clean the codes

paddle/framework/op_desc.proto

@@ -51,9 +51,6 @@ message OpDesc {
     // type of this Operator, such as "add", "sub", "fc".
     required string type = 3;
 
-    // the name of this Operator.
-    required string name = 4;
-
     // Attributes of this Operator. e.g., scale=3.0 in cosine op.
-    repeated AttrDesc attrs = 5;
-};
+    repeated AttrDesc attrs = 4;
+};

paddle/framework/recurrent_network_op.cc

@@ -69,7 +69,6 @@ void RecurrentOp::Init(const OpDesc& op_desc, AttributeMap& attrs) {
     outputs_.push_back(output);
   }
 
-  name_ = op_desc.name();
   net_name_ = inputs_.at(GetAttr<int>("step_net"));
   step_scopes_name_ = outputs_.back();
 

paddle/framework/recurrent_network_op.h

@@ -92,7 +92,7 @@ class PlainNet {
 // TODO:
 // 1. No-padding computing for sequences with indifinite length in one batch.
 // 2. Hierarchical RNN for sequence with sub-sequence.
-// 3. Multi-inputs with indifinate length for RecurrentOp.
+// 3. External Memory.
 // 4. More Complex RNN architecture, such as Gated Feedback RNN.
 //    Refer to: https://arxiv.org/pdf/1502.02367.pdf
 
@@ -143,11 +143,6 @@ class RecurrentOp : public OperatorBase {
    */
   void ConcatOutputs(ScopePtr scope) const;
 
-  /*
-   * Create a `Net` which is shared across all steps.
-   */
-  // void CreateStepNet(ScopePtr scope) const;
-
   /*
    * the step scopes as the father scope. The step scopes will be stored in
    * the father scope as a variable whose name is specified by
@@ -158,11 +153,6 @@ class RecurrentOp : public OperatorBase {
    */
   void CreateScopes(ScopePtr scope) const;
 
-  /*
-   * Create memories in each step scope.
-   */
-  // void CreateMemories(ScopePtr scope) const;
-
   /*
    * Link memory in previous step scope to current scope.
    */
@@ -213,9 +203,6 @@ class RecurrentOp : public OperatorBase {
   // TODO copy from OpBase's
   mutable std::vector<MemoryAttr> memory_attrs_;
 
-  // this op's name, used as a unique key in father scope.
-  // TODO repace it with OpBase's interface if supported.
-  std::string name_;
   // name of rnn op's step net, the step net will be shared by both `Forward`
   // and `Backward`, so we store it as a variable in father's scope, with a
   // unique key specified by `net_name_`.

paddle/framework/recurrent_network_op_test.cc

@@ -24,7 +24,7 @@ namespace framework {
 namespace fake {
 class FcOp : public OperatorBase {
  public:
-  FcOp(const OpDesc& desc) : name_(desc.name()) {}
+  FcOp(const OpDesc& desc) {}
 
   virtual void InferShape(ScopePtr scope) const override {
     for (const auto& output : outputs_) {
@@ -54,7 +54,7 @@ class FcOp : public OperatorBase {
 
 class AddOp : public OperatorBase {
  public:
-  AddOp(const OpDesc& desc) : name_(desc.name()) {}
+  AddOp(const OpDesc& desc) {}
 
   virtual void InferShape(ScopePtr scope) const override {
     for (const auto& output : outputs_) {
@@ -136,7 +136,6 @@ class RecurrentOpTest : public ::testing::Test {
     OpDesc op_desc;
 
     op_desc.set_type("rnn_op");
-    op_desc.set_name("rnn");
     op_desc.add_inputs("x");
     op_desc.add_inputs("h_boot");    // initial memory
     op_desc.add_inputs("step_net");  // step net
@@ -204,22 +203,20 @@ class RecurrentOpTest : public ::testing::Test {
   OpDesc CreateFcOpDesc() {
     OpDesc op_desc;
     op_desc.set_type("fc");
-    op_desc.set_name("fc");
     op_desc.add_inputs("rnn/h_pre");
     op_desc.add_inputs("rnn/w");
     op_desc.add_outputs("rnn/s");
-    // s = h_pre * check
+    // rnn/s = rnn/h_pre * rnn/w
     return op_desc;
   }
 
   OpDesc CreateAddOpDesc() {
     OpDesc op_desc;
     op_desc.set_type("add");
-    op_desc.set_name("add");
     op_desc.add_inputs("rnn/x");
     op_desc.add_inputs("rnn/s");
     op_desc.add_outputs("rnn/h");
-    // h = x + s
+    // rnn/h = rnn/x + rnn/s
     return op_desc;
   }