fix develop build issue (#10978)

* fix develop build issue

* fix google style

* cpplint check only fluid

.clang-format

@@ -19,7 +19,7 @@ BasedOnStyle:  Google
 IndentWidth:     2
 TabWidth:        2
 ContinuationIndentWidth: 4
-AccessModifierOffset: -2  # The private/protected/public has no indent in class
+AccessModifierOffset: -1  # The private/protected/public has no indent in class
 Standard:  Cpp11 
 AllowAllParametersOfDeclarationOnNextLine: true
 BinPackParameters: false

paddle/api/GradientMachine.cpp

@@ -94,7 +94,7 @@ void UpdateCallback::apply(Parameter* p) {
 }
 
 class UpdateCallbackWrapper {
-public:
+ public:
   explicit UpdateCallbackWrapper(const UpdateCallback& callback)
       : callback(const_cast<UpdateCallback&>(callback)) {}
 
@@ -105,7 +105,7 @@ public:
     delete p;
   }
 
-private:
+ private:
   UpdateCallback& callback;
 };
 

paddle/api/SequenceGenerator.cpp

@@ -138,7 +138,7 @@ struct SequenceGeneratorPrivate {
         maxLength(0UL),
         feedback(__create_feedback__()) {}
 
-private:
+ private:
   static paddle::Argument __create_feedback__() {
     paddle::Argument feedback;
     feedback.ids = paddle::IVector::create(/* size= */ 1, FLAGS_use_gpu);
@@ -157,7 +157,7 @@ SequenceGenerator::~SequenceGenerator() { delete m; }
 
 class PathSequenceResults : public ISequenceResults {
   // ISequenceResults interface
-public:
+ public:
   PathSequenceResults(const std::shared_ptr<std::vector<Path>>& path,
                       const std::shared_ptr<std::vector<std::string>>& dict)
       : path_(path), dict_(dict) {}
@@ -196,7 +196,7 @@ public:
     }
   }
 
-private:
+ private:
   std::shared_ptr<std::vector<Path>> path_;
   std::shared_ptr<std::vector<std::string>> dict_;
 };

paddle/capi/gradient_machine.cpp

@@ -26,7 +26,7 @@ enum GradientMatchineCreateMode {
 namespace paddle {
 
 class MyNeuralNetwork : public NeuralNetwork {
-public:
+ public:
   MyNeuralNetwork(const std::string& name, NeuralNetwork* network)
       : NeuralNetwork(name, network) {}
 };

paddle/contrib/inference/paddle_inference_api.h

@@ -50,7 +50,7 @@ struct PaddleTensor {
 * TODO(Superjomn) Prepare another API for NLP-related usages.
 */
 class PaddlePredictor {
-public:
+ public:
   struct Config;
   PaddlePredictor() = default;
   PaddlePredictor(const PaddlePredictor&) = delete;
@@ -66,6 +66,7 @@ public:
   // be thread-safe.
   virtual std::unique_ptr<PaddlePredictor> Clone() = 0;
 
+  virtual bool InitShared() { return false; }
   // Destroy the Predictor.
   virtual ~PaddlePredictor() {}
 

paddle/contrib/inference/paddle_inference_api_impl.cc

@@ -28,7 +28,7 @@ namespace {
 
 // Timer for timer
 class Timer {
-public:
+ public:
   double start;
   double startu;
   void tic() {
@@ -135,8 +135,8 @@ bool PaddlePredictorImpl::Run(const std::vector<PaddleTensor> &inputs,
 
 std::unique_ptr<PaddlePredictor> PaddlePredictorImpl::Clone() {
   VLOG(3) << "Predictor::clone";
-  std::unique_ptr<PaddlePredictorImpl> cls(new PaddlePredictorImpl(config_));
-  if (!cls->InitShared(this)) {
+  std::unique_ptr<PaddlePredictor> cls(new PaddlePredictorImpl(config_));
+  if (!cls->InitShared()) {
     LOG(ERROR) << "fail to call InitShared";
     return nullptr;
   }
@@ -144,7 +144,7 @@ std::unique_ptr<PaddlePredictor> PaddlePredictorImpl::Clone() {
 }
 
 // TODO(panyx0718): Consider merge with Init()?
-bool PaddlePredictorImpl::InitShared(PaddlePredictorImpl *cls) {
+bool PaddlePredictorImpl::InitShared() {
   VLOG(3) << "Predictor::init_shared";
   // 1. Define place, executor, scope
   if (this->config_.device >= 0) {

paddle/contrib/inference/paddle_inference_api_impl.h

@@ -41,7 +41,7 @@ struct VisConfig : public PaddlePredictor::Config {
  * Do not use this, just a demo indicating how to customize a Predictor.
  */
 class PaddlePredictorImpl : public PaddlePredictor {
-public:
+ public:
   explicit PaddlePredictorImpl(const VisConfig &config) : config_(config) {}
 
   bool Init();
@@ -53,8 +53,8 @@ public:
 
   ~PaddlePredictorImpl() override{};
 
-private:
-  bool InitShared(PaddlePredictorImpl *cls);
+ private:
+  bool InitShared();
   bool SetFeed(const std::vector<PaddleTensor> &input_datas,
                std::vector<paddle::framework::LoDTensor> *feeds);
   bool GetFetch(const std::vector<paddle::framework::LoDTensor> &fetchs,

paddle/contrib/inference/test_paddle_inference_api.cc

@@ -31,7 +31,7 @@ struct DemoConfig : public PaddlePredictor::Config {
  * Do not use this, just a demo indicating how to customize a Predictor.
  */
 class DemoPredictor : public PaddlePredictor {
-public:
+ public:
   explicit DemoPredictor(const DemoConfig &config) {
     LOG(INFO) << "I get other_config " << config.other_config;
   }

paddle/cuda/include/hl_activation_functions.h

@@ -31,7 +31,7 @@ namespace hppl {
  */
 template <class T>
 class Active {
-public:
+ public:
   typedef T (*forward)(T);
   typedef T (*backward)(T, T);
 };

paddle/cuda/src/hl_cuda_lstm.cu

@@ -30,7 +30,7 @@ bool hl_lstm_sequence_parallel(int frameSize) {
 }
 
 class frameValue {
-public:
+ public:
   real *value_;
   __device__ frameValue(real *value) : value_(value) {}
   template <int reversed, int frameSize>

paddle/function/BlockExpandOp.cpp

@@ -33,7 +33,7 @@ namespace paddle {
  * \param outputs[0] Image data of NCHW format.
  */
 class BlockExpandFunction : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     // function arguments
     strides_ = config.get<std::vector<size_t>>("strides");
@@ -81,7 +81,7 @@ public:
                         (size_t)blockW()});
   }
 
-protected:
+ protected:
   std::vector<size_t> strides_;
   std::vector<size_t> paddings_;
   std::vector<size_t> blocks_;
@@ -101,7 +101,7 @@ protected:
 
 template <DeviceType Device>
 class BlockExpandForward : public BlockExpandFunction {
-public:
+ public:
   void init(const FuncConfig& config) override {
     BlockExpandFunction::init(config);
   }
@@ -149,7 +149,7 @@ public:
 
 template <DeviceType Device>
 class BlockExpandBackward : public BlockExpandFunction {
-public:
+ public:
   void init(const FuncConfig& config) override {
     BlockExpandFunction::init(config);
   }

paddle/function/BufferArg.h

@@ -63,12 +63,12 @@ enum ArgType {
   ADD_TO = 2,
 };
 class BufferArg {
-public:
+ public:
   void setArgType(ArgType argType) { argType_ = argType; }
 
   ArgType getArgType() const { return argType_; }
 
-public:
+ public:
   BufferArg(ValueType valueType,
             const TensorShape& shape,
             ArgType argType = UNSPECIFIED)
@@ -169,7 +169,7 @@ public:
   const SequenceArg& sequence() const;
   const SparseMatrixArg& sparse() const;
 
-protected:
+ protected:
   void* buf_;
   ValueType valueType_;
   TensorShape shape_;
@@ -185,7 +185,7 @@ protected:
 // valueType_ = int32
 // if a < b then value_.buf_[a] < value_.buf_[b]
 class SequenceIdArg : public BufferArg {
-public:
+ public:
   SequenceIdArg(const TensorShape& shape, ArgType argType = UNSPECIFIED)
       : BufferArg(VALUE_TYPE_INT32, shape, argType) {
     bufferType_ = TENSOR_SEQUENCE_ID;
@@ -212,7 +212,7 @@ public:
 
   size_t numSeqs() const { return numSeqs_; }
 
-private:
+ private:
   size_t numSeqs_;
 };
 
@@ -222,7 +222,7 @@ private:
 // SequenceArg can be used to represent sequences that contain multiple
 // unequal lengths.
 class SequenceArg : public BufferArg {
-public:
+ public:
   SequenceArg(ValueType valueType,
               const TensorShape& shape,
               ArgType argType = UNSPECIFIED)
@@ -255,7 +255,7 @@ public:
   SequenceIdArg& getSequenceId() { return startPositions_; }
   const SequenceIdArg& getSequenceId() const { return startPositions_; }
 
-private:
+ private:
   SequenceIdArg startPositions_;
 };
 
@@ -263,7 +263,7 @@ private:
 // valueType_ == float or double
 // shape_.ndims() == 2
 class SparseMatrixArg : public BufferArg {
-public:
+ public:
   SparseMatrixArg(void* buf,
                   ValueType valueType,
                   const TensorShape& shape,
@@ -353,7 +353,7 @@ public:
 
   SparseDataType dataType() const { return type_; }
 
-private:
+ private:
   BufferArg row_;
   BufferArg col_;
   size_t nnz_;

paddle/function/ContextProjectionOp.cpp

@@ -100,7 +100,7 @@ void ContextProjectionForward<DEVICE_TYPE_CPU>(CpuMatrix& out_mat,
  */
 template <DeviceType Device>
 class ContextProjectionForwardFunc : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     context_length_ = config.get<size_t>("context_length");
     context_start_ = config.get<int>("context_start");
@@ -146,7 +146,7 @@ public:
                                      begin_pad_);
   }
 
-private:
+ private:
   size_t context_length_;
   int context_start_;
   size_t begin_pad_;
@@ -223,7 +223,7 @@ void ContextProjectionBackward<DEVICE_TYPE_CPU>(const CpuMatrix& out_grad_mat,
  */
 template <DeviceType Device>
 class ContextProjectionBackwardFunc : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     context_length_ = config.get<size_t>("context_length");
     context_start_ = config.get<int>("context_start");
@@ -278,7 +278,7 @@ public:
                                       total_pad_);
   }
 
-private:
+ private:
   size_t context_length_;
   int context_start_;
   size_t begin_pad_;
@@ -299,7 +299,7 @@ private:
  */
 template <DeviceType Device>
 class ContextProjectionBackwardDataFunc : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     context_length_ = config.get<size_t>("context_length");
     context_start_ = config.get<int>("context_start");
@@ -331,7 +331,7 @@ public:
         out_grad_mat, in_grad_mat, seq_vec, context_length_, context_start_);
   }
 
-private:
+ private:
   size_t context_length_;
   int context_start_;
 };
@@ -348,7 +348,7 @@ private:
  */
 template <DeviceType Device>
 class ContextProjectionBackwardWeightFunc : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     context_length_ = config.get<size_t>("context_length");
     context_start_ = config.get<int>("context_start");
@@ -382,7 +382,7 @@ public:
                                             begin_pad_);
   }
 
-private:
+ private:
   size_t context_length_;
   int context_start_;
   size_t begin_pad_;

paddle/function/ConvOp.h

@@ -56,7 +56,7 @@ namespace paddle {
  *      H and W is height and width of filter.
  */
 class ConvFunctionBase : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     // function arguments
     strides_ = config.get<std::vector<size_t>>("strides");
@@ -101,7 +101,7 @@ public:
     }
   }
 
-protected:
+ protected:
   size_t getFilterHeight(const TensorShape& filter) const {
     return filter[filter.ndims() - 2];
   }

paddle/function/CosSimOp.cpp

@@ -97,7 +97,7 @@ class CosSimForwardFunc : public FunctionBase {
     CosSimForward<Device>(out_mat, in1_mat, in2_mat, scale_);
   }
 
-private:
+ private:
   real scale_;
 };
 
@@ -227,7 +227,7 @@ class CosSimBackwardFunc : public FunctionBase {
         out_grad, out_val, in1_val, in2_val, in1_grad, in2_grad, scale_);
   }
 
-private:
+ private:
   real scale_;
 };
 

paddle/function/CropOp.cpp

@@ -112,7 +112,7 @@ void CropGrad<DEVICE_TYPE_CPU>(const real* inGrad,
  */
 template <DeviceType Device>
 class CropFunc : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override { conf_ = config; }
 
   void calc(const BufferArgs& inputs, const BufferArgs& outputs) override {
@@ -130,7 +130,7 @@ public:
                  conf_);
   }
 
-private:
+ private:
   FuncConfig conf_;
 };
 
@@ -145,7 +145,7 @@ private:
 
 template <DeviceType Device>
 class CropGradFunc : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override { conf_ = config; }
 
   void calc(const BufferArgs& inputs, const BufferArgs& outputs) override {
@@ -163,7 +163,7 @@ public:
                      conf_);
   }
 
-private:
+ private:
   FuncConfig conf_;
 };
 

paddle/function/CrossMapNormalOp.cpp

@@ -160,7 +160,7 @@ void CrossMapNormalGrad<DEVICE_TYPE_CPU>(real* inputsGrad,
  */
 template <DeviceType Device>
 class CrossMapNormalFunc : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     // function arguments
     size_ = config.get<size_t>("size");
@@ -220,7 +220,7 @@ public:
     return ops;
   }
 
-private:
+ private:
   size_t size_;
   real scale_;
   real pow_;
@@ -260,7 +260,7 @@ private:
  */
 template <DeviceType Device>
 class CrossMapNormalGradFunc : public FunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     // function arguments
     size_ = config.get<size_t>("size");
@@ -328,7 +328,7 @@ public:
     return ops;
   }
 
-private:
+ private:
   size_t size_;
   real scale_;
   real pow_;

paddle/function/DepthwiseConvOp.cpp

@@ -19,7 +19,7 @@ namespace paddle {
 
 template <class T>
 class DepthwiseConvFunctor<DEVICE_TYPE_CPU, T> {
-public:
+ public:
   void operator()(const T* inputData,
                   const T* filterData,
                   int batchSize,
@@ -43,7 +43,7 @@ public:
 
 template <class T>
 class DepthwiseConvGradInputFunctor<DEVICE_TYPE_CPU, T> {
-public:
+ public:
   void operator()(const T* outputGrad,
                   const T* filterData,
                   int batchSize,
@@ -66,7 +66,7 @@ public:
 
 template <class T>
 class DepthwiseConvGradFilterFunctor<DEVICE_TYPE_CPU, T> {
-public:
+ public:
   void operator()(const T* outputGrad,
                   const T* inputData,
                   int batchSize,
@@ -93,7 +93,7 @@ public:
  */
 template <DeviceType Device>
 class DepthwiseConvFunction : public ConvFunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     ConvFunctionBase::init(config);
   }
@@ -156,7 +156,7 @@ public:
  */
 template <DeviceType Device>
 class DepthwiseConvGradInputFunction : public ConvFunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     ConvFunctionBase::init(config);
   }
@@ -220,7 +220,7 @@ public:
  */
 template <DeviceType Device>
 class DepthwiseConvGradFilterFunction : public ConvFunctionBase {
-public:
+ public:
   void init(const FuncConfig& config) override {
     ConvFunctionBase::init(config);
   }

paddle/function/DepthwiseConvOp.h

@@ -44,7 +44,7 @@ namespace paddle {
  */
 template <DeviceType Device, class T>
 class DepthwiseConvFunctor {
-public:
+ public:
   void operator()(const T* inputData,
                   const T* filterData,
                   int batchSize,
@@ -89,7 +89,7 @@ public:
  */
 template <DeviceType Device, class T>
 class DepthwiseConvGradInputFunctor {
-public:
+ public:
   void operator()(const T* outputGrad,
                   const T* filterData,
                   int batchSize,
@@ -135,7 +135,7 @@ public:
  */
 template <DeviceType Device, class T>
 class DepthwiseConvGradFilterFunctor {
-public:
+ public:
   void operator()(const T* outputGrad,
                   const T* inputData,
                   int batchSize,

paddle/function/DepthwiseConvOpGpu.cu

@@ -199,7 +199,7 @@ __global__ void ConvolutionDepthwiseFilterBackward(const int num_i,
 
 template <class T>
 class DepthwiseConvFunctor<DEVICE_TYPE_GPU, T> {
-public:
+ public:
   void operator()(const T* inputData,
                   const T* filterData,
                   int batchSize,
@@ -249,7 +249,7 @@ public:
 
 template <class T>
 class DepthwiseConvGradInputFunctor<DEVICE_TYPE_GPU, T> {
-public:
+ public:
   void operator()(const T* outputGrad,
                   const T* filterData,
                   int batchSize,
@@ -300,7 +300,7 @@ public:
 
 template <class T>
 class DepthwiseConvGradFilterFunctor<DEVICE_TYPE_GPU, T> {
-public:
+ public:
   void operator()(const T* outputGrad,
                   const T* inputData,
                   int batchSize,

paddle/function/EigenThreadDevice.h

@@ -46,7 +46,7 @@ int GetCpuCount() { return 1; }
 #endif
 
 class EigenDeviceWarpper {
-public:  // NOLINT
+ public:  // NOLINT
 #if EIGEN_USE_THREADS
   static Eigen::ThreadPoolDevice* device() {
     const int num_cpus = GetCpuCount();

paddle/function/Function.h

@@ -29,7 +29,7 @@ namespace paddle {
  * The argument type of Function::init.
  */
 class FuncConfig {
-public:
+ public:
   template <typename T>
   T get(const std::string& key, Error* err = nullptr) const {
     try {
@@ -59,7 +59,7 @@ public:
     return *this;
   }
 
-protected:
+ protected:
   mutable std::unordered_map<std::string, any> valueMap_;
 };
 
@@ -77,7 +77,7 @@ protected:
  * in the BufferArgs life time.
  */
 class BufferArgs {
-public:
+ public:
   BufferArgs() {}
 
   ~BufferArgs() {
@@ -137,7 +137,7 @@ public:
 
   void addArg(SparseMatrixArg& arg) { args_.push_back(&arg); }
 
-private:
+ private:
   std::vector<BufferArg*> args_;
   // The BufferArg object is constructed and freed by BufferArgs.
   std::vector<BufferArg*> _args_;
@@ -163,7 +163,7 @@ private:
  * If Function has more than one output, each output can have different modes.
  */
 class FunctionBase {
-public:
+ public:
   virtual ~FunctionBase() {}
 
   virtual void init(const FuncConfig& config) {}
@@ -192,7 +192,7 @@ public:
 
   static ClassRegistrar<FunctionBase> funcRegistrar_;
 
-protected:
+ protected:
   // numInputs_ and numOutputs_ represents the maximum
   // input and output supported by Function.
   // Some functions are optimized for input and output,

paddle/function/FunctionTest.h

@@ -39,7 +39,7 @@ struct Allocator<DEVICE_TYPE_GPU> {
 // Copy argument1 to argument2
 template <DeviceType DType1, DeviceType DType2>
 class CopyArgument {
-public:
+ public:
   void operator()(const BufferArg& arg1, BufferArg& arg2) {
     CHECK_EQ(arg1.valueType(), arg2.valueType());
     CHECK_LE(arg1.shape().getElements(), arg2.shape().getElements());
@@ -95,7 +95,7 @@ public:
  */
 template <DeviceType DType1, DeviceType DType2>
 class Compare2Function {
-public:
+ public:
   typedef typename test::Allocator<DType1>::type Allocator1;
   typedef typename test::Allocator<DType2>::type Allocator2;
   typedef typename Tensor<real, DType1>::Vector Vector1;
@@ -305,7 +305,7 @@ public:
 
   std::shared_ptr<FunctionBase> getFunction2() const { return function2_; }
 
-protected:
+ protected:
   // only init cpu argument, gpu argument copy from cpu argument.
   void initArg(BufferArg& arg) {
     Vector1 vector(arg.shape().getElements(), (real*)arg.data());
@@ -381,7 +381,7 @@ protected:
     }
   }
 
-protected:
+ protected:
   std::shared_ptr<FunctionBase> function1_;
   std::shared_ptr<FunctionBase> function2_;
   std::vector<std::shared_ptr<Allocator1>> func1Memory_;
@@ -400,7 +400,7 @@ protected:
 
 class CpuGpuFuncCompare
     : public Compare2Function<DEVICE_TYPE_CPU, DEVICE_TYPE_GPU> {
-public:
+ public:
   CpuGpuFuncCompare(const std::string& name, const FuncConfig& config)
       : Compare2Function(name + "-CPU", name + "-GPU", config) {}