variable %s", name);

paddle/framework/executor.cc

@@ -66,7 +66,7 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id) {
 
   // Instantiate all the vars in the global scope
   for (auto& var : block.vars()) {
-    scope->NewVar(var.name());
+    scope->GetOrCreateVar(var.name());
   }
 
   Scope& local_scope = scope->NewScope();
@@ -78,7 +78,7 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id) {
       for (auto& var : block.ops(i).outputs()) {
         for (auto& argu : var.arguments()) {
           if (local_scope.FindVar(argu) == nullptr) {
-            local_scope.NewVar(argu);
+            local_scope.GetOrCreateVar(argu);
           }
         }
       }

paddle/framework/executor_test.cc

@@ -34,7 +34,7 @@ void AddOp(const std::string& type, const VariableNameMap& inputs,
   // insert output
   for (auto kv : outputs) {
     for (auto v : kv.second) {
-      auto var = block->NewVar(v);
+      auto var = block->GetOrCreateVar(v);
       var->SetDataType(paddle::framework::DataType::FP32);
     }
   }

paddle/framework/scope.cc

@@ -31,7 +31,7 @@ Scope& Scope::NewScope() const {
   return *kids_.back();
 }
 
-Variable* Scope::NewVar(const std::string& name) {
+Variable* Scope::GetOrCreateVar(const std::string& name) {
   auto iter = vars_.find(name);
   if (iter != vars_.end()) {
     return iter->second;
@@ -42,8 +42,8 @@ Variable* Scope::NewVar(const std::string& name) {
   return v;
 }
 
-Variable* Scope::NewVar() {
-  return NewVar(string::Sprintf("%p.%d", this, vars_.size()));
+Variable* Scope::GetOrCreateVar() {
+  return GetOrCreateVar(string::Sprintf("%p.%d", this, vars_.size()));
 }
 
 Variable* Scope::FindVar(const std::string& name) const {
@@ -71,8 +71,8 @@ framework::Scope& GetGlobalScope() {
   static std::unique_ptr<framework::Scope> g_scope{nullptr};
   std::call_once(feed_variable_flag, [&]() {
     g_scope.reset(new framework::Scope());
-    g_scope->NewVar("feed_value");
-    g_scope->NewVar("fetch_value");
+    g_scope->GetOrCreateVar("feed_value");
+    g_scope->GetOrCreateVar("fetch_value");
   });
   return *(g_scope.get());
 }

paddle/framework/scope.h

@@ -45,10 +45,10 @@ class Scope {
   Scope& NewScope() const;
 
   /// Create a variable with given name if it doesn't exist.
-  Variable* NewVar(const std::string& name);
+  Variable* GetOrCreateVar(const std::string& name);
 
   /// Create a variable with a scope-unique name.
-  Variable* NewVar();
+  Variable* GetOrCreateVar();
 
   /// Find a variable in the scope or any of its ancestors.  Returns
   /// nullptr if cannot find.

paddle/operators/cond_op.cc

@@ -134,7 +134,7 @@ void CondOp::PrepareDataForSubnet(
   for (int i = 0; i < BRANCH_NUM; ++i) {
     for (auto& output : (*sub_net_op_[i]).Outputs()) {
       for (auto& var_name : output.second) {
-        sub_scopes[i]->NewVar(var_name);
+        sub_scopes[i]->GetOrCreateVar(var_name);
       }
     }
   }

paddle/operators/dynamic_recurrent_op.cc

@@ -29,7 +29,7 @@ namespace detail {
 inline void CreateVariables(Scope& scope,
                             const std::vector<std::string>& var_names) {
   for (const auto& name : var_names) {
-    scope.NewVar(name);
+    scope.GetOrCreateVar(name);
   }
 }
 
@@ -112,7 +112,7 @@ void DynamicRecurrentOp::WriteStepInputs() const {
       auto& step_scope = cache_.GetScope(step);
       Variable* var = step_scope.FindVar(item.first);
       if (var == nullptr) {
-        var = step_scope.NewVar(item.first);
+        var = step_scope.GetOrCreateVar(item.first);
       }
       var->GetMutable<LoDTensor>()->ShareDataWith<value_type>(tensor);
     }
@@ -125,7 +125,7 @@ void DynamicRecurrentOp::WriteStepOutputs() const {
     for (auto& item : step_outputs_) {
       auto* var = scope.FindVar(item.first);
       if (var == nullptr) {
-        var = scope.NewVar(item.first);
+        var = scope.GetOrCreateVar(item.first);
       }
       auto* tensor = var->GetMutable<LoDTensor>();
       item.second.WriteShared(step, *tensor);

paddle/operators/dynamic_recurrent_op_test.cc

@@ -36,7 +36,7 @@ void OpDescNewVar(const std::string& param_name,
 // create a LoD tensor in scope with specific dims
 LoDTensor* CreateVar(Scope& scope, std::string name, framework::DDim dims,
                      const platform::Place& place) {
-  auto* var = scope.NewVar(name);
+  auto* var = scope.GetOrCreateVar(name);
   auto* tensor = var->GetMutable<LoDTensor>();
   tensor->Resize(dims);
   tensor->mutable_data<float>(place);
@@ -85,7 +85,7 @@ class DynamicRecurrentOpTestHelper : public ::testing::Test {
 
   void CreateGlobalVariables() {
     platform::CPUPlace place;
-    scope.NewVar("step_scopes");
+    scope.GetOrCreateVar("step_scopes");
     CreateVar(scope, "boot_mem", framework::make_ddim({10, 20}), place);
     // auto* out0 =
     CreateVar(scope, "out0", framework::make_ddim({10, 20}), place);

paddle/operators/recurrent_op.cc

@@ -70,14 +70,14 @@ void RecurrentAlgorithm::CreateScopes(const Scope& scope,
         // the weight are located in parent scope
         for (auto& var_name : input.second) {
           if (!step_scope.FindVar(var_name)) {
-            step_scope.NewVar(var_name)->GetMutable<LoDTensor>();
+            step_scope.GetOrCreateVar(var_name)->GetMutable<LoDTensor>();
           }
         }
       }
       // create stepnet's outputs
       for (const auto& output : (*stepnet_)->Outputs()) {
         for (auto& var_name : output.second) {
-          step_scope.NewVar(var_name);
+          step_scope.GetOrCreateVar(var_name);
         }
       }
       step_scopes->emplace_back(&step_scope);
@@ -87,7 +87,8 @@ void RecurrentAlgorithm::CreateScopes(const Scope& scope,
 
 void RecurrentAlgorithm::InitMemories(Scope* step_scope) const {
   for (auto& attr : arg_->memories) {
-    auto* pre_mem = step_scope->NewVar(attr.pre_var)->GetMutable<LoDTensor>();
+    auto* pre_mem =
+        step_scope->GetOrCreateVar(attr.pre_var)->GetMutable<LoDTensor>();
     PADDLE_ENFORCE(step_scope->FindVar(attr.boot_var) != nullptr,
                    "memory [%s]'s boot variable [%s] not exists", attr.var,
                    attr.boot_var);
@@ -167,9 +168,10 @@ void RecurrentGradientAlgorithm::LinkBootMemoryGradients(
                    "memory variable [%s] does not exists", attr.var);
     PADDLE_ENFORCE(step_scope->FindVar(attr.boot_var) != nullptr,
                    "boot variable [%s] does not exists", attr.boot_var);
-    auto* mem_grad = step_scope->NewVar(attr.var)->GetMutable<LoDTensor>();
+    auto* mem_grad =
+        step_scope->GetOrCreateVar(attr.var)->GetMutable<LoDTensor>();
     auto* boot_mem_grad =
-        step_scope->NewVar(attr.boot_var)->GetMutable<LoDTensor>();
+        step_scope->GetOrCreateVar(attr.boot_var)->GetMutable<LoDTensor>();
     boot_mem_grad->Resize(mem_grad->dims());
     boot_mem_grad->ShareDataWith<float>(*mem_grad);
   }

paddle/operators/rnn/recurrent_op_utils.cc

@@ -40,7 +40,7 @@ void SegmentInputs(const std::vector<Scope*>& step_scopes,
     f::DDim step_dims = slice_ddim(dims, 1, dims.size());
     for (size_t j = 0; j < seq_len; j++) {
       Tensor* step_input =
-          step_scopes[j]->NewVar(inlinks[i])->GetMutable<Tensor>();
+          step_scopes[j]->GetOrCreateVar(inlinks[i])->GetMutable<Tensor>();
       // The input of operators of each step is Tensor here.
       // Maybe need to modify Slice function.
       *step_input = input->Slice<float>(j, j + 1);

paddle/pybind/protobuf.cc

@@ -137,7 +137,7 @@ void BindBlockDesc(py::module &m) {
       .def("new_var",
            [](BlockDescBind &self, py::bytes byte_name) {
              std::string name = byte_name;
-             return self.NewVar(name);
+             return self.GetOrCreateVar(name);
            },
            py::return_value_policy::reference)
       .def("var",

paddle/pybind/pybind.cc

@@ -165,7 +165,7 @@ All parameter, weight, gradient are variables in Paddle.
   py::class_<Scope>(m, "Scope", "")
       .def("new_var",
            [](Scope &self, const std::string &name) -> Variable * {
-             return self.NewVar(name);
+             return self.GetOrCreateVar(name);
            },
            py::return_value_policy::reference)
       .def("find_var", &Scope::FindVar, py::return_value_policy::reference)