FIX: cppint code style

paddle/function/GemmConvOp.cpp

@@ -117,8 +117,7 @@ public:
     ConvFunctionBase::init(config);
   }
 
-  virtual void check(const BufferArgs& inputs,
-                     const BufferArgs& outputs) override {
+  void check(const BufferArgs& inputs, const BufferArgs& outputs) override {
     const TensorShape& input = inputs[0].shape();
     const TensorShape& filter = inputs[1].shape();
     const TensorShape& output = outputs[0].shape();
@@ -217,8 +216,7 @@ public:
     ConvFunctionBase::init(config);
   }
 
-  virtual void check(const BufferArgs& inputs,
-                     const BufferArgs& outputs) override {
+  void check(const BufferArgs& inputs, const BufferArgs& outputs) override {
     const TensorShape& output = inputs[0].shape();
     const TensorShape& filter = inputs[1].shape();
     const TensorShape& input = outputs[0].shape();
@@ -311,8 +309,7 @@ public:
     ConvFunctionBase::init(config);
   }
 
-  virtual void check(const BufferArgs& inputs,
-                     const BufferArgs& outputs) override {
+  void check(const BufferArgs& inputs, const BufferArgs& outputs) override {
     const TensorShape& output = inputs[0].shape();
     const TensorShape& input = inputs[1].shape();
     const TensorShape& filter = outputs[0].shape();

paddle/function/NaiveConvOp.cpp

@@ -90,8 +90,7 @@ public:
     ConvFunctionBase::init(config);
   }
 
-  virtual void check(const BufferArgs& inputs,
-                     const BufferArgs& outputs) override {
+  void check(const BufferArgs& inputs, const BufferArgs& outputs) override {
     const TensorShape& input = inputs[0].shape();
     const TensorShape& filter = inputs[1].shape();
     const TensorShape& output = outputs[0].shape();

paddle/gserver/gradientmachines/NeuralNetwork.cpp

@@ -403,7 +403,7 @@ public:
       : layerName_(layerName) {
     addEvaluator(std::move(evaluator));
   }
-  virtual void eval(const NeuralNetwork& nn) override {
+  void eval(const NeuralNetwork& nn) override {
     const LayerPtr& layer = nn.getLayer(layerName_);
     CHECK(layer) << "Nonexisted layer: " << layerName_ << " in submodel "
                  << nn.getName();

paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp

@@ -636,7 +636,7 @@ void lenToStarts(std::vector<int>& starts) {
   }
   starts.back() = pos;
 }
-}
+}  // namespace
 
 void RecurrentGradientMachine::calcSequenceStartPositions() {
   std::vector<int> starts(commonSeqInfo_.size() + 1);

paddle/gserver/layers/AgentLayer.cpp

@@ -124,7 +124,7 @@ void copyElements(const IVector& srcVec,
     dest[index[i]] = src[i];
   }
 }
-}
+}  // namespace
 
 void GatherAgentLayer::forwardIds(PassType passType) {
   IVectorPtr realId = realLayers_[0]->getOutputLabel();

paddle/operators/add_op.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License. */
+
 #include <paddle/framework/op_registry.h>
 #include <paddle/framework/tensor.h>
 #include <paddle/operators/add_op.h>
@@ -36,7 +50,7 @@ The equation is: Out = X + Y
 )DOC");
   }
 };
-}  // namespace op
+}  // namespace operators
 }  // namespace paddle
 
 REGISTER_OP(add_two, paddle::operators::AddOp, paddle::operators::AddOpMaker);

paddle/optimizer/parameter_optimizer_test.cpp

+/*
+  Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+  Licensed under the Apache License, Version 2.0 (the "License");
+  you may not use this file except in compliance with the License.
+  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+  Unless required by applicable law or agreed to in writing, software
+  distributed under the License is distributed on an "AS IS" BASIS,
+  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+  See the License for the specific language governing permissions and
+  limitations under the License.
+*/
+
 #include "parameter_optimizer.h"
 #include <cmath>
 #include <map>
@@ -5,21 +21,18 @@
 #include "gtest/gtest.h"
 #include "lr_policy.h"
 
-using namespace paddle;
-using namespace paddle::optimizer;
-
-Tensor* FillTensor(size_t size) {
-  Tensor* param = new Tensor(size);
-  Tensor& p = *param;
+paddle::optimizer::Tensor* FillTensor(size_t size) {
+  paddle::optimizer::Tensor* param = new paddle::optimizer::Tensor(size);
+  paddle::optimizer::Tensor& p = *param;
   for (size_t i = 0; i < p.size(); ++i) {
     p[i] = (float)rand() / (float)RAND_MAX;
   }
   return param;
 }
 
-Tensor* FixedTensor(size_t size) {
-  Tensor* param = new Tensor(size);
-  Tensor& p = *param;
+paddle::optimizer::Tensor* FixedTensor(size_t size) {
+  paddle::optimizer::Tensor* param = new paddle::optimizer::Tensor(size);
+  paddle::optimizer::Tensor& p = *param;
   for (size_t i = 0; i < p.size(); ++i) {
     p[i] = i;
   }
@@ -28,7 +41,8 @@ Tensor* FixedTensor(size_t size) {
 
 class OptimizerTest : public testing::Test {
 public:
-  // init tensor shape
+  virtual ~OptimizerTest();
+  // init paddle::optimizer::Tensor shape
   const size_t kSize = 5;
 
   virtual void SetUp() {
@@ -38,34 +52,36 @@ public:
   virtual void TearDown() {}
 
   void CreateSGD() {
-    Tensor* parameter = FixedTensor(kSize);
-    config_.set_optimizer(OptimizerConfig::SGD);
+    paddle::optimizer::Tensor* parameter = FixedTensor(kSize);
+    config_.set_optimizer(paddle::OptimizerConfig::SGD);
     config_.mutable_sgd()->set_momentum(0.0);
     config_.mutable_sgd()->set_decay(0.0);
     config_.mutable_sgd()->set_nesterov(false);
-    config_.set_lr_policy(OptimizerConfig::Const);
+    config_.set_lr_policy(paddle::OptimizerConfig::Const);
     config_.mutable_const_lr()->set_learning_rate(0.1);
     std::string str = config_.SerializeAsString();
-    ParameterOptimizer* opt = ParameterOptimizer::Create(str, parameter);
+    paddle::optimizer::ParameterOptimizer* opt =
+        paddle::optimizer::ParameterOptimizer::Create(str, parameter);
     opts_.push_back(opt);
   }
 
   void CreateAdam() {
-    Tensor* parameter = FixedTensor(kSize);
-    config_.set_optimizer(OptimizerConfig::Adam);
+    paddle::optimizer::Tensor* parameter = FixedTensor(kSize);
+    config_.set_optimizer(paddle::OptimizerConfig::Adam);
     config_.mutable_adam()->set_beta_1(0.9);
     config_.mutable_adam()->set_beta_2(0.1);
     config_.mutable_adam()->set_epsilon(1e-3);
     config_.mutable_adam()->set_decay(0.0);
-    config_.set_lr_policy(OptimizerConfig::Const);
+    config_.set_lr_policy(paddle::OptimizerConfig::Const);
     config_.mutable_const_lr()->set_learning_rate(0.1);
     std::string str = config_.SerializeAsString();
-    ParameterOptimizer* opt = ParameterOptimizer::Create(str, parameter);
+    paddle::optimizer::ParameterOptimizer* opt =
+        paddle::optimizer::ParameterOptimizer::Create(str, parameter);
     opts_.push_back(opt);
   }
 
   void TestGetWeight() {
-    Tensor* p = FixedTensor(kSize);
+    paddle::optimizer::Tensor* p = FixedTensor(kSize);
     for (size_t i = 0; i < opts_.size(); ++i) {
       int s = 0;
       float* newp = (float*)opts_[i]->get_weight(&s);
@@ -76,7 +92,7 @@ public:
   }
 
   void TestUpdate() {
-    Tensor* g = FixedTensor(kSize);
+    paddle::optimizer::Tensor* g = FixedTensor(kSize);
     for (size_t i = 0; i < opts_.size(); ++i) {
       opts_[i]->Update(g);
     }
@@ -91,8 +107,8 @@ public:
   }
 
 private:
-  std::vector<ParameterOptimizer*> opts_;
-  OptimizerConfig config_;
+  std::vector<paddle::optimizer::ParameterOptimizer*> opts_;
+  paddle::OptimizerConfig config_;
 };
 
 TEST_F(OptimizerTest, TestGetWeight) { TestGetWeight(); }

paddle/optimizer/serialization_test.cpp

+/*
+  Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+  Licensed under the Apache License, Version 2.0 (the "License");
+  you may not use this file except in compliance with the License.
+  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+  Unless required by applicable law or agreed to in writing, software
+  distributed under the License is distributed on an "AS IS" BASIS,
+  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+  See the License for the specific language governing permissions and
+  limitations under the License.
+*/
+
 #include "serialization.h"
 #include "gtest/gtest.h"
 
-using namespace paddle;
-using namespace paddle::optimizer;
-
 TEST(TensorToProto, Case1) {
-  Tensor t(3), t1(3);
+  paddle::optimizer::Tensor t(3), t1(3);
   for (size_t i = 0; i < t.size(); ++i) {
     t[i] = i;
     t1[i] = 0;
   }
 
-  TensorProto proto;
-  TensorToProto(t, &proto);
-  ProtoToTensor(proto, &t1);
+  paddle::TensorProto proto;
+  paddle::optimizer::TensorToProto(t, &proto);
+  paddle::optimizer::ProtoToTensor(proto, &t1);
   for (size_t i = 0; i < t1.size(); ++i) {
     EXPECT_EQ(t1[i], t[i]);
   }

paddle/utils/DynamicLoader.h

@@ -12,8 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#ifndef DYNAMIC_LOAD_H_
-#define DYNAMIC_LOAD_H_
+#pragma once
 
 #include <dlfcn.h>
 #include <memory>
@@ -59,5 +58,3 @@ void GetWarpCTCDsoHandle(void** dso_handle);
  *
  */
 void GetLapackDsoHandle(void** dso_handle);
-
-#endif  // DYNAMIC_LOAD_H_

paddle/utils/ThreadLocal.h

@@ -51,7 +51,7 @@ template <class T>
 class ThreadLocal {
 public:
   ThreadLocal() {
-    CHECK(pthread_key_create(&threadSpecificKey_, dataDestructor) == 0);
+    CHECK_EQ(pthread_key_create(&threadSpecificKey_, dataDestructor), 0);
   }
   ~ThreadLocal() { pthread_key_delete(threadSpecificKey_); }
 
@@ -65,7 +65,7 @@ public:
     if (!p && createLocal) {
       p = new T();
       int ret = pthread_setspecific(threadSpecificKey_, p);
-      CHECK(ret == 0);
+      CHECK_EQ(ret, 0);
     }
     return p;
   }
@@ -79,7 +79,7 @@ public:
     if (T* q = get(false)) {
       dataDestructor(q);
     }
-    CHECK(pthread_setspecific(threadSpecificKey_, p) == 0);
+    CHECK_EQ(pthread_setspecific(threadSpecificKey_, p), 0);
   }
 
   /**
@@ -112,7 +112,7 @@ private:
 template <class T>
 class ThreadLocalD {
 public:
-  ThreadLocalD() { CHECK(pthread_key_create(&threadSpecificKey_, NULL) == 0); }
+  ThreadLocalD() { CHECK_EQ(pthread_key_create(&threadSpecificKey_, NULL), 0); }
   ~ThreadLocalD() {
     pthread_key_delete(threadSpecificKey_);
     for (auto t : threadMap_) {
@@ -127,7 +127,7 @@ public:
     T* p = (T*)pthread_getspecific(threadSpecificKey_);
     if (!p) {
       p = new T();
-      CHECK(pthread_setspecific(threadSpecificKey_, p) == 0);
+      CHECK_EQ(pthread_setspecific(threadSpecificKey_, p), 0);
       updateMap(p);
     }
     return p;
@@ -141,7 +141,7 @@ public:
     if (T* q = (T*)pthread_getspecific(threadSpecificKey_)) {
       dataDestructor(q);
     }
-    CHECK(pthread_setspecific(threadSpecificKey_, p) == 0);
+    CHECK_EQ(pthread_setspecific(threadSpecificKey_, p), 0);
     updateMap(p);
   }