"protobuf required to optional"

paddle/optimizer/adam_optimizer.cc

@@ -26,7 +26,6 @@ const char *AdamOptimizer::SerializeState(int *state_len) {
   AdamOptimizerState state;
   // TODO(zhihong) : add lr_policy serialization
   state.set_num_sample_passed(num_sample_passed_);
-
   TensorToProto(*parameter_, state.mutable_parameter());
   TensorToProto(*momentums_, state.mutable_momentums());
   TensorToProto(*velocitys_, state.mutable_velocitys());
@@ -42,6 +41,7 @@ void AdamOptimizer::DeserializeState(const std::string &str) {
   num_sample_passed_ = state.num_sample_passed();
 
   ProtoToTensor(state.parameter(), parameter_);
+  ProtoToTensor(state.momentums(), momentums_);
   ProtoToTensor(state.velocitys(), velocitys_);
 }
 }  // namespace optimizer

paddle/optimizer/parameter_optimizer_test.cpp

@@ -45,11 +45,9 @@ public:
     config_.mutable_sgd()->set_nesterov(false);
     config_.set_lr_policy(OptimizerConfig::Const);
     config_.mutable_const_lr()->set_learning_rate(0.1);
-
     std::string str = config_.SerializeAsString();
     ParameterOptimizer* opt = ParameterOptimizer::Create(str, parameter);
     opts_.push_back(opt);
-    opts_table_[opts_.size()] = OptimizerConfig::SGD;
   }
 
   void CreateAdam() {
@@ -64,7 +62,6 @@ public:
     std::string str = config_.SerializeAsString();
     ParameterOptimizer* opt = ParameterOptimizer::Create(str, parameter);
     opts_.push_back(opt);
-    opts_table_[opts_.size()] = OptimizerConfig::Adam;
   }
 
   void TestGetWeight() {
@@ -86,21 +83,15 @@ public:
   }
 
   void TestCheckPoint() {
-    std::map<OptimizerConfig::Optimizer, int> expected_state_len = {
-        {OptimizerConfig::SGD, kSize * sizeof(float) + sizeof(double)},
-        {OptimizerConfig::Adam, kSize * 3 * sizeof(float) + sizeof(double)},
-    };
     for (size_t i = 0; i < opts_.size(); ++i) {
       int state_len = 0;
       std::string state = opts_[i]->SerializeState(&state_len);
-      EXPECT_EQ(state_len, expected_state_len[opts_table_[i + 1]]);
       opts_[i]->DeserializeState(state);
     }
   }
 
 private:
   std::vector<ParameterOptimizer*> opts_;
-  std::map<int, OptimizerConfig::Optimizer> opts_table_;
   OptimizerConfig config_;
 };
 

paddle/optimizer/sgd_optimizer.cc

@@ -42,7 +42,7 @@ void SGDOptimizer::DeserializeState(const std::string &str) {
   state.ParseFromString(str);
   num_sample_passed_ = state.num_sample_passed();
   ProtoToTensor(state.parameter(), parameter_);
-  ProtoToTensor(state.parameter(), momentums_);
+  if (momentum_ != 0.0) ProtoToTensor(state.parameter(), momentums_);
 }
 
 }  // namespace optimizer

proto/OptimizerConfig.proto

@@ -55,12 +55,12 @@ message AdamConfig {
 
 message ConstLrConfig {
   // learninRate Policy
-  required double learning_rate = 1 [default = 1.0];
+  optional double learning_rate = 1 [default = 1.0];
 }
 
 message LinearLrConfig {
   // learninRate Policy
-  required double learning_rate = 1 [default = 1.0];
+  optional double learning_rate = 1 [default = 1.0];
   optional double lr_decay_a = 2;
   optional double lr_decay_b = 3;
 }
@@ -74,7 +74,7 @@ enum DataType {
   PADDLE_ELEMENT_TYPE_FLOAT32 = 4;
   PADDLE_ELEMENT_TYPE_FLOAT64 = 5;
 }
-  required DataType data_type = 1;
+  optional DataType data_type = 1;
   repeated bytes content = 2;
 }
 
@@ -132,7 +132,7 @@ message OptimizerConfig {
    Adagrad = 3;
    Adam = 4;
   }
-  required Optimizer optimizer = 1;
+  optional Optimizer optimizer = 1;
   optional SGDConfig sgd = 3;
   optional AdadeltaConfig adadelta = 4;
   optional AdagradConfig adagrad = 5;
@@ -142,7 +142,7 @@ message OptimizerConfig {
    Const = 0;
    Linear = 1;
   }
-  required LrPolicy lr_policy = 11;
+  optional LrPolicy lr_policy = 11;
   optional ConstLrConfig const_lr = 12;
   optional LinearLrConfig linear_lr = 13;