diff --git a/.clang-format b/.clang-format index aff93435f58c522f5ed1090aef2005f76e91cf31..8b5830627348c6bff12260b7d9adbd357f074718 100644 --- a/.clang-format +++ b/.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 diff --git a/paddle/api/GradientMachine.cpp b/paddle/api/GradientMachine.cpp index a3d6f0f080abcf1f45d9bc5fbdb39bb6b6ca1553..0d9ad30de9c1f3f8f58c856a748abdc050ff8740 100644 --- a/paddle/api/GradientMachine.cpp +++ b/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(callback)) {} @@ -105,7 +105,7 @@ public: delete p; } -private: + private: UpdateCallback& callback; }; diff --git a/paddle/api/PaddleAPI.h b/paddle/api/PaddleAPI.h index 67368d1a99d980b248789d24a2ea4f466255687a..7866122006a996cbe5201c661cab9c81aa82a219 100644 --- a/paddle/api/PaddleAPI.h +++ b/paddle/api/PaddleAPI.h @@ -59,9 +59,10 @@ class RangeError {}; /// Not support Error, such as access GPU memory directly, etc. class UnsupportError : public std::runtime_error { -public: - UnsupportError() : std::runtime_error(" "){}; - UnsupportError(const std::string& message) : std::runtime_error(message){}; + public: + UnsupportError() : std::runtime_error(" ") {} + explicit UnsupportError(const std::string& message) + : std::runtime_error(message) {} }; /// This type will map to python's list of float. @@ -105,7 +106,7 @@ class Matrix { DISABLE_COPY(Matrix); static Matrix* createByPaddleMatrixPtr(void* sharedPtr); -public: + public: virtual ~Matrix(); /** @@ -231,7 +232,7 @@ public: bool isGpu() const; -private: + private: void* getSharedPtr() const; MatrixPrivate* m; @@ -248,7 +249,7 @@ class Vector { void* getSharedPtr(); -public: + public: ~Vector(); /// Create Vector filled with zero. @@ -310,10 +311,10 @@ public: /// __len__ in python size_t getSize() const; -private: + private: VectorPrivate* m; -private: + private: friend class Parameter; friend class ParameterOptimizer; friend struct ParameterTraverseCallbackPrivate; @@ -325,7 +326,7 @@ class IVector { DISABLE_COPY(IVector); static IVector* createByPaddleVectorPtr(void* ptr); -public: + public: /// Create IVector filled with zero static IVector* createZero(size_t sz, bool useGpu = isUsingGpu()); @@ -389,7 +390,7 @@ public: /// This method will map to python __len__(); size_t getSize() const; -private: + private: void* getSharedPtr() const; friend class Arguments; @@ -400,11 +401,11 @@ struct ArgumentsPrivate; /// The Arguments is actual a std::vector in paddle. class Arguments { -private: + private: Arguments(); // Internal Create. DISABLE_COPY(Arguments); -public: + public: /** * Create a arguments with size. * Note that it can be zero. @@ -475,12 +476,12 @@ public: float sum() const; -private: + private: static Arguments* createByPaddleArgumentVector(void* ptr); static Arguments* createByPaddleArgument(const void* ptr); void* getInternalArgumentsPtr() const; -private: + private: ArgumentsPrivate* m; friend class Trainer; friend class GradientMachine; @@ -507,7 +508,7 @@ class ParameterConfig { static ParameterConfig* createParameterConfigFromParameterPtr(void* ptr); void* getRawPtr(); -public: + public: ~ParameterConfig(); /** @@ -515,10 +516,10 @@ public: */ std::string toProtoString() const; -private: + private: ParameterConfigPrivate* m; -private: + private: friend class Parameter; friend class ParameterOptimizer; friend struct ParameterTraverseCallbackPrivate; @@ -529,7 +530,7 @@ class OptimizationConfig { DISABLE_COPY(OptimizationConfig); OptimizationConfig(); -public: + public: static OptimizationConfig* createFromProtoString(const std::string& str); ~OptimizationConfig(); @@ -538,7 +539,7 @@ public: */ std::string toProtoString(); -private: + private: OptimizationConfigPrivate* m; friend class TrainerConfig; @@ -549,11 +550,11 @@ private: struct ParameterPrivate; class Parameter { -private: + private: Parameter(); DISABLE_COPY(Parameter); -public: + public: virtual ~Parameter(); /** @@ -580,11 +581,11 @@ public: size_t getSize() const; -private: + private: static Parameter* createFromRawPtr(void* ptr); static Parameter* createFromSharedPtr(void* ptr); -private: + private: ParameterPrivate* m; friend class UpdateCallbackWrapper; friend class GradientMachine; @@ -598,14 +599,14 @@ struct ModelConfigPrivate; * It is used by GradientMachine. */ class ModelConfig { -private: + private: ModelConfig(); DISABLE_COPY(ModelConfig); -public: + public: virtual ~ModelConfig(); -private: + private: ModelConfigPrivate* m; friend class TrainerConfig; friend struct TrainerConfigPrivate; @@ -619,11 +620,11 @@ struct TrainerConfigPrivate; * It is used by GradientMachine. */ class TrainerConfig { -private: + private: TrainerConfig(); DISABLE_COPY(TrainerConfig); -public: + public: virtual ~TrainerConfig(); static TrainerConfig* createFromTrainerConfigFile( @@ -634,7 +635,7 @@ public: OptimizationConfig* getOptimizationConfig() const; -private: + private: TrainerConfigPrivate* m; friend class Trainer; }; @@ -654,7 +655,7 @@ private: * @endcode */ class UpdateCallback { -public: + public: virtual ~UpdateCallback(); virtual void apply(Parameter* p); }; @@ -664,14 +665,14 @@ class ParameterTraverseCallback { DISABLE_COPY(ParameterTraverseCallback); ParameterTraverseCallback(); -public: + public: ~ParameterTraverseCallback(); void apply(const std::vector& vecs, const ParameterConfig& config, size_t sparseId); -private: + private: ParameterTraverseCallbackPrivate* m; friend class ParameterOptimizer; }; @@ -686,7 +687,7 @@ class ParameterOptimizer { DISABLE_COPY(ParameterOptimizer); ParameterOptimizer(); -public: + public: static ParameterOptimizer* create(OptimizationConfig* config); ~ParameterOptimizer(); @@ -710,7 +711,7 @@ public: ParameterTraverseCallback* needSpecialTraversal( const ParameterConfig& config) const; -private: + private: ParameterOptimizerPrivate* m; }; @@ -718,11 +719,11 @@ class SequenceGenerator; class Evaluator; struct GradientMachinePrivate; class GradientMachine { -private: + private: GradientMachine(); DISABLE_COPY(GradientMachine); -public: + public: virtual ~GradientMachine(); /** @@ -817,7 +818,7 @@ public: void eval(Evaluator* evaluator); -private: + private: GradientMachinePrivate* m; static GradientMachine* createFromPaddleModelPtr( @@ -833,10 +834,10 @@ private: struct ParameterUpdaterPrivate; class ParameterUpdater { -private: + private: ParameterUpdater(); -public: + public: static ParameterUpdater* createLocalUpdater(OptimizationConfig* config); static ParameterUpdater* createRemoteUpdater(OptimizationConfig* config, int passCount, @@ -911,17 +912,17 @@ public: */ void catchUpWith(); -private: + private: ParameterUpdaterPrivate* m; }; struct EvaluatorPrivate; class Evaluator { -private: + private: Evaluator(); DISABLE_COPY(Evaluator); -public: + public: ~Evaluator(); /** @@ -945,7 +946,7 @@ public: double getValue(const std::string name) const; -private: + private: EvaluatorPrivate* m; friend class GradientMachine; @@ -953,13 +954,13 @@ private: struct TrainerPrivate; class Trainer { -private: + private: TrainerPrivate* m; Trainer(); Trainer(TrainerConfig* optConfig, GradientMachine* gm); DISABLE_COPY(Trainer); -public: + public: virtual ~Trainer(); /// Create A Trainer By TrainerConfig. using paddle command line. @@ -1002,7 +1003,7 @@ public: /// the N-Best results generated from one input sequence. class ISequenceResults { -public: + public: virtual ~ISequenceResults(); /// Number of result. @@ -1026,7 +1027,7 @@ class SequenceGenerator { DISABLE_COPY(SequenceGenerator); SequenceGenerator(); -public: + public: virtual ~SequenceGenerator(); /** @@ -1044,10 +1045,10 @@ public: void setMaxLength(size_t maxlength); void setBeamSize(size_t beamSize); -private: + private: static SequenceGenerator* createByGradientMachineSharedPtr(void* ptr); friend class GradientMachine; -private: + private: SequenceGeneratorPrivate* m; }; diff --git a/paddle/api/SequenceGenerator.cpp b/paddle/api/SequenceGenerator.cpp index 1b30aec8f6b6b73764886a7c7274be67851e4815..1446c3084238859a759669f3a32c7efde67dcc2b 100644 --- a/paddle/api/SequenceGenerator.cpp +++ b/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>& path, const std::shared_ptr>& dict) : path_(path), dict_(dict) {} @@ -196,7 +196,7 @@ public: } } -private: + private: std::shared_ptr> path_; std::shared_ptr> dict_; }; diff --git a/paddle/capi/gradient_machine.cpp b/paddle/capi/gradient_machine.cpp index ea9aab00e3d05f1e2ef0c91eab93b67e0a3d5f37..8c3f504e5a2d807c0cc664af486ebab4a82ddec3 100644 --- a/paddle/capi/gradient_machine.cpp +++ b/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) {} }; diff --git a/paddle/contrib/inference/paddle_inference_api.h b/paddle/contrib/inference/paddle_inference_api.h index 9ac8ebdef8151f2a144b479fa258b8bc830fc2e9..f804d9b28697a6703d63d9a640c4ec337effaba6 100644 --- a/paddle/contrib/inference/paddle_inference_api.h +++ b/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 Clone() = 0; + virtual bool InitShared() { return false; } // Destroy the Predictor. virtual ~PaddlePredictor() {} diff --git a/paddle/contrib/inference/paddle_inference_api_impl.cc b/paddle/contrib/inference/paddle_inference_api_impl.cc index ecca16d3f82bbeee6858883a0f9e577a479f9d06..8fb650a7330ef4e28fb824a8a4755c984460ac36 100644 --- a/paddle/contrib/inference/paddle_inference_api_impl.cc +++ b/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 &inputs, std::unique_ptr PaddlePredictorImpl::Clone() { VLOG(3) << "Predictor::clone"; - std::unique_ptr cls(new PaddlePredictorImpl(config_)); - if (!cls->InitShared(this)) { + std::unique_ptr cls(new PaddlePredictorImpl(config_)); + if (!cls->InitShared()) { LOG(ERROR) << "fail to call InitShared"; return nullptr; } @@ -144,7 +144,7 @@ std::unique_ptr 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) { diff --git a/paddle/contrib/inference/paddle_inference_api_impl.h b/paddle/contrib/inference/paddle_inference_api_impl.h index 831abce5da58f90b38e27b5638e953de5167647a..9a333a872c14c8134409373580d332a41ae81f7f 100644 --- a/paddle/contrib/inference/paddle_inference_api_impl.h +++ b/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 &input_datas, std::vector *feeds); bool GetFetch(const std::vector &fetchs, diff --git a/paddle/contrib/inference/test_paddle_inference_api.cc b/paddle/contrib/inference/test_paddle_inference_api.cc index a19173087649e8493b8c72e758456cc5b8970e23..bc7faab6e208a66d7a56e41a56bd743c7644eea2 100644 --- a/paddle/contrib/inference/test_paddle_inference_api.cc +++ b/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; } diff --git a/paddle/cuda/include/hl_activation_functions.h b/paddle/cuda/include/hl_activation_functions.h index 29ec248420058db08bd1932f702d26074d49f38c..66a69db545b541409f895820ad621a2a9a684e20 100644 --- a/paddle/cuda/include/hl_activation_functions.h +++ b/paddle/cuda/include/hl_activation_functions.h @@ -31,7 +31,7 @@ namespace hppl { */ template class Active { -public: + public: typedef T (*forward)(T); typedef T (*backward)(T, T); }; diff --git a/paddle/cuda/include/hl_tensor_ops.h b/paddle/cuda/include/hl_tensor_ops.h index 85a022ff5e26daab97be52b7ea9814c6b8078561..bc5e5da53d5c6ac2bae3b0067f46e39accd1b9d8 100644 --- a/paddle/cuda/include/hl_tensor_ops.h +++ b/paddle/cuda/include/hl_tensor_ops.h @@ -23,128 +23,128 @@ namespace unary { template class add_scale { -private: + private: const T p; -public: + public: INLINE add_scale(const T s) : p(s) {} INLINE T operator()(const T a) const { return a + p; } }; template class sub_scale { -private: + private: const T p; -public: + public: INLINE sub_scale(const T s) : p(s) {} INLINE T operator()(const T a) const { return a - p; } }; template class mul_scale { -private: + private: const T p; -public: + public: INLINE mul_scale(const T s) : p(s) {} INLINE T operator()(const T a) const { return a * p; } }; template class div_scale { -private: + private: const T p; -public: + public: INLINE div_scale(const T s) : p(s) {} INLINE T operator()(const T a) const { return a / p; } }; template class neg { -public: + public: INLINE T operator()(const T a) const { return -a; } }; template class exp_op { -public: + public: INLINE T operator()(const T a) const { return std::exp(a); } }; template class log_op { -public: + public: INLINE T operator()(const T a) const { return std::log(a); } }; template class sqrt_op { -public: + public: INLINE T operator()(const T a) const { return std::sqrt(a); } }; template class square { -public: + public: INLINE T operator()(const T a) const { return a * a; } }; template class reciprocal { -public: + public: INLINE T operator()(const T a) const { return T(1) / a; } }; template class abs { -public: + public: INLINE T operator()(const T a) const { return a > 0 ? a : -a; } }; template class sign { -public: + public: INLINE T operator()(const T a) const { return (a > 0) - (a < 0); } }; template class min { -private: + private: const T p; -public: + public: INLINE min(const T s) : p(s) {} INLINE T operator()(const T a) const { return a > p ? p : a; } }; template class max { -private: + private: const T p; -public: + public: INLINE max(const T s) : p(s) {} INLINE T operator()(const T a) const { return a < p ? p : a; } }; template class pow_op { -private: + private: const T p; -public: + public: INLINE pow_op(const T s) : p(s) {} INLINE T operator()(const T a) const { return std::pow(a, p); } }; template class constant { -private: + private: const T p; -public: + public: INLINE constant(const T s) : p(s) {} INLINE T operator()(int i) const { return p; } INLINE T operator()(int i, int j) const { return p; } @@ -152,80 +152,80 @@ public: template class cmp_eq { -private: + private: const T p; -public: + public: INLINE cmp_eq(const T s) : p(s) {} INLINE bool operator()(const T a) const { return a == p; } }; template class cmp_ne { -private: + private: const T p; -public: + public: INLINE cmp_ne(const T s) : p(s) {} INLINE bool operator()(const T a) const { return a != p; } }; template class cmp_le { -private: + private: const T p; -public: + public: INLINE cmp_le(const T s) : p(s) {} INLINE bool operator()(const T a) const { return a <= p; } }; template class cmp_lt { -private: + private: const T p; -public: + public: INLINE cmp_lt(const T s) : p(s) {} INLINE bool operator()(const T a) const { return a < p; } }; template class cmp_ge { -private: + private: const T p; -public: + public: INLINE cmp_ge(const T s) : p(s) {} INLINE bool operator()(const T a) const { return a >= p; } }; template class cmp_gt { -private: + private: const T p; -public: + public: INLINE cmp_gt(const T s) : p(s) {} INLINE bool operator()(const T a) const { return a > p; } }; template class and_op { -private: + private: const T p; -public: + public: INLINE and_op(const T s) : p(s) {} INLINE bool operator()(const T a) const { return a && p; } }; template class or_op { -private: + private: const T p; -public: + public: INLINE or_op(const T s) : p(s) {} INLINE bool operator()(const T a) const { return a || p; } }; @@ -235,96 +235,96 @@ public: namespace binary { template class add { -public: + public: INLINE T operator()(const T a, const T b) const { return a + b; } }; template class add_scale { -private: + private: const T p1; const T p2; -public: + public: INLINE add_scale(const T s1, const T s2) : p1(s1), p2(s2) {} INLINE T operator()(const T a, const T b) const { return p1 * a + p2 * b; } }; template class sub { -public: + public: INLINE T operator()(const T a, const T b) const { return a - b; } }; template class mul { -public: + public: INLINE T operator()(const T a, const T b) const { return a * b; } }; template class div { -public: + public: INLINE T operator()(const T a, const T b) const { return a / b; } }; template class cmp_eq { -public: + public: INLINE bool operator()(const T a, const T b) const { return a == b; } }; template class cmp_ne { -public: + public: INLINE bool operator()(const T a, const T b) const { return a != b; } }; template class cmp_le { -public: + public: INLINE bool operator()(const T a, const T b) const { return a <= b; } }; template class cmp_lt { -public: + public: INLINE bool operator()(const T a, const T b) const { return a < b; } }; template class cmp_ge { -public: + public: INLINE bool operator()(const T a, const T b) const { return a >= b; } }; template class cmp_gt { -public: + public: INLINE bool operator()(const T a, const T b) const { return a > b; } }; template class and_op { -public: + public: INLINE bool operator()(const T a, const T b) const { return a && b; } }; template class or_op { -public: + public: INLINE bool operator()(const T a, const T b) const { return a || b; } }; template class min { -public: + public: INLINE T operator()(const T a, const T b) const { return a > b ? b : a; } }; template class max { -public: + public: INLINE T operator()(const T a, const T b) const { return a < b ? b : a; } }; @@ -332,7 +332,7 @@ public: #ifndef PADDLE_TYPE_DOUBLE template <> class add<__m128> { -public: + public: INLINE __m128 operator()(const __m128 a, const __m128 b) const { return _mm_add_ps(a, b); } @@ -340,11 +340,11 @@ public: template <> class add_scale<__m128> { -private: + private: const __m128 p1; const __m128 p2; -public: + public: INLINE add_scale(const __m128 s1, const __m128 s2) : p1(s1), p2(s2) {} INLINE __m128 operator()(const __m128 a, const __m128 b) const { return _mm_add_ps(_mm_mul_ps(p1, a), _mm_mul_ps(p2, b)); @@ -353,7 +353,7 @@ public: template <> class sub<__m128> { -public: + public: INLINE __m128 operator()(const __m128 a, const __m128 b) const { return _mm_sub_ps(a, b); } @@ -361,7 +361,7 @@ public: template <> class mul<__m128> { -public: + public: INLINE __m128 operator()(const __m128 a, const __m128 b) const { return _mm_mul_ps(a, b); } @@ -369,7 +369,7 @@ public: template <> class div<__m128> { -public: + public: INLINE __m128 operator()(const __m128 a, const __m128 b) const { return _mm_div_ps(a, b); } @@ -377,7 +377,7 @@ public: template <> class min<__m128> { -public: + public: INLINE __m128 operator()(const __m128 a, const __m128 b) const { return _mm_min_ps(a, b); } @@ -385,7 +385,7 @@ public: template <> class max<__m128> { -public: + public: INLINE __m128 operator()(const __m128 a, const __m128 b) const { return _mm_max_ps(a, b); } @@ -393,7 +393,7 @@ public: #else template <> class add<__m128d> { -public: + public: INLINE __m128d operator()(const __m128d a, const __m128d b) const { return _mm_add_pd(a, b); } @@ -401,11 +401,11 @@ public: template <> class add_scale<__m128d> { -private: + private: const __m128d p1; const __m128d p2; -public: + public: INLINE add_scale(const __m128d s1, const __m128d s2) : p1(s1), p2(s2) {} INLINE __m128d operator()(const __m128d a, const __m128d b) const { return _mm_add_pd(_mm_mul_pd(p1, a), _mm_mul_pd(p2, b)); @@ -414,7 +414,7 @@ public: template <> class sub<__m128d> { -public: + public: INLINE __m128d operator()(const __m128d a, const __m128d b) const { return _mm_sub_pd(a, b); } @@ -422,7 +422,7 @@ public: template <> class mul<__m128d> { -public: + public: INLINE __m128d operator()(const __m128d a, const __m128d b) const { return _mm_mul_pd(a, b); } @@ -430,7 +430,7 @@ public: template <> class div<__m128d> { -public: + public: INLINE __m128d operator()(const __m128d a, const __m128d b) const { return _mm_div_pd(a, b); } @@ -438,7 +438,7 @@ public: template <> class min<__m128d> { -public: + public: INLINE __m128d operator()(const __m128d a, const __m128d b) const { return _mm_min_pd(a, b); } @@ -446,7 +446,7 @@ public: template <> class max<__m128d> { -public: + public: INLINE __m128d operator()(const __m128d a, const __m128d b) const { return _mm_max_pd(a, b); } @@ -458,7 +458,7 @@ public: #ifndef PADDLE_TYPE_DOUBLE template <> class add { -public: + public: INLINE float32x4_t operator()(const float32x4_t a, const float32x4_t b) const { return vaddq_f32(a, b); @@ -467,11 +467,11 @@ public: template <> class add_scale { -private: + private: const float32x4_t p1; const float32x4_t p2; -public: + public: INLINE add_scale(const float32x4_t s1, const float32x4_t s2) : p1(s1), p2(s2) {} INLINE float32x4_t operator()(const float32x4_t a, @@ -482,7 +482,7 @@ public: template <> class sub { -public: + public: INLINE float32x4_t operator()(const float32x4_t a, const float32x4_t b) const { return vsubq_f32(a, b); @@ -491,7 +491,7 @@ public: template <> class mul { -public: + public: INLINE float32x4_t operator()(const float32x4_t a, const float32x4_t b) const { return vmulq_f32(a, b); @@ -500,7 +500,7 @@ public: template <> class div { -public: + public: INLINE float32x4_t operator()(const float32x4_t a, const float32x4_t b) const { float32x4_t tmp = vrecpeq_f32(b); @@ -510,7 +510,7 @@ public: template <> class min { -public: + public: INLINE float32x4_t operator()(const float32x4_t a, const float32x4_t b) const { return vminq_f32(a, b); @@ -519,7 +519,7 @@ public: template <> class max { -public: + public: INLINE float32x4_t operator()(const float32x4_t a, const float32x4_t b) const { return vmaxq_f32(a, b); diff --git a/paddle/cuda/src/hl_cuda_lstm.cu b/paddle/cuda/src/hl_cuda_lstm.cu index e30fcddffdf99417a4b9b811a0b0cb0a12e79b99..b8c4e433a118fb1c5af753751f91c34543b1114c 100644 --- a/paddle/cuda/src/hl_cuda_lstm.cu +++ b/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 diff --git a/paddle/function/BlockExpandOp.cpp b/paddle/function/BlockExpandOp.cpp index aa53853e08716ff0dd8dce7c73766d9543bed2b9..f01f89a7277acc5fe494b92a3e7ca3ca18498c97 100644 --- a/paddle/function/BlockExpandOp.cpp +++ b/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>("strides"); @@ -81,7 +81,7 @@ public: (size_t)blockW()}); } -protected: + protected: std::vector strides_; std::vector paddings_; std::vector blocks_; @@ -101,7 +101,7 @@ protected: template class BlockExpandForward : public BlockExpandFunction { -public: + public: void init(const FuncConfig& config) override { BlockExpandFunction::init(config); } @@ -149,7 +149,7 @@ public: template class BlockExpandBackward : public BlockExpandFunction { -public: + public: void init(const FuncConfig& config) override { BlockExpandFunction::init(config); } diff --git a/paddle/function/BufferArg.h b/paddle/function/BufferArg.h index 89ee09837db69d79bbd678312f02f6dc87e8067c..6de8c94e778c8d1439b2a2aa3c581a5a3cf70261 100644 --- a/paddle/function/BufferArg.h +++ b/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_; diff --git a/paddle/function/ContextProjectionOp.cpp b/paddle/function/ContextProjectionOp.cpp index 904b0958e6f2c1b8fb8cf56f3cd7d07ad8e24f19..1187842452460ac3fd71f48150fab6467f93dc6c 100644 --- a/paddle/function/ContextProjectionOp.cpp +++ b/paddle/function/ContextProjectionOp.cpp @@ -100,7 +100,7 @@ void ContextProjectionForward(CpuMatrix& out_mat, */ template class ContextProjectionForwardFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { context_length_ = config.get("context_length"); context_start_ = config.get("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(const CpuMatrix& out_grad_mat, */ template class ContextProjectionBackwardFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { context_length_ = config.get("context_length"); context_start_ = config.get("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 class ContextProjectionBackwardDataFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { context_length_ = config.get("context_length"); context_start_ = config.get("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 class ContextProjectionBackwardWeightFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { context_length_ = config.get("context_length"); context_start_ = config.get("context_start"); @@ -382,7 +382,7 @@ public: begin_pad_); } -private: + private: size_t context_length_; int context_start_; size_t begin_pad_; diff --git a/paddle/function/ConvOp.h b/paddle/function/ConvOp.h index 7d23d0079c8f62b2c8912dfcb9f191c622a60bc9..2d8437bcfe60d1d81897f1c4be1cbfecb5b27fe0 100644 --- a/paddle/function/ConvOp.h +++ b/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>("strides"); @@ -101,7 +101,7 @@ public: } } -protected: + protected: size_t getFilterHeight(const TensorShape& filter) const { return filter[filter.ndims() - 2]; } diff --git a/paddle/function/CosSimOp.cpp b/paddle/function/CosSimOp.cpp index 81bccc1a9c7d614763a10e3838271b57eef2c603..2c25e1af44965d30591faeccc9a181e36c7e0a0f 100644 --- a/paddle/function/CosSimOp.cpp +++ b/paddle/function/CosSimOp.cpp @@ -97,7 +97,7 @@ class CosSimForwardFunc : public FunctionBase { CosSimForward(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_; }; diff --git a/paddle/function/CropOp.cpp b/paddle/function/CropOp.cpp index 7aa527d21615e19257bd003d0563b5e26b2fcb2f..5bd98910fe838751935f8ef2387ce96e755c6df1 100644 --- a/paddle/function/CropOp.cpp +++ b/paddle/function/CropOp.cpp @@ -112,7 +112,7 @@ void CropGrad(const real* inGrad, */ template 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 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_; }; diff --git a/paddle/function/CrossMapNormalOp.cpp b/paddle/function/CrossMapNormalOp.cpp index 75c0fc2a3d047a9162d49809a717629f2270872d..7ff9227e5c2702d9d5334db501730b57ec10bfe3 100644 --- a/paddle/function/CrossMapNormalOp.cpp +++ b/paddle/function/CrossMapNormalOp.cpp @@ -160,7 +160,7 @@ void CrossMapNormalGrad(real* inputsGrad, */ template class CrossMapNormalFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { // function arguments size_ = config.get("size"); @@ -220,7 +220,7 @@ public: return ops; } -private: + private: size_t size_; real scale_; real pow_; @@ -260,7 +260,7 @@ private: */ template class CrossMapNormalGradFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { // function arguments size_ = config.get("size"); @@ -328,7 +328,7 @@ public: return ops; } -private: + private: size_t size_; real scale_; real pow_; diff --git a/paddle/function/DepthwiseConvOp.cpp b/paddle/function/DepthwiseConvOp.cpp index 46651345b45e4ced9a3ef3373af437d939a66716..958034e08e60c9a63d1c480bde7c84b760205ae4 100644 --- a/paddle/function/DepthwiseConvOp.cpp +++ b/paddle/function/DepthwiseConvOp.cpp @@ -19,7 +19,7 @@ namespace paddle { template class DepthwiseConvFunctor { -public: + public: void operator()(const T* inputData, const T* filterData, int batchSize, @@ -43,7 +43,7 @@ public: template class DepthwiseConvGradInputFunctor { -public: + public: void operator()(const T* outputGrad, const T* filterData, int batchSize, @@ -66,7 +66,7 @@ public: template class DepthwiseConvGradFilterFunctor { -public: + public: void operator()(const T* outputGrad, const T* inputData, int batchSize, @@ -93,7 +93,7 @@ public: */ template class DepthwiseConvFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } @@ -156,7 +156,7 @@ public: */ template class DepthwiseConvGradInputFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } @@ -220,7 +220,7 @@ public: */ template class DepthwiseConvGradFilterFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } diff --git a/paddle/function/DepthwiseConvOp.h b/paddle/function/DepthwiseConvOp.h index 6700747314fa8377828dab0c436eb4b2053f46f6..7837edd1c071980592b1cf36ecb69a3b7c12cc5e 100644 --- a/paddle/function/DepthwiseConvOp.h +++ b/paddle/function/DepthwiseConvOp.h @@ -44,7 +44,7 @@ namespace paddle { */ template class DepthwiseConvFunctor { -public: + public: void operator()(const T* inputData, const T* filterData, int batchSize, @@ -89,7 +89,7 @@ public: */ template class DepthwiseConvGradInputFunctor { -public: + public: void operator()(const T* outputGrad, const T* filterData, int batchSize, @@ -135,7 +135,7 @@ public: */ template class DepthwiseConvGradFilterFunctor { -public: + public: void operator()(const T* outputGrad, const T* inputData, int batchSize, diff --git a/paddle/function/DepthwiseConvOpGpu.cu b/paddle/function/DepthwiseConvOpGpu.cu index cd1d55a416c84c6327226ffaae4d5d9d5be81038..2c0e71b19b22abac25d273d8bbeddc330e67f8b0 100644 --- a/paddle/function/DepthwiseConvOpGpu.cu +++ b/paddle/function/DepthwiseConvOpGpu.cu @@ -199,7 +199,7 @@ __global__ void ConvolutionDepthwiseFilterBackward(const int num_i, template class DepthwiseConvFunctor { -public: + public: void operator()(const T* inputData, const T* filterData, int batchSize, @@ -249,7 +249,7 @@ public: template class DepthwiseConvGradInputFunctor { -public: + public: void operator()(const T* outputGrad, const T* filterData, int batchSize, @@ -300,7 +300,7 @@ public: template class DepthwiseConvGradFilterFunctor { -public: + public: void operator()(const T* outputGrad, const T* inputData, int batchSize, diff --git a/paddle/function/EigenThreadDevice.h b/paddle/function/EigenThreadDevice.h index 74269aa664a711c905e12a61958c9ab01e2340c0..eb92251c827a26d55ca021c4418182bae28dd6a5 100644 --- a/paddle/function/EigenThreadDevice.h +++ b/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(); diff --git a/paddle/function/Function.h b/paddle/function/Function.h index 01288ef92e7b59d7958e6e23daf641b30a60eed1..a6c14ef29b760faa393c37bd2357824a061c7b38 100644 --- a/paddle/function/Function.h +++ b/paddle/function/Function.h @@ -29,7 +29,7 @@ namespace paddle { * The argument type of Function::init. */ class FuncConfig { -public: + public: template T get(const std::string& key, Error* err = nullptr) const { try { @@ -59,7 +59,7 @@ public: return *this; } -protected: + protected: mutable std::unordered_map 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 args_; // The BufferArg object is constructed and freed by BufferArgs. std::vector _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 funcRegistrar_; -protected: + protected: // numInputs_ and numOutputs_ represents the maximum // input and output supported by Function. // Some functions are optimized for input and output, diff --git a/paddle/function/FunctionTest.h b/paddle/function/FunctionTest.h index 56c3537b6a96c8042d172f8aca2163fa18c813c1..14003d2c885c8f846f9445ad8844869c9112816e 100644 --- a/paddle/function/FunctionTest.h +++ b/paddle/function/FunctionTest.h @@ -39,7 +39,7 @@ struct Allocator { // Copy argument1 to argument2 template 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 class Compare2Function { -public: + public: typedef typename test::Allocator::type Allocator1; typedef typename test::Allocator::type Allocator2; typedef typename Tensor::Vector Vector1; @@ -305,7 +305,7 @@ public: std::shared_ptr 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 function1_; std::shared_ptr function2_; std::vector> func1Memory_; @@ -400,7 +400,7 @@ protected: class CpuGpuFuncCompare : public Compare2Function { -public: + public: CpuGpuFuncCompare(const std::string& name, const FuncConfig& config) : Compare2Function(name + "-CPU", name + "-GPU", config) {} diff --git a/paddle/function/GemmConvOp.cpp b/paddle/function/GemmConvOp.cpp index 2b7c6f9eab223c8d6a2107ff4605ac6e60295f7d..5b023e2c10e5040a28660d555efceb0e26b40d49 100644 --- a/paddle/function/GemmConvOp.cpp +++ b/paddle/function/GemmConvOp.cpp @@ -24,7 +24,7 @@ namespace paddle { */ template class GemmConvFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } @@ -136,7 +136,7 @@ public: */ template class GemmConvMobileFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } @@ -297,7 +297,7 @@ public: */ template class GemmConvGradInputFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } @@ -404,7 +404,7 @@ public: */ template class GemmConvGradFilterFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } diff --git a/paddle/function/Im2Col.h b/paddle/function/Im2Col.h index 6a0778700037c142d62fdb99667403ade806f7c1..e0ce6918a2a5324a396ade734945cf426b81ab56 100644 --- a/paddle/function/Im2Col.h +++ b/paddle/function/Im2Col.h @@ -70,7 +70,7 @@ enum ColFormat { kCFO = 0, kOCF = 1 }; */ template class Im2ColFunctor { -public: + public: void operator()(const T* imData, const TensorShape& imShape, T* colData, @@ -85,7 +85,7 @@ public: template class Col2ImFunctor { -public: + public: void operator()(T* imData, const TensorShape& imShape, const T* colData, @@ -100,7 +100,7 @@ public: template class Im2ColMobileFunctor { -public: + public: void operator()(const T* imData, const TensorShape& imShape, T* colData, diff --git a/paddle/function/Im2ColOp.cpp b/paddle/function/Im2ColOp.cpp index ad2aed8f3c237cf9c0f7f0dcc4900cac807e25ea..55a3ff98db63ede96094a3d3fdeedf03b573294f 100644 --- a/paddle/function/Im2ColOp.cpp +++ b/paddle/function/Im2ColOp.cpp @@ -23,7 +23,7 @@ namespace paddle { */ template class Im2ColFunctor { -public: + public: void operator()(const T* imData, const TensorShape& imShape, T* colData, @@ -75,7 +75,7 @@ public: */ template class Col2ImFunctor { -public: + public: void operator()(T* imData, const TensorShape& imShape, const T* colData, @@ -130,7 +130,7 @@ template class Col2ImFunctor; */ template class Im2ColFunctor { -public: + public: void operator()(const T* imData, const TensorShape& imShape, T* colData, @@ -188,7 +188,7 @@ public: */ template class Col2ImFunctor { -public: + public: void operator()(T* imData, const TensorShape& imShape, const T* colData, diff --git a/paddle/function/Im2ColOpGpu.cu b/paddle/function/Im2ColOpGpu.cu index a944a0ee687fefc5e002096b9c5b869495554167..96dd8f528eaa38f9d174ab7c2a5ea5eb96e2a060 100644 --- a/paddle/function/Im2ColOpGpu.cu +++ b/paddle/function/Im2ColOpGpu.cu @@ -71,7 +71,7 @@ __global__ void im2col(const T* data_im, */ template class Im2ColFunctor { -public: + public: void operator()(const T* imData, const TensorShape& imShape, T* colData, @@ -184,7 +184,7 @@ __global__ void col2im(size_t n, */ template class Col2ImFunctor { -public: + public: void operator()(T* imData, const TensorShape& imShape, const T* colData, @@ -292,7 +292,7 @@ __global__ void im2colOCF(const T* imData, */ template class Im2ColFunctor { -public: + public: void operator()(const T* imData, const TensorShape& imShape, T* colData, @@ -399,7 +399,7 @@ __global__ void col2imOCF(T* imData, */ template class Col2ImFunctor { -public: + public: void operator()(T* imData, const TensorShape& imShape, const T* colData, diff --git a/paddle/function/MulOp.cpp b/paddle/function/MulOp.cpp index 90cd4a2b6d1bfb2529e1c966cf7a1fb904a844d7..7bf36c8050a8c33d836ce98dc7f3cf6d3de38d55 100644 --- a/paddle/function/MulOp.cpp +++ b/paddle/function/MulOp.cpp @@ -240,7 +240,7 @@ void MulOp(CpuMatrix& out, */ template class MulFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { aTrans_ = config.get("aTrans"); bTrans_ = config.get("bTrans"); @@ -335,7 +335,7 @@ public: } } -private: + private: bool aTrans_; bool bTrans_; }; diff --git a/paddle/function/NaiveConvOp.cpp b/paddle/function/NaiveConvOp.cpp index 22d3b33d0f4a730691234c6c742978abd72294a6..99c8b81acbbb16a91bc0faa1c7f2873fa94ab108 100644 --- a/paddle/function/NaiveConvOp.cpp +++ b/paddle/function/NaiveConvOp.cpp @@ -24,7 +24,7 @@ namespace paddle { */ template class NaiveConvFunctor { -public: + public: void operator()(const T* inputData, size_t batchSize, size_t inputChannels, @@ -85,7 +85,7 @@ public: template class NaiveConvFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } diff --git a/paddle/function/PadOp.cpp b/paddle/function/PadOp.cpp index db6dd518ca5df9d852e545b37f61f1141c81f57c..5d7515e8c053439b95fb18de3c8ffe70705600a3 100644 --- a/paddle/function/PadOp.cpp +++ b/paddle/function/PadOp.cpp @@ -132,7 +132,7 @@ static inline PadConf castToPadConf(const FuncConfig& conf) { template class PadFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { pad_ = castToPadConf(config); } void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { @@ -157,7 +157,7 @@ public: pad_); } -private: + private: PadConf pad_; }; @@ -173,7 +173,7 @@ private: template class PadGradFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { pad_ = castToPadConf(config); } void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { @@ -201,7 +201,7 @@ public: pad_); } -private: + private: PadConf pad_; }; diff --git a/paddle/function/RowConvOp.cpp b/paddle/function/RowConvOp.cpp index 925860346e1a53065b0fe4ccbd26853afc8898a1..129e9334582fad011c259e8ab8268b00a7fab7b6 100644 --- a/paddle/function/RowConvOp.cpp +++ b/paddle/function/RowConvOp.cpp @@ -129,7 +129,7 @@ void RowConvGrad(const CpuMatrix& outG, template class RowConvFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override {} void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { @@ -176,7 +176,7 @@ public: template class RowConvGradFunc : public FunctionBase { // TODO(qingqing): split into RowConvDataFunc and RowConvWeightFunc -public: + public: void init(const FuncConfig& config) override {} void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { diff --git a/paddle/function/ScaleSubRegionOp.cpp b/paddle/function/ScaleSubRegionOp.cpp index 6ed6eb2dba477722664ca4a29f4689114f368846..9a06ef2a96f25b5b7326049df2a708637f319561 100644 --- a/paddle/function/ScaleSubRegionOp.cpp +++ b/paddle/function/ScaleSubRegionOp.cpp @@ -92,7 +92,7 @@ void ScaleSubRegionGrad(const real* inGrad, */ template class ScaleSubRegionFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { conf_ = config; } void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { @@ -109,7 +109,7 @@ public: conf_); } -private: + private: FuncConfig conf_; }; @@ -124,7 +124,7 @@ private: template class ScaleSubRegionGradFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override { conf_ = config; } void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { @@ -141,7 +141,7 @@ public: conf_); } -private: + private: FuncConfig conf_; }; diff --git a/paddle/function/SwitchOp.cpp b/paddle/function/SwitchOp.cpp index 50e1d6c04c54fed5b847aa10dbb253f00cfa42d4..750fb6bf28baf050b1f9f965a1a9b315363e5645 100644 --- a/paddle/function/SwitchOp.cpp +++ b/paddle/function/SwitchOp.cpp @@ -75,7 +75,7 @@ void NHWC2NCHW(real* outputs, */ template class NCHW2NHWCFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override {} void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { @@ -108,7 +108,7 @@ public: */ template class NHWC2NCHWFunc : public FunctionBase { -public: + public: void init(const FuncConfig& config) override {} void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { diff --git a/paddle/function/TensorShape.h b/paddle/function/TensorShape.h index 02d38c32c007325a928910d136d48214ba5f6bc3..d4d1eae3960c333a2a7dc6099ae7a68677fdcd5f 100644 --- a/paddle/function/TensorShape.h +++ b/paddle/function/TensorShape.h @@ -22,7 +22,7 @@ namespace paddle { * TensorShape used to represent shape of normal tensor. */ class TensorShape { -public: + public: TensorShape() : ndims_(0), nelements_(0) { initDims(0); } TensorShape(size_t ndims) : ndims_(ndims), nelements_(1) { initDims(ndims); }; @@ -80,7 +80,7 @@ public: bool operator!=(const TensorShape& t) const { return !(*this == t); } -private: + private: // compute number of elements void numElements() { nelements_ = 1; diff --git a/paddle/function/neon/NeonDepthwiseConv.cpp b/paddle/function/neon/NeonDepthwiseConv.cpp index d3298c753853ca6d212a619cf8d0bd9356a8dbd7..85bc95bb88ca606e289fb6dad4946a77faf3d5fb 100644 --- a/paddle/function/neon/NeonDepthwiseConv.cpp +++ b/paddle/function/neon/NeonDepthwiseConv.cpp @@ -21,7 +21,7 @@ namespace paddle { template class NeonDepthwiseConvFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } diff --git a/paddle/function/neon/NeonDepthwiseConvTranspose.cpp b/paddle/function/neon/NeonDepthwiseConvTranspose.cpp index d443d3fa4902f998230651c5c64355d93c4c4f6a..1fc5daf6078bbd5b4506ff2e0832e2cc3ec48fe3 100644 --- a/paddle/function/neon/NeonDepthwiseConvTranspose.cpp +++ b/paddle/function/neon/NeonDepthwiseConvTranspose.cpp @@ -21,7 +21,7 @@ namespace paddle { template class NeonDepthwiseConvTransposeFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); } diff --git a/paddle/function/nnpack/NNPACKConvOp.cpp b/paddle/function/nnpack/NNPACKConvOp.cpp index 3cdba4f2ed0dad42035fe2d0de87ad5aeeef20ca..48c997b50d8c73b25c58801c30e597c9d1f3232a 100644 --- a/paddle/function/nnpack/NNPACKConvOp.cpp +++ b/paddle/function/nnpack/NNPACKConvOp.cpp @@ -46,7 +46,7 @@ nnp_convolution_algorithm get_nnp_convolution_algorithm( template class NNPACKConvFunction : public ConvFunctionBase { -public: + public: void init(const FuncConfig& config) override { ConvFunctionBase::init(config); algorithm_ = get_nnp_convolution_algorithm(config.get("algo")); @@ -231,7 +231,7 @@ public: } } -private: + private: nnp_convolution_algorithm algorithm_; nnp_convolution_transform_strategy transform_strategy_; void* workspaceBuffer_; diff --git a/paddle/gserver/activations/ActivationFunction.cpp b/paddle/gserver/activations/ActivationFunction.cpp index 8d8f01234fe3859989e44fe6147105fb72b832ff..71c238fbfe9f32f3764601ebb441336931f8ef5f 100644 --- a/paddle/gserver/activations/ActivationFunction.cpp +++ b/paddle/gserver/activations/ActivationFunction.cpp @@ -44,10 +44,10 @@ static ClassRegistrar gActivationRegistrar; */ #define BEGIN_DEFINE_ACTIVATION(ACTIVATION_NAME) \ class ACTIVATION_CLASS_NAME(ACTIVATION_NAME) : public ActivationFunction { \ - private: \ + private: \ static const std::string name; \ \ - public: \ + public: \ const std::string& getName() const { return name; } /** * @def END_DEFINE_ACTIVATION @@ -70,7 +70,7 @@ static ClassRegistrar gActivationRegistrar; * Do nothing when forward/backward. */ class IdentityActivation : public ActivationFunction { -public: + public: static const std::string name; Error __must_check forward(Argument& act) { (void)act; diff --git a/paddle/gserver/activations/ActivationFunction.h b/paddle/gserver/activations/ActivationFunction.h index 0f4b0fe0abb85403d42fc8a2ac28560e10058c20..8e2e144769f2e668a9a8f02890d29c4a7fe128a3 100644 --- a/paddle/gserver/activations/ActivationFunction.h +++ b/paddle/gserver/activations/ActivationFunction.h @@ -31,7 +31,7 @@ struct Argument; * */ class ActivationFunction { -public: + public: static ActivationFunction* create(const std::string& type); static std::vector getAllRegisteredTypes(); diff --git a/paddle/gserver/activations/MKLDNNActivation.cpp b/paddle/gserver/activations/MKLDNNActivation.cpp index 56ffb839344aabe43eaae0bd46e6dbf95e4d8f20..672444c6561adbeb78c3c453f12ab6aaedeed646 100644 --- a/paddle/gserver/activations/MKLDNNActivation.cpp +++ b/paddle/gserver/activations/MKLDNNActivation.cpp @@ -35,10 +35,10 @@ static ClassRegistrar gMKLDNNActivationRegistrar; * @def END_MKLDNN_ACTIVATION */ #define END_MKLDNN_ACTIVATION(ACT_TYPE) \ -private: \ + private: \ static const std::string name; \ \ -public: \ + public: \ const std::string& getName() const { return name; } \ } \ ; \ @@ -63,11 +63,11 @@ public: \ #define DEFINE_MKLDNN_ELTWISE_ACTIVATION( \ ACT_TYPE, BASE_CLASS, ALPHA, BWD_ALPHA) \ BEGIN_MKLDNN_ACTIVATION(ACT_TYPE, BASE_CLASS) \ -private: \ + private: \ static const float alpha; \ static const float bwdAlpha; \ \ -public: \ + public: \ float getAlpha() const { return alpha; } \ float getBwdAlpha() const { return bwdAlpha; } \ END_MKLDNN_ACTIVATION(ACT_TYPE) \ diff --git a/paddle/gserver/activations/MKLDNNActivation.h b/paddle/gserver/activations/MKLDNNActivation.h index 392b32c70dae3728e13ee64f09f135c015c122cf..eece1b9c37e72624dffd119804c65f7bd36e20fb 100644 --- a/paddle/gserver/activations/MKLDNNActivation.h +++ b/paddle/gserver/activations/MKLDNNActivation.h @@ -27,7 +27,7 @@ namespace paddle { * including mkldnn_relu, mkldnn_elu, mkldnn_tanh, mkldnn_softmax */ class MKLDNNActivation : public ActivationFunction { -protected: + protected: // input value element count size_t cnt_; // should not merge the resetBwd into resetFwd, @@ -43,7 +43,7 @@ protected: std::vector pipelineFwd_; std::vector pipelineBwd_; -public: + public: MKLDNNActivation() : cnt_(0), needResetBwd_(true) {} ~MKLDNNActivation() {} static ActivationFunction* create(const std::string& type); @@ -72,7 +72,7 @@ class MKLDNNEltwiseActivation : public MKLDNNActivation { typedef mkldnn::eltwise_backward eltwise_bwd; typedef mkldnn::algorithm algorithm; -protected: + protected: // save the forward primitive desc, which can be used backward std::shared_ptr fwdPD_; // eltwise_bwd need src input value @@ -80,7 +80,7 @@ protected: // use for copy data std::shared_ptr copyInVal_; -public: + public: MKLDNNEltwiseActivation() {} ~MKLDNNEltwiseActivation() {} virtual const std::string& getName() const = 0; @@ -102,12 +102,12 @@ public: class MKLDNNSoftmaxActivation : public MKLDNNActivation { typedef mkldnn::softmax_forward softmax_fwd; -private: + private: // for backward MatrixPtr sftMaxSum_; MatrixPtr sftMaxDot_; -public: + public: MKLDNNSoftmaxActivation() {} ~MKLDNNSoftmaxActivation() {} virtual const std::string& getName() const = 0; diff --git a/paddle/gserver/dataproviders/DataProvider.h b/paddle/gserver/dataproviders/DataProvider.h index 4851168abab7179d552648c88923a529d55e6a7e..21822b10c2ebf1d353195794cf8f49e02b64c177 100644 --- a/paddle/gserver/dataproviders/DataProvider.h +++ b/paddle/gserver/dataproviders/DataProvider.h @@ -71,7 +71,7 @@ typedef std::shared_ptr BufferBatchPtr; * @brief Data for batch training a neural network */ class DataBatch { -public: + public: DataBatch() : size_(0) { data_.clear(); } /** * @brief Get batch size @@ -181,7 +181,7 @@ public: } } -protected: + protected: /** * @brief batch size */ @@ -194,7 +194,7 @@ protected: }; class BufferBatch { -public: + public: BufferBatch() { hlStream_ = HPPL_STREAM_DEFAULT; hlEvent_ = NULL; @@ -235,7 +235,7 @@ public: void swap(BufferBatch* bufBatch); void clone(DataBatch* srcBatch, bool useGpu); -protected: + protected: DataBatch* batchData_; hl_stream_t hlStream_; hl_event_t hlEvent_; @@ -247,7 +247,7 @@ typedef std::shared_ptr DataProviderPtr; typedef Queue BufferBatchQueue; class DoubleBuffer { -public: + public: DoubleBuffer(DataProvider* dataPool, bool useGpu, int64_t batchSize = 0); virtual ~DoubleBuffer(); void removeOneBatch(DataBatch* dataBatch); @@ -267,7 +267,7 @@ public: void setPending(bool pending) { pending_ = pending; } -protected: + protected: virtual void asyncLoadBatch(); void insertOneBatch(DataBatch* batch); @@ -290,7 +290,7 @@ protected: * one is for input, one is for label. */ class DataProvider { -public: + public: static ClassRegistrar registrar_; static DataProvider* create(const DataConfig& config, const ModelConfig& modelConfig, @@ -359,7 +359,7 @@ public: */ virtual int64_t getNextBatchInternal(int64_t size, DataBatch* batch) = 0; -protected: + protected: DataConfig config_; bool skipShuffle_; float usageRatio_; @@ -382,7 +382,7 @@ protected: * necessary configurations such as stream_names */ class DummyDataProvider : public DataProvider { -public: + public: DummyDataProvider(const DataConfig& config, bool useGpu) : DataProvider(config, useGpu) {} virtual void shuffle() {} @@ -399,7 +399,7 @@ public: * Data provider for one input and one integer label. */ class SimpleDataProviderBase : public DataProvider { -protected: + protected: /// sample feature dimension int64_t sampleDim_; /// the number of samples @@ -425,7 +425,7 @@ protected: RWLock lock_; -public: + public: SimpleDataProviderBase(const DataConfig& config, bool useGpu, bool withInfo); ~SimpleDataProviderBase() {} @@ -440,7 +440,7 @@ public: /// return the number of samples in the buffer int64_t fillBuffer(); -protected: + protected: /** * @brief Fill at most size samples into data and label. * @@ -458,12 +458,12 @@ protected: }; class SimpleDataProvider : public SimpleDataProviderBase { -public: + public: SimpleDataProvider(const DataConfig& config, bool useGpu); ~SimpleDataProvider(); virtual void reset(); -protected: + protected: void loadData(const std::string& fileName); void loadDataFile(const std::string& fileName); virtual int64_t fillBufferImp(real* data, @@ -471,7 +471,7 @@ protected: int* info, int64_t size); -protected: + protected: size_t currentSampleIndex_; std::vector labels_; std::vector data_; diff --git a/paddle/gserver/dataproviders/DataProviderGroup.h b/paddle/gserver/dataproviders/DataProviderGroup.h index 768e54fe82bedd6faca5ad9eb2b6f2ee0017dc3d..91c94dc986c7aeb70df25511ce14a5f9c312a159 100644 --- a/paddle/gserver/dataproviders/DataProviderGroup.h +++ b/paddle/gserver/dataproviders/DataProviderGroup.h @@ -20,7 +20,7 @@ namespace paddle { template class DataProviderGroup : public DataProvider { -protected: + protected: typedef T ProviderType; typedef std::shared_ptr ProviderPtrType; ProviderPtrType provider_; @@ -29,7 +29,7 @@ protected: std::mutex lock_; std::unique_ptr> loader_; -public: + public: DataProviderGroup(const DataConfig& config, bool useGpu); ~DataProviderGroup() {} @@ -38,7 +38,7 @@ public: virtual int64_t getSize() { return -1; } virtual int64_t getNextBatchInternal(int64_t size, DataBatch* batch); -private: + private: void startLoader(); void stopLoader(); void forceStopLoader(); diff --git a/paddle/gserver/dataproviders/MultiDataProvider.h b/paddle/gserver/dataproviders/MultiDataProvider.h index 9a863c896773d71a99e21660fc13e3dd477a0c12..baa1fc019002f86414c9c45734ad65cda916d457 100644 --- a/paddle/gserver/dataproviders/MultiDataProvider.h +++ b/paddle/gserver/dataproviders/MultiDataProvider.h @@ -19,10 +19,10 @@ limitations under the License. */ namespace paddle { class MultiDataProvider : public DataProvider { -protected: + protected: std::vector> subDataProviders_; -public: + public: MultiDataProvider(const DataConfig& config, const ModelConfig& modelConfig, bool useGpu); @@ -33,7 +33,7 @@ public: virtual int64_t getNextBatchInternal(int64_t size, DataBatch* batch); bool isTestMode() const { return isTestMode_; } -private: + private: int totalDataRatio_; bool isTestMode_; }; diff --git a/paddle/gserver/dataproviders/ProtoReader.h b/paddle/gserver/dataproviders/ProtoReader.h index 786703f4dee4802bb967f9d15fb69ebcbc15d997..08d045226e1ebb014bdd91ebf0e8f0353179b0c8 100644 --- a/paddle/gserver/dataproviders/ProtoReader.h +++ b/paddle/gserver/dataproviders/ProtoReader.h @@ -28,7 +28,7 @@ namespace paddle { * messages from/to i/ostream. */ class ProtoReader { -public: + public: explicit ProtoReader(std::istream* s, bool dataCompression = false) { CHECK(s) << "istream pointer is nullptr"; istreamInput_.reset(new google::protobuf::io::IstreamInputStream(s)); @@ -109,7 +109,7 @@ public: return true; } -protected: + protected: std::unique_ptr istreamInput_; std::unique_ptr gzipInput_; std::unique_ptr codedInput_; @@ -144,7 +144,7 @@ protected: }; class ProtoWriter { -public: + public: explicit ProtoWriter(std::ostream* s, bool dataCompression = false) { CHECK(s) << "ostream pointer is nullptr"; ostreamOutput_.reset(new google::protobuf::io::OstreamOutputStream(s)); @@ -168,7 +168,7 @@ public: return ret; } -protected: + protected: std::unique_ptr ostreamOutput_; std::unique_ptr gzipOutput_; std::unique_ptr codedOutput_; diff --git a/paddle/gserver/dataproviders/PyDataProvider.h b/paddle/gserver/dataproviders/PyDataProvider.h index e53354c9e43ea9dc58fd4bd38a533025b6f17482..da50dd4e2ebb743ef45af319bc713ed7ac3d3e10 100644 --- a/paddle/gserver/dataproviders/PyDataProvider.h +++ b/paddle/gserver/dataproviders/PyDataProvider.h @@ -23,7 +23,7 @@ limitations under the License. */ namespace paddle { class PyDataProvider : public DataProvider { -public: + public: PyDataProvider(const DataConfig& config, bool useGpu, bool loadDataAll = true); @@ -40,7 +40,7 @@ public: virtual int64_t getNextBatchInternal(int64_t size, DataBatch* batch); -protected: + protected: struct ProtoSlot; // return false if each each sample is one sequence, i.e., independent // of other samples. @@ -73,7 +73,7 @@ protected: void resetSlots(); void loadData(const std::vector& fileList); -protected: + protected: struct ProtoSlot { SlotDef::SlotType type; int dim; diff --git a/paddle/gserver/dataproviders/PyDataProvider2.cpp b/paddle/gserver/dataproviders/PyDataProvider2.cpp index b4215bb307cc31ce64bb724986b88fdc20bbbf45..54ee091e8f257f76b113d4ca6f8a7c3989c0c1df 100644 --- a/paddle/gserver/dataproviders/PyDataProvider2.cpp +++ b/paddle/gserver/dataproviders/PyDataProvider2.cpp @@ -93,7 +93,7 @@ inline std::ostream& operator<<(std::ostream& os, const SlotHeader& header) { * prepare step, fill data into argument during fill step. */ class IFieldScanner { -public: + public: DISABLE_COPY(IFieldScanner); /** * Ctor. @@ -146,7 +146,7 @@ public: */ static IFieldScanner* create(SlotHeader* header); -protected: + protected: SlotHeader* headerPtr_; }; @@ -154,7 +154,7 @@ protected: * Py Data Provider Cache Interface. */ class IPyDataProviderCache { -public: + public: virtual ~IPyDataProviderCache() {} /** @@ -193,7 +193,7 @@ public: * data. And it support cache strategies. */ class PyDataProvider2 : public DataProvider { -public: + public: /** * Ctor */ @@ -234,7 +234,7 @@ public: */ virtual ~PyDataProvider2() { resetImpl(false); } -private: + private: void createPyDataObj(const std::string& model, const std::string& className, const std::string& fileListName, @@ -435,7 +435,7 @@ private: exit_ = false; } -private: + private: std::unique_ptr loadThread_; std::atomic exit_; std::deque callingContexts_; @@ -461,7 +461,7 @@ private: static PyObjectPtr zeroTuple_; class PositionRandom { - public: + public: inline explicit PositionRandom(bool skipRand) : eng_(ThreadLocalRandomEngine::get()), skipRand_(skipRand) {} @@ -476,14 +476,14 @@ private: } } - private: + private: std::default_random_engine& eng_; std::unique_ptr> dist_; bool skipRand_; }; // DataProvider interface -public: + public: /** * Resetting the PyDataProvider. May start reading thread here. */ @@ -666,7 +666,7 @@ REGISTER_DATA_PROVIDER_EX(py2, PyDataProvider2); * Scanner for dense slot. */ class DenseScanner : public IFieldScanner { -public: + public: explicit DenseScanner(SlotHeader* ptr) : IFieldScanner(ptr), height_(0) {} /** @@ -708,7 +708,7 @@ public: ++height_; } -private: + private: size_t height_; }; @@ -716,7 +716,7 @@ private: * Scanner for index slot */ class IndexScanner : public IFieldScanner { -public: + public: explicit IndexScanner(SlotHeader* ptr) : IFieldScanner(ptr), cnt_(0) {} /** @@ -740,12 +740,12 @@ public: CHECK(ok) << "Cannot cast int " << py::repr(obj); } -private: + private: size_t cnt_; }; class SparseNonValueScanner : public IFieldScanner { -public: + public: explicit SparseNonValueScanner(SlotHeader* ptr) : IFieldScanner(ptr), nnz_(0), height_(0) {} @@ -790,7 +790,7 @@ public: ++height_; } -protected: + protected: /** * Set a single sparse index and value. * @param [out] col sparse index @@ -809,7 +809,7 @@ protected: }; class SparseValueScanner : public SparseNonValueScanner { -public: + public: explicit SparseValueScanner(SlotHeader* ptr) : SparseNonValueScanner(ptr) {} virtual void finishPrepare(Argument& argument) { @@ -817,7 +817,7 @@ public: argument.value, height_, headerPtr_->dim, nnz_, FLOAT_VALUE); } -protected: + protected: virtual void setData(int* col, real* dat, PyObject* obj) { py::SequenceHelper s(obj); SparseNonValueScanner::setData(col, dat, s[0]); @@ -829,7 +829,7 @@ protected: * Sequence Scanner. Scanner for sequence or sub-sequence. */ class SequenceScanner : public IFieldScanner { -public: + public: /** * Ctor * @param innerScanner inner scanner for each timestep or sub-sequence. @@ -902,7 +902,7 @@ public: */ virtual void finishFill(Argument& argument) { inner_->finishFill(argument); } -protected: + protected: size_t getSize(PyObject* obj) { py::SequenceHelper s(obj); auto sc = dynamic_cast(inner_.get()); @@ -917,7 +917,7 @@ protected: } } -private: + private: std::unique_ptr inner_; size_t cnt_; std::function getSeqStartPos_; @@ -969,7 +969,7 @@ IFieldScanner* IFieldScanner::create(SlotHeader* header) { * python every pass. */ class NoCacheStrategy : public IPyDataProviderCache { -public: + public: virtual bool reset() { return true; } virtual void drop(std::deque* data) { data->clear(); } @@ -984,7 +984,7 @@ public: * The rest passes, will load data from memory. */ class CacheOnePassInMemory : public IPyDataProviderCache { -public: + public: CacheOnePassInMemory() : objPool_(new std::deque()), droppedPool_(new std::deque()) {} @@ -1011,7 +1011,7 @@ public: virtual std::deque* load() { return objPool_.get(); } -private: + private: std::unique_ptr> objPool_; std::unique_ptr> droppedPool_; }; diff --git a/paddle/gserver/evaluators/CTCErrorEvaluator.cpp b/paddle/gserver/evaluators/CTCErrorEvaluator.cpp index 0f680de776f4755ca5fe83c86ea759d88f93ed01..c6cd41de9a1a22470d8659eb90d1ac2b075b2df9 100644 --- a/paddle/gserver/evaluators/CTCErrorEvaluator.cpp +++ b/paddle/gserver/evaluators/CTCErrorEvaluator.cpp @@ -22,7 +22,7 @@ namespace paddle { * calculate sequence-to-sequence edit distance */ class CTCErrorEvaluator : public Evaluator { -private: + private: MatrixPtr outActivations_; int numTimes_, numClasses_, numSequences_, blank_; real deletions_, insertions_, substitutions_; @@ -197,7 +197,7 @@ private: (real)seqClassficationError_ / numSequences_; } -public: + public: CTCErrorEvaluator() : numTimes_(0), numClasses_(0), diff --git a/paddle/gserver/evaluators/ChunkEvaluator.cpp b/paddle/gserver/evaluators/ChunkEvaluator.cpp index 755b91d05caf33745e66415e7b111ba348c575d9..a2216293b1ab3a32e9cc903b805ca0aca10d58c1 100644 --- a/paddle/gserver/evaluators/ChunkEvaluator.cpp +++ b/paddle/gserver/evaluators/ChunkEvaluator.cpp @@ -77,7 +77,7 @@ class ChunkEvaluator : public Evaluator { std::set excludedChunkTypes_; mutable std::unordered_map values_; -public: + public: virtual void init(const EvaluatorConfig& config) { Evaluator::init(config); if (config.chunk_scheme() == "IOB") { @@ -276,7 +276,7 @@ public: return "chunk"; } -private: + private: void storeLocalValues() const { CHECK_GE(numOutputSegments_, 0); CHECK_GE(numLabelSegments_, 0); diff --git a/paddle/gserver/evaluators/DetectionMAPEvaluator.cpp b/paddle/gserver/evaluators/DetectionMAPEvaluator.cpp index f43ef5dd51407236a3a36b300b33f92a9fad885a..ddb8ebca784db4a83c328ff75f5c50c7aecd7352 100644 --- a/paddle/gserver/evaluators/DetectionMAPEvaluator.cpp +++ b/paddle/gserver/evaluators/DetectionMAPEvaluator.cpp @@ -28,7 +28,7 @@ namespace paddle { * The config file api is detection_map_evaluator. */ class DetectionMAPEvaluator : public Evaluator { -public: + public: DetectionMAPEvaluator() : evaluateDifficult_(false), cpuOutput_(nullptr), cpuLabel_(nullptr) {} @@ -132,7 +132,7 @@ public: LOG(FATAL) << "Distribute detection evaluation not implemented."; } -protected: + protected: void calcTFPos(const size_t batchSize, const vector>>& allGTBBoxes, const vector>>>& @@ -287,7 +287,7 @@ protected: real getValueImpl() const { return calcMAP(); } -private: + private: real overlapThreshold_; // overlap threshold when determining whether matched bool evaluateDifficult_; // whether evaluate difficult ground truth size_t backgroundId_; // class index of background diff --git a/paddle/gserver/evaluators/Evaluator.cpp b/paddle/gserver/evaluators/Evaluator.cpp index 79478e7fac63a49c494105d53a6944b4b89e6c63..941fb8fb539d58cca22ecf563d2effa816243c3b 100644 --- a/paddle/gserver/evaluators/Evaluator.cpp +++ b/paddle/gserver/evaluators/Evaluator.cpp @@ -38,7 +38,7 @@ void Evaluator::eval(const NeuralNetwork& nn) { * The config file api is classification_error_evaluator. */ class ClassificationErrorEvaluator : public Evaluator { -public: + public: /* ClassificationErrorEvaluator() : totalScore2_(0) {} @@ -124,7 +124,7 @@ public: } // Evaluator interface -protected: + protected: std::string getTypeImpl() const { return "classification_error"; } }; @@ -135,7 +135,7 @@ protected: */ class SequenceClassificationErrorEvaluator : public ClassificationErrorEvaluator { -public: + public: virtual void updateSamplesNum(const std::vector& arguments) { numSamples_ += arguments[0].getNumSequences(); } @@ -166,7 +166,7 @@ public: } // Evaluator interface -protected: + protected: std::string getTypeImpl() const { return "seq_classification_error"; } }; REGISTER_EVALUATOR(seq_classification_error, @@ -178,7 +178,7 @@ REGISTER_EVALUATOR(seq_classification_error, * The config file api is sum_evaluator. */ class SumEvaluator : public Evaluator { -public: + public: SumEvaluator() : cpuLabel_(nullptr), cpuWeight_(nullptr) {} virtual void updateSamplesNum(const std::vector& arguments) { @@ -255,12 +255,12 @@ public: mergeResultsOfAllClients(client); } -private: + private: IVectorPtr cpuLabel_; MatrixPtr cpuWeight_; // Evaluator interface -protected: + protected: std::string getTypeImpl() const { return "sum"; } }; /** @@ -274,7 +274,7 @@ protected: * */ class ColumnSumEvaluator : public Evaluator { -public: + public: explicit ColumnSumEvaluator(int32_t colIdx) : colIdx_(colIdx), colNum_(0), sum_(nullptr) {} @@ -368,13 +368,13 @@ public: client->reduce(&numSamples_, &numSamples_, 1, FLAGS_trainer_id, 0); } -private: + private: int32_t colIdx_; size_t colNum_; MatrixPtr sum_; /* cpu matrix */ // Evaluator interface -protected: + protected: std::string getTypeImpl() const { if (colIdx_ == -1) return "last-column-sum"; @@ -1018,7 +1018,7 @@ static InitFunction __reg_type_auc_sum__([]() { * The config file api is value_printer_evaluator. */ class ValuePrinter : public NotGetableEvaluator { -public: + public: virtual void eval(const NeuralNetwork& nn) { for (const std::string& name : config_.input_layers()) { nn.getLayer(name)->getOutput().printValueString(LOG(INFO), @@ -1038,7 +1038,7 @@ REGISTER_EVALUATOR(value_printer, ValuePrinter); * The config file api is gradient_printer_evaluator. */ class GradientPrinter : public NotGetableEvaluator { -public: + public: virtual void eval(const NeuralNetwork& nn) { for (const std::string& name : config_.input_layers()) { const Argument& argu = nn.getLayer(name)->getOutput(); @@ -1061,11 +1061,11 @@ REGISTER_EVALUATOR(gradient_printer, GradientPrinter); * The config file api is maxid_printer_evaluator. */ class MaxIdPrinter : public NotGetableEvaluator { -private: + private: IVectorPtr maxIds_; MatrixPtr maxValues_; -public: + public: MaxIdPrinter() {} virtual void eval(const NeuralNetwork& nn) { @@ -1103,12 +1103,12 @@ REGISTER_EVALUATOR(max_id_printer, MaxIdPrinter); * The config file api is maxframe_printer_evaluator. */ class MaxFramePrinter : public NotGetableEvaluator { -private: + private: IVectorPtr maxIds_; MatrixPtr maxValues_; MatrixPtr value_; -public: + public: MaxFramePrinter() { value_ = Matrix::create(nullptr, /* height= */ 1, 1, /* trans= */ false, false); @@ -1190,7 +1190,7 @@ REGISTER_EVALUATOR(max_frame_printer, MaxFramePrinter); * */ class SequenceTextPrinter : public NotGetableEvaluator { -private: + private: /// dict_file, which contains a list of tokens std::vector dict_; /// result_file, which is the output file @@ -1203,7 +1203,7 @@ private: /// store the probability associated with each sequence std::vector cpuIn_; -public: + public: SequenceTextPrinter() {} virtual void init(const EvaluatorConfig& config) { @@ -1334,7 +1334,7 @@ REGISTER_EVALUATOR(seq_text_printer, SequenceTextPrinter); * The config file api is classification_error_printer_evaluator. */ class ClassificationErrorPrinter : public ClassificationErrorEvaluator { -public: + public: virtual void updateSamplesNum(const std::vector& arguments) {} virtual real evalImp(std::vector& arguments) { diff --git a/paddle/gserver/evaluators/Evaluator.h b/paddle/gserver/evaluators/Evaluator.h index be2032992c455fe2b442dbe05d84128ef8ebf82f..42948f1097d9a12600f4b11646a47e45b9bf4e96 100644 --- a/paddle/gserver/evaluators/Evaluator.h +++ b/paddle/gserver/evaluators/Evaluator.h @@ -40,7 +40,7 @@ class NeuralNetwork; * has been by a trained model. */ class Evaluator { -public: + public: static Evaluator* create(const EvaluatorConfig& config); Evaluator() : numSamples_(0), totalScore_(0) {} @@ -172,7 +172,7 @@ public: return this->getTypeImpl(); } -protected: + protected: /** * @brief getValueImpl The simplest way to define getValue result. If this * evaluator doesn't contain multiple fields, and do not throw any error, just @@ -191,7 +191,7 @@ protected: */ virtual std::string getTypeImpl() const { return "base"; } -protected: + protected: EvaluatorConfig config_; double numSamples_; double totalScore_; @@ -204,7 +204,7 @@ protected: */ class NotGetableEvaluator : public Evaluator { // Evaluator interface -public: + public: void getNames(std::vector* names) {} real getValue(const std::string& name, Error* err) const { @@ -219,7 +219,7 @@ public: }; class DummyEvaluator : public Evaluator { -public: + public: DummyEvaluator() {} virtual void init(const EvaluatorConfig&) {} virtual void start() {} @@ -232,7 +232,7 @@ public: virtual void printStats(std::ostream&) const {} // Evaluator interface -protected: + protected: std::string getTypeImpl() const; }; /** @@ -251,7 +251,7 @@ protected: * */ class AucEvaluator : public Evaluator { -public: + public: AucEvaluator(int32_t colIdx) : colIdx_(colIdx), realColumnIdx_(0), @@ -269,7 +269,7 @@ public: virtual void distributeEval(ParameterClient2* client); -private: + private: static const uint32_t kBinNum_ = (1 << 24) - 1; static const int kNegativeLabel_ = 0; double statPos_[kBinNum_ + 1]; @@ -292,7 +292,7 @@ private: double calcAuc() const; // Evaluator interface -protected: + protected: real getValueImpl() const; std::string getTypeImpl() const; }; @@ -305,7 +305,7 @@ protected: * dense value. */ class RankAucEvaluator : public Evaluator { -public: + public: // evaluate ranking AUC virtual void start(); @@ -317,7 +317,7 @@ public: mergeResultsOfAllClients(client); } -private: + private: MatrixPtr output_; MatrixPtr click_; MatrixPtr pv_; @@ -329,7 +329,7 @@ private: size_t size); // Evaluator interface -protected: + protected: std::string getTypeImpl() const; }; @@ -344,7 +344,7 @@ protected: * The config file api is precision_recall_evaluator. */ class PrecisionRecallEvaluator : public Evaluator { -public: + public: // Evaluate precision, recall and F1 score PrecisionRecallEvaluator() : isMultiBinaryLabel_(false), @@ -379,7 +379,7 @@ public: StatsInfo() : TP(0.0), TN(0.0), FP(0.0), FN(0.0) {} }; -private: + private: bool isMultiBinaryLabel_; std::vector statsInfo_; @@ -444,7 +444,7 @@ private: * The config file api is pnpair_evaluator. */ class PnpairEvaluator : public Evaluator { -public: + public: PnpairEvaluator() : cpuOutput_(nullptr), cpuLabel_(nullptr), @@ -491,7 +491,7 @@ public: << " calc total neg pair: " << pairArray_[1]; } -private: + private: static const uint32_t kPairArrayNum_ = 2; double pairArray_[kPairArrayNum_]; MatrixPtr cpuOutput_; @@ -500,7 +500,7 @@ private: MatrixPtr cpuWeight_; // Evaluator interface -protected: + protected: real getValueImpl() const { return pairArray_[0] / ((pairArray_[1] <= 0) ? 1.0 : pairArray_[1]); } diff --git a/paddle/gserver/gradientmachines/GradientMachine.h b/paddle/gserver/gradientmachines/GradientMachine.h index 60936c311d1b0119186c76d5c95b8819294446ce..22cf5d265f429ecbcea1808a54c85d7e89f8bc99 100644 --- a/paddle/gserver/gradientmachines/GradientMachine.h +++ b/paddle/gserver/gradientmachines/GradientMachine.h @@ -73,7 +73,7 @@ class GradientMachine; typedef std::shared_ptr GradientMachinePtr; class GradientMachine { -public: + public: enum CreateMode { kNormal = 0, kSgdSparseCpuTraining = 3, @@ -240,7 +240,7 @@ public: */ virtual void releaseOutput() {} -protected: + protected: virtual void onLoadParameter() {} std::vector parameters_; diff --git a/paddle/gserver/gradientmachines/GradientMachineMode.h b/paddle/gserver/gradientmachines/GradientMachineMode.h index 898b68fbbc329145109ad0ae4b97c872d4f9a37c..dd944a35f8952e354f8e4f3eb5c67b136c5f080e 100644 --- a/paddle/gserver/gradientmachines/GradientMachineMode.h +++ b/paddle/gserver/gradientmachines/GradientMachineMode.h @@ -19,14 +19,14 @@ limitations under the License. */ namespace paddle { class IGradientMachineMode { -public: + public: virtual ~IGradientMachineMode() {} -public: // interfaces - /** - * @brief create current mode's gradient machine by model config. - * @param config model config - */ + public: // interfaces + /** + * @brief create current mode's gradient machine by model config. + * @param config model config + */ virtual GradientMachine* create(const ModelConfig& config) = 0; /** @@ -55,14 +55,14 @@ public: // interfaces */ virtual bool needTrainWholeDataInOneBatch() const = 0; -public: // static methods. - /** - * @brief register a custom gradient machine mode. - * @note For user to register a custom gradient machine mode, id should >= - * kCustom. - * @param mode mode id. - * @param ptr mode description object. - */ + public: // static methods. + /** + * @brief register a custom gradient machine mode. + * @note For user to register a custom gradient machine mode, id should >= + * kCustom. + * @param mode mode id. + * @param ptr mode description object. + */ static void regGradientMachineMode( int32_t mode, std::unique_ptr&& ptr) { modes_.insert(std::make_pair(mode, std::move(ptr))); @@ -141,7 +141,7 @@ public: // static methods. } } -private: + private: static std::unordered_map> modes_; }; diff --git a/paddle/gserver/gradientmachines/MultiGradientMachine.h b/paddle/gserver/gradientmachines/MultiGradientMachine.h index 83d2651f34b3698848427f29b1a90e606e57950e..eff7d5284c6dd4898344203b50acc94ae61b4d59 100644 --- a/paddle/gserver/gradientmachines/MultiGradientMachine.h +++ b/paddle/gserver/gradientmachines/MultiGradientMachine.h @@ -166,7 +166,7 @@ struct GradBuffer { * the merged gradient to parameter server. */ class MultiGradientMachine : public GradientMachine { -public: + public: enum TaskType { TASK_FORWARD_BACKWARD = 0, TASK_FORWARD = 1, @@ -213,7 +213,7 @@ public: /// The gradietns will be copied to each thread in the computing threads. virtual void setOutputGrad(const std::vector& args); -protected: + protected: friend class TrainerThread; std::vector& getAllThreads() { return threads_; } @@ -281,7 +281,7 @@ protected: int paraMainThread(int pid) const { return paraMainThread_[pid]; } -protected: + protected: virtual void forwardImp(const std::vector& inArgs, std::vector* outArgs, PassType passType, @@ -298,7 +298,7 @@ protected: void allocGradBufs(); -protected: + protected: bool useGpu_; bool hasNonstaticCpuParamters_; @@ -342,7 +342,7 @@ protected: }; class TrainerThread { -public: + public: TrainerThread(const ModelConfig& config, int threadId, MultiGradientMachine* multiMachine); @@ -392,7 +392,7 @@ public: /// Whether the thread has input data. bool hasInputData() { return batchSize_ != 0; } -protected: + protected: void mergeCpuGradients(); void mergeGradSparse( @@ -421,7 +421,7 @@ protected: /// GradientMachine::backward void doCallback(int pid); -protected: + protected: MultiGradientMachine* multiMachine_; ModelConfig config_; /// whether the thread should stop diff --git a/paddle/gserver/gradientmachines/MultiNetwork.cpp b/paddle/gserver/gradientmachines/MultiNetwork.cpp index a1140402b8baaae20e20802ebf87462e301b60f9..5f3d09dda26772850828e6d44e8cc65635b314dc 100644 --- a/paddle/gserver/gradientmachines/MultiNetwork.cpp +++ b/paddle/gserver/gradientmachines/MultiNetwork.cpp @@ -122,7 +122,7 @@ void MultiNetwork::finish() { } class MultiCombinedEvaluator : public Evaluator { -public: + public: MultiCombinedEvaluator() {} void addEvaluator(std::unique_ptr&& evaluator) { evaluators_.emplace_back(std::move(evaluator)); @@ -167,7 +167,7 @@ public: } } -protected: + protected: std::vector> evaluators_; }; diff --git a/paddle/gserver/gradientmachines/MultiNetwork.h b/paddle/gserver/gradientmachines/MultiNetwork.h index 186a9ad0a39cd7815aea6738e6c6bc4a0c944aa9..495d5592017b5fb937fb8243bf12a5f2f30d67e7 100644 --- a/paddle/gserver/gradientmachines/MultiNetwork.h +++ b/paddle/gserver/gradientmachines/MultiNetwork.h @@ -22,7 +22,7 @@ limitations under the License. */ namespace paddle { class MultiNetwork : public NeuralNetwork { -public: + public: explicit MultiNetwork(std::string subModelName = "") : NeuralNetwork(subModelName) {} @@ -58,7 +58,7 @@ public: virtual void finish(); -protected: + protected: std::vector> subNetworks_; }; } // namespace paddle diff --git a/paddle/gserver/gradientmachines/NeuralNetwork.cpp b/paddle/gserver/gradientmachines/NeuralNetwork.cpp index a3c13df3dbad973505d8919bce8b95348527e273..ac60a3a3408d37b66cb712d893c6b93a1750f448 100644 --- a/paddle/gserver/gradientmachines/NeuralNetwork.cpp +++ b/paddle/gserver/gradientmachines/NeuralNetwork.cpp @@ -362,7 +362,7 @@ void NeuralNetwork::releaseOutput() { #ifndef PADDLE_MOBILE_INFERENCE class CombinedEvaluator : public Evaluator { -public: + public: void addEvaluator(std::unique_ptr&& evaluator) { evaluators_.emplace_back(std::move(evaluator)); } @@ -400,11 +400,11 @@ public: } } -protected: + protected: std::vector> evaluators_; // Evaluator interface -public: + public: /** * @brief getNames will return all inside evaluators' names. * @param names [out]: return names. @@ -435,7 +435,7 @@ public: }); } -private: + private: template T getMethodHelper(const std::string& name, Error* err, @@ -454,7 +454,7 @@ private: }; class SubnetEvaluator : public CombinedEvaluator { -public: + public: SubnetEvaluator(const std::string& layerName, std::unique_ptr&& evaluator) : layerName_(layerName) { @@ -473,7 +473,7 @@ public: << " in submodel " << nn.getName(); } -protected: + protected: std::string layerName_; }; diff --git a/paddle/gserver/gradientmachines/NeuralNetwork.h b/paddle/gserver/gradientmachines/NeuralNetwork.h index 5b32f844f742c07c8bee6638cb46dc00285f49b0..3e5615c8f0b30ab1283d41e025496051869289dc 100644 --- a/paddle/gserver/gradientmachines/NeuralNetwork.h +++ b/paddle/gserver/gradientmachines/NeuralNetwork.h @@ -56,7 +56,7 @@ void parameterInitNN(int paramId, std::vector* sharedParams); class NeuralNetwork : public GradientMachine { -public: + public: virtual void init(const ModelConfig& config, ParamInitCallback callback = nullptr, const std::vector& parameterTypes = @@ -144,7 +144,7 @@ public: */ void releaseOutput(); -protected: + protected: /** * The constructor of NeuralNetwork. * The sub networks can get parameters_ and parameterMap_ diff --git a/paddle/gserver/gradientmachines/ParallelNeuralNetwork.h b/paddle/gserver/gradientmachines/ParallelNeuralNetwork.h index e3b6812123141e8e0afb9368fb06f2b34f526800..c091459506ad477bed3f429a22071eccedd664bb 100644 --- a/paddle/gserver/gradientmachines/ParallelNeuralNetwork.h +++ b/paddle/gserver/gradientmachines/ParallelNeuralNetwork.h @@ -32,7 +32,7 @@ enum TaskType { * multiple threads in parallel. */ class ParallelNeuralNetwork : public NeuralNetwork { -public: + public: ParallelNeuralNetwork(std::string subModelName = "", NeuralNetwork *rootNetwork = nullptr) : NeuralNetwork(subModelName, rootNetwork) {} @@ -66,7 +66,7 @@ public: // virtual void eval(Evaluator* evaluator); -protected: + protected: bool useGpu_; /// number of gpu devices int numDevices_; @@ -74,7 +74,7 @@ protected: }; class ParallelThread { -public: + public: ParallelThread(int threadId, int deviceId, bool useGpu); ~ParallelThread(); void jobEnqueue(LayerPtr layer, TaskType task); @@ -87,10 +87,10 @@ public: } void setForwardPassType(PassType passType) { passType_ = passType; } -protected: + protected: void computeThread(); -public: + public: struct Job { LayerPtr layer_; TaskType task_; @@ -98,7 +98,7 @@ public: typedef Queue JobQueue; JobQueue queue_; -protected: + protected: /// from 0 to threads-1 int threadId_; /// the GPU device Id which the computeThread_ used diff --git a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp index 2429b5d1a0a5ccf66db365b82c494c53d8e1fd4b..73ac8cda721f200c1a02cd9c1d9456df70d7b7d2 100644 --- a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp +++ b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp @@ -96,7 +96,7 @@ static InitFunction __init__diy_prob_method( std::numeric_limits::max()); class BeamSearchControlCallbacks { -public: + public: RecurrentGradientMachine::BeamSearchCandidatesAdjustCallback beamSearchCandidateAdjust; RecurrentGradientMachine::NormOrDropNodeCallback normOrDropNode; @@ -115,7 +115,7 @@ public: }; class BeamSearchStatisticsCallbacks { -public: + public: RecurrentGradientMachine::EachStepCallback onEachStepStarted; RecurrentGradientMachine::EachStepCallback onEachStepStoped; @@ -148,11 +148,11 @@ RecurrentGradientMachine::RecurrentGradientMachine( * so it's should not be placed in root network. */ class BootBiasLayer : public Layer { -protected: + protected: std::unique_ptr biases_; IVectorPtr cpuIds_; -public: + public: explicit BootBiasLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/gradientmachines/RecurrentGradientMachine.h b/paddle/gserver/gradientmachines/RecurrentGradientMachine.h index 0032b72cdae44588af976f1ac542149545f551f1..7e943cebd35234ba7af357c9f64fde6b0a9546ce 100644 --- a/paddle/gserver/gradientmachines/RecurrentGradientMachine.h +++ b/paddle/gserver/gradientmachines/RecurrentGradientMachine.h @@ -30,7 +30,7 @@ class BeamSearchControlCallbacks; class BeamSearchStatisticsCallbacks; class RecurrentGradientMachine : public NeuralNetwork { -public: + public: RecurrentGradientMachine(const std::string& subModelName, NeuralNetwork* rootNetwork); @@ -290,7 +290,7 @@ public: return this->finalPaths_; } -protected: + protected: std::vector commonSeqInfo_; ICpuGpuVectorPtr sequenceStartPositions_; void calcSequenceStartPositions(); @@ -447,7 +447,7 @@ protected: MatrixPtr cpuProb_; IVectorPtr cpuEos_; -private: + private: /* * @return beam size in beam search */ diff --git a/paddle/gserver/layers/AddtoLayer.h b/paddle/gserver/layers/AddtoLayer.h index 1d000630567cb1116ab0ff69e42380fc0eae6173..6ea54f4a53d466594055db2fb5167fa1a9d6c9da 100644 --- a/paddle/gserver/layers/AddtoLayer.h +++ b/paddle/gserver/layers/AddtoLayer.h @@ -33,10 +33,10 @@ namespace paddle { * The config file api is addto_layer. */ class AddtoLayer : public Layer { -protected: + protected: std::unique_ptr biases_; -public: + public: explicit AddtoLayer(const LayerConfig& config) : Layer(config) {} ~AddtoLayer() {} diff --git a/paddle/gserver/layers/AgentLayer.h b/paddle/gserver/layers/AgentLayer.h index da0ac4530836205757399ac8eb64dd003740a53f..51f346d5c9fdf9599cddf4b668c128035fd94187 100644 --- a/paddle/gserver/layers/AgentLayer.h +++ b/paddle/gserver/layers/AgentLayer.h @@ -26,11 +26,11 @@ namespace paddle { * called to set one and only one real layer */ class AgentLayer : public Layer { -protected: + protected: LayerPtr realLayer_; int numSamples_; -public: + public: explicit AgentLayer(const LayerConfig& config) : Layer(config) {} ~AgentLayer() {} @@ -55,14 +55,14 @@ public: * GatherAgentLayer collect a complete sequence. */ class GatherAgentLayer : public Layer { -protected: + protected: std::vector realLayers_; std::vector idsVec_; // we don't clear idsVec_ vector to aviod IVector alloc/free IVectorPtr allIds_; std::vector idIndex_; -public: + public: explicit GatherAgentLayer(const LayerConfig& config) : Layer(config) {} virtual ~GatherAgentLayer() {} @@ -95,7 +95,7 @@ public: * if it is, the agent will select a few ids in real layer. */ class ScatterAgentLayer : public Layer { -protected: + protected: LayerPtr realLayer_; IVectorPtr ids_; IVectorPtr cpuIds_; @@ -113,7 +113,7 @@ protected: // true for setRealLayer, false for setRealLayerAndOutput bool selectionMode_; -public: + public: explicit ScatterAgentLayer(const LayerConfig& config) : Layer(config) {} virtual ~ScatterAgentLayer() {} diff --git a/paddle/gserver/layers/AverageLayer.h b/paddle/gserver/layers/AverageLayer.h index 24602d2a9c3e08cf76f6f98b5f9e3f593118e6e1..03e2673b55ceca7a698f1b858327ad6fad739087 100644 --- a/paddle/gserver/layers/AverageLayer.h +++ b/paddle/gserver/layers/AverageLayer.h @@ -37,7 +37,7 @@ namespace paddle { * The config file api is pooling_layer. */ class AverageLayer : public SequencePoolLayer { -public: + public: enum AverageStrategy { kAverage = 0, kSum = 1, kAverageSquareRootN = 2 }; explicit AverageLayer(const LayerConfig& config) : SequencePoolLayer(config) {} @@ -48,7 +48,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -protected: + protected: int mode_; }; } // namespace paddle diff --git a/paddle/gserver/layers/BatchNormBaseLayer.h b/paddle/gserver/layers/BatchNormBaseLayer.h index 69d642af4f12593e8db8a726310e6b1934c8e3be..5a446c0843a22adecbaf2ae09fcd526b68865ae2 100644 --- a/paddle/gserver/layers/BatchNormBaseLayer.h +++ b/paddle/gserver/layers/BatchNormBaseLayer.h @@ -40,7 +40,7 @@ namespace paddle { */ class BatchNormBaseLayer : public Layer { -public: + public: explicit BatchNormBaseLayer(const LayerConfig& config) : Layer(config) {} ~BatchNormBaseLayer() {} @@ -61,7 +61,7 @@ public: */ void calFeatureMapSize(); -protected: + protected: /// Batch normalization scale parameter, which is referred to as gamma in /// in original paper. std::unique_ptr weight_; diff --git a/paddle/gserver/layers/BatchNormalizationLayer.h b/paddle/gserver/layers/BatchNormalizationLayer.h index 95add69215e3ea0b0225d0a245fe37905c33127b..e5e4e690b6017f32de0f4d7557065c02c03d689f 100644 --- a/paddle/gserver/layers/BatchNormalizationLayer.h +++ b/paddle/gserver/layers/BatchNormalizationLayer.h @@ -27,7 +27,7 @@ namespace paddle { */ class BatchNormalizationLayer : public BatchNormBaseLayer { -public: + public: explicit BatchNormalizationLayer(const LayerConfig& config) : BatchNormBaseLayer(config), firstTest_(true) {} @@ -38,7 +38,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -protected: + protected: /// Load pre-calculated mean and std. void setMeanAndStd(); diff --git a/paddle/gserver/layers/BilinearInterpLayer.h b/paddle/gserver/layers/BilinearInterpLayer.h index acd320420f4bbfe313f3ae77577ffc6b5cbfbfdf..8e08c2e1ce80172f55c93d8242821f683fa1a731 100644 --- a/paddle/gserver/layers/BilinearInterpLayer.h +++ b/paddle/gserver/layers/BilinearInterpLayer.h @@ -26,13 +26,13 @@ namespace paddle { * @note The config file api is bilinear_interp_layer. */ class BilinearInterpLayer : public Layer { -protected: + protected: size_t outImgH_, outImgW_; size_t inImgH_, inImgW_; real ratioH_, ratioW_; size_t numChannels_; -public: + public: explicit BilinearInterpLayer(const LayerConfig& config) : Layer(config) {} virtual ~BilinearInterpLayer() {} diff --git a/paddle/gserver/layers/BlockExpandLayer.h b/paddle/gserver/layers/BlockExpandLayer.h index 1797b64036b5cb9f97477d5a44b2f58e2d6c0cd4..9d76584f3a4eda19a9e8f806256a7b8da617cc37 100644 --- a/paddle/gserver/layers/BlockExpandLayer.h +++ b/paddle/gserver/layers/BlockExpandLayer.h @@ -40,7 +40,7 @@ namespace paddle { * The config file api is block_expand_layer. */ class BlockExpandLayer : public Layer { -protected: + protected: /** * @brief Calculate outputH_ and outputW_ and return block number which * actually is time steps. @@ -53,7 +53,7 @@ protected: TensorShape inputShape_; TensorShape outputShape_; -public: + public: explicit BlockExpandLayer(const LayerConfig& config) : Layer(config) {} ~BlockExpandLayer() {} diff --git a/paddle/gserver/layers/CRFDecodingLayer.h b/paddle/gserver/layers/CRFDecodingLayer.h index fba3cebac1a375008c58d21c458d9e0b98305ffa..018162e146fa93725fe84bdf2da9a6124f3cea6f 100644 --- a/paddle/gserver/layers/CRFDecodingLayer.h +++ b/paddle/gserver/layers/CRFDecodingLayer.h @@ -30,14 +30,14 @@ namespace paddle { * See LinearChainCRF.h for the detail of the CRF formulation. */ class CRFDecodingLayer : public CRFLayer { -public: + public: explicit CRFDecodingLayer(const LayerConfig& config) : CRFLayer(config) {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap) override; void forward(PassType passType) override; void backward(const UpdateCallback& callback) override; -protected: + protected: std::unique_ptr crf_; }; diff --git a/paddle/gserver/layers/CRFLayer.h b/paddle/gserver/layers/CRFLayer.h index cb5bd05568cc79c0093d6af0791cf0b3ce2dae47..88c2ed343ad5743068c871fe351437270d85f223 100644 --- a/paddle/gserver/layers/CRFLayer.h +++ b/paddle/gserver/layers/CRFLayer.h @@ -27,14 +27,14 @@ namespace paddle { * See class LinearChainCRF for the detail of the CRF formulation. */ class CRFLayer : public Layer { -public: + public: explicit CRFLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap) override; void forward(PassType passType) override; void backward(const UpdateCallback& callback) override; -protected: + protected: size_t numClasses_; ParameterPtr parameter_; std::vector crfs_; diff --git a/paddle/gserver/layers/CTCLayer.h b/paddle/gserver/layers/CTCLayer.h index fcbc42565e9340903d05aca2d0ba2091ffe20be0..5d70b1f4ceb03028865378d1d01b5706b35b10de 100644 --- a/paddle/gserver/layers/CTCLayer.h +++ b/paddle/gserver/layers/CTCLayer.h @@ -20,7 +20,7 @@ limitations under the License. */ namespace paddle { class CTCLayer : public Layer { -public: + public: explicit CTCLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap) override; @@ -31,7 +31,7 @@ public: const Argument& softmaxSeqs, const Argument& labelSeqs); -protected: + protected: size_t numClasses_; bool normByTimes_; std::vector ctcs_; diff --git a/paddle/gserver/layers/ClipLayer.cpp b/paddle/gserver/layers/ClipLayer.cpp index dbc3337499788af5a9b6f68a6016e94c2072d61b..6aa3c8fe64f5a59e82f3271baed99fd17fd6653f 100644 --- a/paddle/gserver/layers/ClipLayer.cpp +++ b/paddle/gserver/layers/ClipLayer.cpp @@ -24,11 +24,11 @@ namespace paddle { */ class ClipLayer : public Layer { -protected: + protected: double min_; double max_; -public: + public: explicit ClipLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/ConcatenateLayer.cpp b/paddle/gserver/layers/ConcatenateLayer.cpp index f5ab29a509e45e72c71ba122c73aeba1b3b6a827..e6de329ff3f9ccfdd1cbe697c1de1a9cd8c7926a 100644 --- a/paddle/gserver/layers/ConcatenateLayer.cpp +++ b/paddle/gserver/layers/ConcatenateLayer.cpp @@ -23,7 +23,7 @@ namespace paddle { * each input as one row for the output of this layer and apply activation. */ class ConcatenateLayer : public Layer { -public: + public: explicit ConcatenateLayer(const LayerConfig& config) : Layer(config) {} ~ConcatenateLayer() {} @@ -97,7 +97,7 @@ void ConcatenateLayer::backward(const UpdateCallback& callback) { * processed by a Projection. */ class ConcatenateLayer2 : public Layer { -public: + public: explicit ConcatenateLayer2(const LayerConfig& config) : Layer(config) {} ~ConcatenateLayer2() {} @@ -108,7 +108,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -protected: + protected: std::vector> projections_; std::vector projOutput_; std::vector> projCol_; diff --git a/paddle/gserver/layers/ContextProjection.h b/paddle/gserver/layers/ContextProjection.h index e30f98f58d2be9ac538f6385efe68990b705ac5f..9c217145419048282a9a09ad899dc970e7c9704f 100644 --- a/paddle/gserver/layers/ContextProjection.h +++ b/paddle/gserver/layers/ContextProjection.h @@ -42,7 +42,7 @@ namespace paddle { * The config file api is context_projection. */ class ContextProjection : public Projection { -public: + public: /** * Constructor. If context_start is zero and context_lenth is one, it will * set trainable_padding false. trainable_padding is an optional arguments @@ -63,7 +63,7 @@ public: virtual bool init(); -protected: + protected: std::unique_ptr weight_; /// number of extra timesteps added at the beginning size_t beginPad_; diff --git a/paddle/gserver/layers/Conv3DLayer.h b/paddle/gserver/layers/Conv3DLayer.h index 5ab5ff3d4af07449484c441958c31c8fb06de894..07b804bad02beb6ec9c3e9fd43c3cd3aa6d50b22 100644 --- a/paddle/gserver/layers/Conv3DLayer.h +++ b/paddle/gserver/layers/Conv3DLayer.h @@ -26,7 +26,7 @@ namespace paddle { * calculate convolution operation. */ class Conv3DLayer : public ConvBaseLayer { -public: + public: explicit Conv3DLayer(const LayerConfig& config) : ConvBaseLayer(config) {} ~Conv3DLayer() {} @@ -40,7 +40,7 @@ public: void bpropWeights(int i); size_t getSize(); -protected: + protected: // Figure out the dimensions for individual gemms. IntV M_; /// numFilters_ / filter_group_; IntV N_; /// channels_ * filterSizeZ_ * filterSize_ * filterSizeY_ diff --git a/paddle/gserver/layers/ConvBaseLayer.h b/paddle/gserver/layers/ConvBaseLayer.h index 93869fe68d15b1cf38296fa8e2f6197dc74f879f..801bc4f888c5a60e803c882dcf807678c64af20c 100644 --- a/paddle/gserver/layers/ConvBaseLayer.h +++ b/paddle/gserver/layers/ConvBaseLayer.h @@ -24,7 +24,7 @@ namespace paddle { */ class ConvBaseLayer : public Layer { -protected: + protected: typedef std::vector IntV; /// True if it's deconv layer, false if it's convolution layer @@ -88,7 +88,7 @@ protected: /// of output size. bool caffeMode_; -public: + public: explicit ConvBaseLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/ConvBaseOperator.h b/paddle/gserver/layers/ConvBaseOperator.h index 27fb0362d3c9518a263eac54206e00974d08eb20..c3c647cb69da5a70eb5346737cc0092e2201c89e 100644 --- a/paddle/gserver/layers/ConvBaseOperator.h +++ b/paddle/gserver/layers/ConvBaseOperator.h @@ -29,7 +29,7 @@ namespace paddle { */ class ConvBaseOperator : public Operator { -public: + public: ConvBaseOperator(const OperatorConfig &config, bool useGpu); /** * Free workspace in device and destroy cudnn tensor descriptor. @@ -46,7 +46,7 @@ public: hl_destroy_convolution_descriptor(convDesc_); } -protected: + protected: /** * Get convolution parameters from layer config and * initialize member variables. diff --git a/paddle/gserver/layers/ConvBaseProjection.h b/paddle/gserver/layers/ConvBaseProjection.h index ba76d236d901187093a2e372a61c5d29d661e8bb..f3266ae1ab945042cde9f24b7c2673c18d37bc11 100644 --- a/paddle/gserver/layers/ConvBaseProjection.h +++ b/paddle/gserver/layers/ConvBaseProjection.h @@ -23,7 +23,7 @@ namespace paddle { * @brief Base class for ConvProjection and ConvTransProjection. */ class ConvBaseProjection : public Projection { -public: + public: /** * Constructor. */ @@ -33,7 +33,7 @@ public: ~ConvBaseProjection(); -protected: + protected: void getConvParams(); void initCudnn(); diff --git a/paddle/gserver/layers/ConvOperator.h b/paddle/gserver/layers/ConvOperator.h index fbdb7bb1cd2b81bd72912dffdc9d059c520068a8..527dbf8c270f35e19ca23acd8a3ba8197d03b988 100644 --- a/paddle/gserver/layers/ConvOperator.h +++ b/paddle/gserver/layers/ConvOperator.h @@ -29,7 +29,7 @@ namespace paddle { */ class ConvOperator : public ConvBaseOperator { -public: + public: ConvOperator(const OperatorConfig &config, bool useGpu) : ConvBaseOperator(config, useGpu) {} /** diff --git a/paddle/gserver/layers/ConvProjection.h b/paddle/gserver/layers/ConvProjection.h index e8ecb99431a421d4b52228600909568b0808649a..22a2202bb6cc256a4a5897724d8eb8a93fefb79f 100644 --- a/paddle/gserver/layers/ConvProjection.h +++ b/paddle/gserver/layers/ConvProjection.h @@ -23,7 +23,7 @@ namespace paddle { * @brief Convolution projection do the same calculation with CudnnConvLayer. */ class ConvProjection : public ConvBaseProjection { -public: + public: /** * Constructor. */ diff --git a/paddle/gserver/layers/ConvShiftLayer.cpp b/paddle/gserver/layers/ConvShiftLayer.cpp index fb877710196835e025466f37b5da27bcf80a3db4..615c3478061b591ea30cbf0b3d27ef2551c0dd28 100644 --- a/paddle/gserver/layers/ConvShiftLayer.cpp +++ b/paddle/gserver/layers/ConvShiftLayer.cpp @@ -42,7 +42,7 @@ namespace paddle { */ class ConvShiftLayer : public Layer { -public: + public: explicit ConvShiftLayer(const LayerConfig& config) : Layer(config) {} ~ConvShiftLayer() {} diff --git a/paddle/gserver/layers/ConvTransOperator.h b/paddle/gserver/layers/ConvTransOperator.h index 1bf58f2bfb78ae7dee433455ece37d908b113045..53cb7a21b49189898d09aa20cd46d04cc5c20198 100644 --- a/paddle/gserver/layers/ConvTransOperator.h +++ b/paddle/gserver/layers/ConvTransOperator.h @@ -29,7 +29,7 @@ namespace paddle { */ class ConvTransOperator : public ConvBaseOperator { -public: + public: ConvTransOperator(const OperatorConfig &config, bool useGpu) : ConvBaseOperator(config, useGpu) {} /** diff --git a/paddle/gserver/layers/ConvTransProjection.h b/paddle/gserver/layers/ConvTransProjection.h index 269b2694c82ea076102633537d7c961139a19a43..0f9ed720d3b8855a3a24ac25a1c3917c4b98e81d 100644 --- a/paddle/gserver/layers/ConvTransProjection.h +++ b/paddle/gserver/layers/ConvTransProjection.h @@ -23,7 +23,7 @@ namespace paddle { * @brief Convolution projection do the same calculation with CudnnConvLayer. */ class ConvTransProjection : public ConvBaseProjection { -public: + public: /** * Constructor. */ diff --git a/paddle/gserver/layers/ConvexCombinationLayer.cpp b/paddle/gserver/layers/ConvexCombinationLayer.cpp index dce751940c1bf1695a034a3c551412dcb9b7b8b5..31363d97c4fd318ec2c6d48f9200f6ba1f49ba11 100644 --- a/paddle/gserver/layers/ConvexCombinationLayer.cpp +++ b/paddle/gserver/layers/ConvexCombinationLayer.cpp @@ -36,7 +36,7 @@ namespace paddle { * The config file api is linear_comb_layer. */ class ConvexCombinationLayer : public Layer { -protected: + protected: /// A matrix pointer pointing to second input. MatrixPtr tmpMtx0; /// A matrix pointer pointing to first input. @@ -44,7 +44,7 @@ protected: /// A matrix pointer pointing to output. MatrixPtr tmpRow1; -public: + public: explicit ConvexCombinationLayer(const LayerConfig& config) : Layer(config) {} ~ConvexCombinationLayer() {} diff --git a/paddle/gserver/layers/CosSimLayer.h b/paddle/gserver/layers/CosSimLayer.h index 675cdb16b563faa7acf9e701096bd334ed661160..d9fe1ff270f1f76e3b246dca374ddf45445419f9 100644 --- a/paddle/gserver/layers/CosSimLayer.h +++ b/paddle/gserver/layers/CosSimLayer.h @@ -33,7 +33,7 @@ namespace paddle { * The config file api is cos_sim. */ class CosSimLayer : public Layer { -public: + public: explicit CosSimLayer(const LayerConfig& config) : Layer(config) {} ~CosSimLayer() {} diff --git a/paddle/gserver/layers/CosSimVecMatLayer.cpp b/paddle/gserver/layers/CosSimVecMatLayer.cpp index 685b4e8ef376b76b3058eeba82d803d460e7105c..230ecc768b4d7314b21ac1d76899c3c3bab12309 100644 --- a/paddle/gserver/layers/CosSimVecMatLayer.cpp +++ b/paddle/gserver/layers/CosSimVecMatLayer.cpp @@ -32,7 +32,7 @@ namespace paddle { */ class CosSimVecMatLayer : public Layer { -protected: + protected: MatrixPtr tmpMtx0; MatrixPtr tmpMtx1; MatrixPtr tmpRow0; @@ -40,7 +40,7 @@ protected: MatrixPtr tmpRow2; MatrixPtr tmpRow3; -public: + public: explicit CosSimVecMatLayer(const LayerConfig& config) : Layer(config) {} ~CosSimVecMatLayer() {} diff --git a/paddle/gserver/layers/CostLayer.cpp b/paddle/gserver/layers/CostLayer.cpp index 484f803a8387a16152c5911d7d5c72b0111283ae..1327616950a8887efa2cba410fa7ae8b5bd97da4 100644 --- a/paddle/gserver/layers/CostLayer.cpp +++ b/paddle/gserver/layers/CostLayer.cpp @@ -716,7 +716,7 @@ void HuberTwoClassification::backwardImp(Matrix& output, * \f] */ class SumCostLayer : public Layer { -public: + public: explicit SumCostLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/CostLayer.h b/paddle/gserver/layers/CostLayer.h index 306c067ed1c040555d2b03996cc0749faf0ea68c..9bfec0e2b169fac4f235fd13347be687c4f1a222 100644 --- a/paddle/gserver/layers/CostLayer.h +++ b/paddle/gserver/layers/CostLayer.h @@ -29,7 +29,7 @@ namespace paddle { * handled by the base class. */ class CostLayer : public Layer { -public: + public: explicit CostLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -51,7 +51,7 @@ public: Argument& label, Matrix& outputGrad) = 0; -protected: + protected: LayerPtr weightLayer_; real coeff_; }; @@ -65,7 +65,7 @@ protected: * \f] */ class MultiClassCrossEntropy : public CostLayer { -public: + public: explicit MultiClassCrossEntropy(const LayerConfig& config) : CostLayer(config) {} @@ -95,7 +95,7 @@ public: * In Proceedings of the ACL 2014 Conference. */ class MultiClassCrossEntropyWithSelfNorm : public CostLayer { -public: + public: explicit MultiClassCrossEntropyWithSelfNorm(const LayerConfig& config) : CostLayer(config) {} @@ -108,7 +108,7 @@ public: Argument& label, Matrix& outputGrad) override; -protected: + protected: MatrixPtr sftMaxSum_; MatrixPtr sumInv_; }; @@ -120,7 +120,7 @@ protected: * \f] */ class SoftBinaryClassCrossEntropy : public CostLayer { -public: + public: explicit SoftBinaryClassCrossEntropy(const LayerConfig& config) : CostLayer(config) {} @@ -133,7 +133,7 @@ public: Argument& label, Matrix& outputGrad) override; -protected: + protected: MatrixPtr targetPerDim_; }; @@ -145,7 +145,7 @@ protected: * \f] */ class SumOfSquaresCostLayer : public CostLayer { -public: + public: explicit SumOfSquaresCostLayer(const LayerConfig& config) : CostLayer(config) {} @@ -171,7 +171,7 @@ public: * x = output - label */ class SmoothL1CostLayer : public CostLayer { -public: + public: explicit SmoothL1CostLayer(const LayerConfig& config) : CostLayer(config) {} bool init(const LayerMap& layerMap, @@ -197,7 +197,7 @@ public: * Rank useing Gradient Descent. */ class RankingCost : public Layer { -public: + public: explicit RankingCost(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -225,7 +225,7 @@ public: (void)outputGrad; } -private: + private: double posPairCount_; double negPairCount_; MatrixPtr margin_; @@ -250,7 +250,7 @@ private: * with Nonsmooth Cost Functions. */ class LambdaCost : public Layer { -public: + public: explicit LambdaCost(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -270,7 +270,7 @@ public: real* gradData, int size); -private: + private: MatrixPtr marginGrad_; int truncationSize_; int maxSortSize_; @@ -287,10 +287,10 @@ private: * \f] */ class MultiBinaryLabelCrossEntropy : public CostLayer { -protected: + protected: MatrixPtr targetPerDim_; -public: + public: explicit MultiBinaryLabelCrossEntropy(const LayerConfig& config) : CostLayer(config) {} @@ -308,7 +308,7 @@ public: * A base layer for HuberRegressionLoss and HuberTwoClassification. */ class HuberCost : public CostLayer { -public: + public: std::vector tmpCpuInput_; explicit HuberCost(const LayerConfig& config) : CostLayer(config) {} @@ -331,7 +331,7 @@ public: * Loss = delta * abs(y - f) - 0.5 * delta^2, otherwise */ class HuberRegressionLoss : public HuberCost { -public: + public: explicit HuberRegressionLoss(const LayerConfig& config) : HuberCost(config) {} bool init(const LayerMap& layerMap, @@ -343,7 +343,7 @@ public: Argument& label, Matrix& outputGrad) override; -protected: + protected: real delta_; }; @@ -356,7 +356,7 @@ protected: * Loss = 0, otherwise */ class HuberTwoClassification : public HuberCost { -public: + public: explicit HuberTwoClassification(const LayerConfig& config) : HuberCost(config) {} diff --git a/paddle/gserver/layers/CropLayer.h b/paddle/gserver/layers/CropLayer.h index 1a85911ef75e992df587a60cfc9a727eafa4cc76..ef88bc483d157406a0f5a7924c14c345ea0df8c4 100644 --- a/paddle/gserver/layers/CropLayer.h +++ b/paddle/gserver/layers/CropLayer.h @@ -28,7 +28,7 @@ namespace paddle { * crop input as this shape conf */ class CropLayer : public Layer { -public: + public: explicit CropLayer(const LayerConfig& config) : Layer(config) {} ~CropLayer() {} @@ -38,7 +38,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -protected: + protected: void setOutDims(); void setInDims(); diff --git a/paddle/gserver/layers/CrossEntropyOverBeam.h b/paddle/gserver/layers/CrossEntropyOverBeam.h index b47a2933c255c264ba780b2d87c9fbe53cb5665d..c8702b16165eee8d552c563082ffc708ce443deb 100644 --- a/paddle/gserver/layers/CrossEntropyOverBeam.h +++ b/paddle/gserver/layers/CrossEntropyOverBeam.h @@ -44,7 +44,7 @@ struct BeamExpansion { typedef std::shared_ptr BeamExpansionPtr; class CostForOneSequence { -public: + public: CostForOneSequence() : beamSize_(0), validExpansionCount_(0), goldAsExtraPath_(false) {} void setData(const BeamExpansionPtr bPtr, size_t beamSize) { @@ -64,7 +64,7 @@ public: real forward(); void backward(); -private: + private: void calValidExpandStep(); void constructTotalExpansion(); size_t initLastExpansion(); @@ -93,14 +93,14 @@ private: }; class CrossEntropyOverBeam : public Layer { -public: + public: explicit CrossEntropyOverBeam(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap) override; void forward(PassType passType) override; void backward(const UpdateCallback& callback) override; -private: + private: void checkInputs(); void copyInputsToCpu(); void resizeOutput(); diff --git a/paddle/gserver/layers/CudnnBatchNormLayer.h b/paddle/gserver/layers/CudnnBatchNormLayer.h index aa279f73d66770384815cad4d9e2ee0b04a4a1ad..1bb4eff8d2372660caa4ec4a4a20a27f365bebd0 100644 --- a/paddle/gserver/layers/CudnnBatchNormLayer.h +++ b/paddle/gserver/layers/CudnnBatchNormLayer.h @@ -30,7 +30,7 @@ namespace paddle { */ class CudnnBatchNormLayer : public BatchNormBaseLayer { -public: + public: explicit CudnnBatchNormLayer(const LayerConfig& config) : BatchNormBaseLayer(config) {} @@ -46,7 +46,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -protected: + protected: /// Epsilon value used in the batch normalization formula. /// Same epsilon value should be used in forward and backward functions. double eps_; diff --git a/paddle/gserver/layers/CudnnConvBaseLayer.h b/paddle/gserver/layers/CudnnConvBaseLayer.h index 698104e4fbd2556f426001687a581153f32773d8..1ee1aa100d8adaed04ce24ee12b5b9af52c14b13 100644 --- a/paddle/gserver/layers/CudnnConvBaseLayer.h +++ b/paddle/gserver/layers/CudnnConvBaseLayer.h @@ -31,14 +31,14 @@ namespace paddle { * The config file api is img_conv_layer. */ class CudnnConvBaseLayer : public ConvBaseLayer { -protected: + protected: std::vector> projConf_; std::vector> projections_; hl_tensor_descriptor biasDesc_; hl_tensor_descriptor outputDesc_; -public: + public: explicit CudnnConvBaseLayer(const LayerConfig& config) : ConvBaseLayer(config) {} diff --git a/paddle/gserver/layers/CudnnPoolLayer.h b/paddle/gserver/layers/CudnnPoolLayer.h index 9eb4fc6138b0bce59660406705d15291eb38af9b..fc249354d10333211691b6844bffa3c8da8a79ee 100644 --- a/paddle/gserver/layers/CudnnPoolLayer.h +++ b/paddle/gserver/layers/CudnnPoolLayer.h @@ -26,7 +26,7 @@ namespace paddle { */ class CudnnPoolLayer : public PoolLayer { -protected: + protected: int windowHeight, windowWidth; int heightPadding, widthPadding, strideHeight, strideWidth; int imageH_, imageW_, outputH_, outputW_; @@ -40,7 +40,7 @@ protected: /// A description of a pooling operation. hl_pooling_descriptor poolingDesc_; -public: + public: static bool typeCheck(const std::string& poolType, hl_pooling_mode_t* mode = nullptr); explicit CudnnPoolLayer(const LayerConfig& config); diff --git a/paddle/gserver/layers/DataLayer.h b/paddle/gserver/layers/DataLayer.h index 4b12afe0efe81843b58e459ca1e58b4f7f4a1664..d02f5a4697b9067f7d34e4d0b2d34f8c63ffe020 100644 --- a/paddle/gserver/layers/DataLayer.h +++ b/paddle/gserver/layers/DataLayer.h @@ -25,7 +25,7 @@ namespace paddle { * The config file api is data_layer. */ class DataLayer : public Layer { -public: + public: explicit DataLayer(const LayerConfig& config) : Layer(config) {} virtual void setData(const Argument& data) { data_ = data; } @@ -58,10 +58,10 @@ public: } } -private: + private: void copyDataToOutput(Argument& output); -protected: + protected: Argument data_; }; diff --git a/paddle/gserver/layers/DataNormLayer.h b/paddle/gserver/layers/DataNormLayer.h index 2a2a2a4aa76e8e315d9d66da1b738d6d615d10f2..7ae67a877b488c8d197896b8b1e3e90057fbe1c9 100644 --- a/paddle/gserver/layers/DataNormLayer.h +++ b/paddle/gserver/layers/DataNormLayer.h @@ -37,7 +37,7 @@ namespace paddle { */ class DataNormLayer : public Layer { -public: + public: enum NormalizationStrategy { kZScore = 0, kMinMax = 1, kDecimalScaling = 2 }; explicit DataNormLayer(const LayerConfig& config) : Layer(config) {} @@ -50,7 +50,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -protected: + protected: int mode_; std::unique_ptr weight_; MatrixPtr min_; diff --git a/paddle/gserver/layers/DeConv3DLayer.h b/paddle/gserver/layers/DeConv3DLayer.h index 57d51cdec66930b9b79c0c0395da66922cd53ae4..13d1d07cf5cc6e2a6ea89768e29b1fe8cda5e81c 100644 --- a/paddle/gserver/layers/DeConv3DLayer.h +++ b/paddle/gserver/layers/DeConv3DLayer.h @@ -27,7 +27,7 @@ namespace paddle { * calculate deconvolution3D operation. */ class DeConv3DLayer : public ConvBaseLayer { -public: + public: explicit DeConv3DLayer(const LayerConfig& config) : ConvBaseLayer(config) {} ~DeConv3DLayer() {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap); @@ -40,7 +40,7 @@ public: void bpropWeights(int i); size_t getSize(); -protected: + protected: // Figure out the dimensions for individual gemms. IntV M_; /// numFilters_ / filter_group_; IntV N_; /// channels_ * filterSizeZ_ * filterSize_ * filterSizeY_ diff --git a/paddle/gserver/layers/DetectionOutputLayer.h b/paddle/gserver/layers/DetectionOutputLayer.h index 174a6e5d9acb476276b66627b4aabce2ae6c1037..b0270ed33141993665aeabdc53829600a4403643 100644 --- a/paddle/gserver/layers/DetectionOutputLayer.h +++ b/paddle/gserver/layers/DetectionOutputLayer.h @@ -33,7 +33,7 @@ namespace paddle { */ class DetectionOutputLayer : public Layer { -public: + public: explicit DetectionOutputLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap); @@ -42,7 +42,7 @@ public: void backward(const UpdateCallback& callback = nullptr) {} -protected: + protected: inline LayerPtr getPriorBoxLayer() { return inputLayers_[0]; } inline LayerPtr getLocInputLayer(size_t index) { @@ -53,7 +53,7 @@ protected: return inputLayers_[1 + inputNum_ + index]; } -private: + private: size_t numClasses_; // number of classes size_t inputNum_; // number of input layers real nmsThreshold_; diff --git a/paddle/gserver/layers/DotMulOperator.cpp b/paddle/gserver/layers/DotMulOperator.cpp index 68db2929adee1336e52abfcb8e6495e589afa683..03d18d9b239e57dc41334462f2324ae2d0505a62 100644 --- a/paddle/gserver/layers/DotMulOperator.cpp +++ b/paddle/gserver/layers/DotMulOperator.cpp @@ -27,7 +27,7 @@ namespace paddle { * The config file api is dotmul_operator. */ class DotMulOperator : public Operator { -public: + public: DotMulOperator(const OperatorConfig& config, bool useGpu); virtual void forward(); virtual void backward(); diff --git a/paddle/gserver/layers/DotMulProjection.cpp b/paddle/gserver/layers/DotMulProjection.cpp index 86453aae84142f9f534182d085f4a96a2c7a3e15..d7780387670e83af24fa342be3d596b618b1f677 100644 --- a/paddle/gserver/layers/DotMulProjection.cpp +++ b/paddle/gserver/layers/DotMulProjection.cpp @@ -26,14 +26,14 @@ namespace paddle { * The config file api is dotmul_projection. */ class DotMulProjection : public Projection { -public: + public: DotMulProjection(const ProjectionConfig& config, const ParameterPtr& parameter, bool useGpu); virtual void forward(); virtual void backward(const UpdateCallback& callback); -protected: + protected: /// shared memory with parameter std::unique_ptr weight_; }; diff --git a/paddle/gserver/layers/DotProdLayer.cpp b/paddle/gserver/layers/DotProdLayer.cpp index 5148d93e27d199b0c373221cedd4f03d6d32c8ab..72b0c707b2131dc275ba604cd20ae0007c34a9a9 100644 --- a/paddle/gserver/layers/DotProdLayer.cpp +++ b/paddle/gserver/layers/DotProdLayer.cpp @@ -27,7 +27,7 @@ namespace paddle { */ class DotProdLayer : public Layer { -public: + public: explicit DotProdLayer(const LayerConfig& config) : Layer(config) {} ~DotProdLayer() {} diff --git a/paddle/gserver/layers/EosIdCheckLayer.cpp b/paddle/gserver/layers/EosIdCheckLayer.cpp index 470a5b8ea208ad0acb64e3067881e0d183e1dc39..04400f2836581179849a4dd1c256bbddcc82530f 100644 --- a/paddle/gserver/layers/EosIdCheckLayer.cpp +++ b/paddle/gserver/layers/EosIdCheckLayer.cpp @@ -24,7 +24,7 @@ namespace paddle { * It is used by recurrent layer group. */ class EosIdCheckLayer : public Layer { -public: + public: explicit EosIdCheckLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/ExpandConvLayer.h b/paddle/gserver/layers/ExpandConvLayer.h index be968155efd0b8f19503c996ccd329379c6b1104..6919ef71355a4c660b9ddd60bff75fee399cfaa9 100644 --- a/paddle/gserver/layers/ExpandConvLayer.h +++ b/paddle/gserver/layers/ExpandConvLayer.h @@ -29,7 +29,7 @@ namespace paddle { */ class ExpandConvLayer : public ConvBaseLayer { -public: + public: explicit ExpandConvLayer(const LayerConfig& config) : ConvBaseLayer(config) {} ~ExpandConvLayer() {} @@ -42,7 +42,7 @@ public: size_t getOutputSize(); -protected: + protected: std::vector inputShape_; std::vector filterShape_; std::vector outputShape_; diff --git a/paddle/gserver/layers/ExpandLayer.h b/paddle/gserver/layers/ExpandLayer.h index 04bbfcbd04931fa11d11a9fcc74f0e4f19767f1b..06bd4ef05ee206628d981fee8e7eec3c91b18b7a 100644 --- a/paddle/gserver/layers/ExpandLayer.h +++ b/paddle/gserver/layers/ExpandLayer.h @@ -37,7 +37,7 @@ namespace paddle { */ class ExpandLayer : public Layer { -protected: + protected: std::unique_ptr biases_; /// if input[0] is dense data, ExpandLevel=kNonSeq; /// if input[0] is sequence data, ExpandLevel=kSeq @@ -48,7 +48,7 @@ protected: /// of input[1] ICpuGpuVectorPtr expandStartsPos_; -public: + public: explicit ExpandLayer(const LayerConfig& config) : Layer(config) {} ~ExpandLayer() {} diff --git a/paddle/gserver/layers/FactorizationMachineLayer.h b/paddle/gserver/layers/FactorizationMachineLayer.h index 684da4e65a461d46204c348b3374b0e9e00eb389..148abe238173dd44cd0fcf3f5cda732f70078706 100644 --- a/paddle/gserver/layers/FactorizationMachineLayer.h +++ b/paddle/gserver/layers/FactorizationMachineLayer.h @@ -42,7 +42,7 @@ namespace paddle { */ class FactorizationMachineLayer : public Layer { -protected: + protected: // The latent vectors, shape: (size, factorSize_) // Each row of the latentVectors_ matrix is the latent vector // corresponding to one input feature dimension @@ -50,7 +50,7 @@ protected: // The hyperparameter that defines the dimensionality of the factorization size_t factorSize_; -private: + private: // Store the square values of the letent vectors matrix MatrixPtr latentVectorsSquare_; // Store the square values of input matrix @@ -65,7 +65,7 @@ private: // Negative identity matrix MatrixPtr negOnes_; -public: + public: explicit FactorizationMachineLayer(const LayerConfig& config) : Layer(config) {} ~FactorizationMachineLayer() {} diff --git a/paddle/gserver/layers/FeatureMapExpandLayer.cpp b/paddle/gserver/layers/FeatureMapExpandLayer.cpp index 81b98da45bc4b9b8ef0723dd6ea2db809860e219..d95f0b9b3d13e8bff635373cb4d5705c2351bd97 100644 --- a/paddle/gserver/layers/FeatureMapExpandLayer.cpp +++ b/paddle/gserver/layers/FeatureMapExpandLayer.cpp @@ -38,11 +38,11 @@ namespace paddle { */ class FeatureMapExpandLayer : public Layer { -private: + private: int numFilters_; bool asRowVector_; -public: + public: explicit FeatureMapExpandLayer(const LayerConfig& config) : Layer(config) {} ~FeatureMapExpandLayer() {} diff --git a/paddle/gserver/layers/FullMatrixProjection.h b/paddle/gserver/layers/FullMatrixProjection.h index 7c4cd1a7066d427f54e1a280a956acb025e6dc16..a27aa4a12327ac39ec3418a849b1230e13f759ee 100644 --- a/paddle/gserver/layers/FullMatrixProjection.h +++ b/paddle/gserver/layers/FullMatrixProjection.h @@ -28,14 +28,14 @@ namespace paddle { * The config file api is full_matrix_projection. */ class FullMatrixProjection : public Projection { -public: + public: FullMatrixProjection(const ProjectionConfig& config, const ParameterPtr& parameter, bool useGpu); virtual void forward(); virtual void backward(const UpdateCallback& callback); -protected: + protected: std::unique_ptr weight_; }; diff --git a/paddle/gserver/layers/FullyConnectedLayer.h b/paddle/gserver/layers/FullyConnectedLayer.h index e66aeeb7334c9c871749196d77474a02ecf82b09..e0f9d6ce55fbdf73e5507032c108c735bf04597b 100644 --- a/paddle/gserver/layers/FullyConnectedLayer.h +++ b/paddle/gserver/layers/FullyConnectedLayer.h @@ -28,11 +28,11 @@ namespace paddle { */ class FullyConnectedLayer : public Layer { -protected: + protected: WeightList weights_; std::unique_ptr biases_; -public: + public: explicit FullyConnectedLayer(const LayerConfig& config) : Layer(config) {} ~FullyConnectedLayer() {} diff --git a/paddle/gserver/layers/GatedRecurrentLayer.h b/paddle/gserver/layers/GatedRecurrentLayer.h index f0a3a823018f3943b0295c172b19d0fe9d0674b4..46508dc977bf1a6fd33dc1fb024bd1aed36a0ff3 100644 --- a/paddle/gserver/layers/GatedRecurrentLayer.h +++ b/paddle/gserver/layers/GatedRecurrentLayer.h @@ -47,7 +47,7 @@ namespace paddle { */ class GatedRecurrentLayer : public Layer, public GruCompute { -public: + public: explicit GatedRecurrentLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -63,7 +63,7 @@ public: LayerStatePtr getState() override; -protected: + protected: void forwardSequence(int batchSize, size_t numSequences, const int* starts, @@ -79,7 +79,7 @@ protected: MatrixPtr inputValue); void backwardBatch(int batchSize, MatrixPtr inputGrad); -protected: + protected: std::unique_ptr weight_; std::unique_ptr gateWeight_; std::unique_ptr stateWeight_; diff --git a/paddle/gserver/layers/GetOutputLayer.cpp b/paddle/gserver/layers/GetOutputLayer.cpp index f255681f3e678e51f069522f965fd2776680b595..7c1e3c407cca374c7aa238d07e2263c4a142b6a5 100644 --- a/paddle/gserver/layers/GetOutputLayer.cpp +++ b/paddle/gserver/layers/GetOutputLayer.cpp @@ -17,7 +17,7 @@ limitations under the License. */ namespace paddle { class GetOutputLayer : public Layer { -public: + public: explicit GetOutputLayer(const LayerConfig& config) : Layer(config) {} ~GetOutputLayer() {} diff --git a/paddle/gserver/layers/GruCompute.h b/paddle/gserver/layers/GruCompute.h index fb6bc56422002b4d4080ccb8438767b27ceef064..50006325ce9969c4941aaf28604260f0aeb9b97a 100644 --- a/paddle/gserver/layers/GruCompute.h +++ b/paddle/gserver/layers/GruCompute.h @@ -21,7 +21,7 @@ limitations under the License. */ namespace paddle { class GruCompute { -public: + public: void init(LayerConfig &config); template @@ -33,7 +33,7 @@ public: int frameSize, int batchSize = 1); -public: + public: hl_activation_mode_t activeNode_; hl_activation_mode_t activeGate_; }; diff --git a/paddle/gserver/layers/GruStepLayer.cpp b/paddle/gserver/layers/GruStepLayer.cpp index 917c50250c1c04d6c8f113c8d42ef029e1028606..114f287411c2fccbc08b7da4c05462967c81b268 100644 --- a/paddle/gserver/layers/GruStepLayer.cpp +++ b/paddle/gserver/layers/GruStepLayer.cpp @@ -44,13 +44,13 @@ namespace paddle { * The config file api if gru_step_layer. */ class GruStepLayer : public Layer, public GruCompute { -protected: + protected: Argument gate_; Argument resetOutput_; std::unique_ptr weight_; std::unique_ptr bias_; -public: + public: explicit GruStepLayer(const LayerConfig& config) : Layer(config) {} ~GruStepLayer() {} diff --git a/paddle/gserver/layers/HierarchicalSigmoidLayer.h b/paddle/gserver/layers/HierarchicalSigmoidLayer.h index 10e501f1807ef6ba03d326a1bcf257ede0ee850a..73ef252fd5a5443fe065f3b7bd8c49951ae0b4bd 100644 --- a/paddle/gserver/layers/HierarchicalSigmoidLayer.h +++ b/paddle/gserver/layers/HierarchicalSigmoidLayer.h @@ -58,7 +58,7 @@ namespace paddle { * The config file api is hsigmod_layer. */ class HierarchicalSigmoidLayer : public Layer { -public: + public: explicit HierarchicalSigmoidLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -66,7 +66,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback) override; -protected: + protected: /** * The last of inputs is label layer. */ diff --git a/paddle/gserver/layers/IdentityProjection.cpp b/paddle/gserver/layers/IdentityProjection.cpp index 6c70f77acc0c890e11a4929ea013d7745d8bbed0..34e9eb90161f7942c528b70f177e30f301a8f53f 100644 --- a/paddle/gserver/layers/IdentityProjection.cpp +++ b/paddle/gserver/layers/IdentityProjection.cpp @@ -26,7 +26,7 @@ namespace paddle { * The config file api is identity_projection. */ class IdentityProjection : public Projection { -public: + public: IdentityProjection(const ProjectionConfig& config, const ParameterPtr& parameter, bool useGpu); @@ -68,7 +68,7 @@ void IdentityProjection::backward(const UpdateCallback& callback) { * The config file api is identity_projection. */ class IdentityOffsetProjection : public Projection { -public: + public: IdentityOffsetProjection(const ProjectionConfig& config, const ParameterPtr& parameter, bool useGpu); diff --git a/paddle/gserver/layers/InterpolationLayer.cpp b/paddle/gserver/layers/InterpolationLayer.cpp index 0ac92024bc7eddf05ce023708537d0aa7bab6426..509c07cf22c9bcbe9283241b38540162b3dbe26b 100644 --- a/paddle/gserver/layers/InterpolationLayer.cpp +++ b/paddle/gserver/layers/InterpolationLayer.cpp @@ -33,12 +33,12 @@ namespace paddle { */ class InterpolationLayer : public Layer { -protected: + protected: /// weightLast = 1 - weight MatrixPtr weightLast_; MatrixPtr tmpMatrix; -public: + public: explicit InterpolationLayer(const LayerConfig& config) : Layer(config) {} ~InterpolationLayer() {} diff --git a/paddle/gserver/layers/KmaxSeqScoreLayer.cpp b/paddle/gserver/layers/KmaxSeqScoreLayer.cpp index 0ea960902efc10007896b3f4ce915dea79d0d12d..7fd25954efeb9d9e672040f9909198f2ae3c0449 100644 --- a/paddle/gserver/layers/KmaxSeqScoreLayer.cpp +++ b/paddle/gserver/layers/KmaxSeqScoreLayer.cpp @@ -17,14 +17,14 @@ limitations under the License. */ namespace paddle { class KmaxSeqScoreLayer : public Layer { -private: + private: MatrixPtr scores_; size_t beamSize_; void kmaxScorePerSeq(const real* score, real* sortedRes, const ICpuGpuVectorPtr seqStartPos); -public: + public: explicit KmaxSeqScoreLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/L2DistanceLayer.h b/paddle/gserver/layers/L2DistanceLayer.h index 97f35daf7860fb3b082ef03203327e09dca67371..44e688e1377145845033d9d5cc3f31f5594a11f6 100644 --- a/paddle/gserver/layers/L2DistanceLayer.h +++ b/paddle/gserver/layers/L2DistanceLayer.h @@ -33,7 +33,7 @@ namespace paddle { */ class L2DistanceLayer : public Layer { -public: + public: explicit L2DistanceLayer(const LayerConfig& config) : Layer(config) {} ~L2DistanceLayer() {} @@ -43,7 +43,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -private: + private: // Store the result of subtracting Input2 from Input1 in forward computation, // which will be reused in backward computation. MatrixPtr inputSub_; diff --git a/paddle/gserver/layers/Layer.h b/paddle/gserver/layers/Layer.h index 8da342a00f72ee1196c4af24104ce92c6bbf9f5c..13e20e8316323f9082a9615041584685853aa395 100644 --- a/paddle/gserver/layers/Layer.h +++ b/paddle/gserver/layers/Layer.h @@ -60,7 +60,7 @@ enum PADDLE_DEVICE_ID { * Define necessary variables and functions for every layer. */ class Layer { -protected: + protected: /// Layer config LayerConfig config_; /// whether to use GPU @@ -112,7 +112,7 @@ protected: /// Layer backward function std::vector> backward_; -public: + public: /** * Wait until all input value ready. * Called before Layer::forward() function. @@ -137,7 +137,7 @@ public: */ virtual void markAllInputGrad(); -protected: + protected: /** * Create layer function. Function is called in forward or backward. * \param function, Layer::forward_ or Layer::backward_ @@ -252,7 +252,7 @@ protected: */ void addOutputArgument(int deviceId); -public: + public: explicit Layer(const LayerConfig& config, bool useGpu = FLAGS_use_gpu); virtual ~Layer() {} @@ -490,7 +490,7 @@ public: */ virtual void onPassEnd() {} -protected: + protected: /** * Forward of activation function. */ diff --git a/paddle/gserver/layers/LinearChainCRF.h b/paddle/gserver/layers/LinearChainCRF.h index 1ea4c7e105703b76601499bf3944648cdc98ec99..e802b701d0237bed44adc83273fe53c3e18c92ec 100644 --- a/paddle/gserver/layers/LinearChainCRF.h +++ b/paddle/gserver/layers/LinearChainCRF.h @@ -19,7 +19,7 @@ limitations under the License. */ namespace paddle { class LinearChainCRF { -public: + public: /** * The size of para must be \f$(numClasses + 2) * numClasses\f$. * The first numClasses values of para are for starting weights (\f$a\f$). @@ -71,7 +71,7 @@ public: */ MatrixPtr getXGrad() { return matGrad_; } -protected: + protected: int numClasses_; MatrixPtr a_; MatrixPtr b_; diff --git a/paddle/gserver/layers/LinearChainCTC.h b/paddle/gserver/layers/LinearChainCTC.h index 0b774277dc8cf27f48c6905168cdea047365c99d..5b325a0deb0e9d8df241175159321e52f527f6c4 100644 --- a/paddle/gserver/layers/LinearChainCTC.h +++ b/paddle/gserver/layers/LinearChainCTC.h @@ -20,7 +20,7 @@ limitations under the License. */ namespace paddle { class LinearChainCTC { -public: + public: LinearChainCTC(int numClasses, bool normByTimes); // Calculate the negative log probability as loss @@ -35,7 +35,7 @@ public: int* labelSeq, int labelSeqLen); -protected: + protected: int numClasses_, blank_, totalSegments_, totalTime_; bool normByTimes_; bool isInvalid_; diff --git a/paddle/gserver/layers/LstmCompute.h b/paddle/gserver/layers/LstmCompute.h index b7d55eb1f984d102802cab87ba12ca9c69a2f4be..80fb01cd1885151c8d62a4b5dfdb4ba08327926d 100644 --- a/paddle/gserver/layers/LstmCompute.h +++ b/paddle/gserver/layers/LstmCompute.h @@ -21,7 +21,7 @@ limitations under the License. */ namespace paddle { class LstmCompute { -public: + public: void init(LayerConfig &config); /** @@ -57,7 +57,7 @@ public: hl_lstm_grad grad, int frameSize); -public: + public: hl_activation_mode_t activeNode_; hl_activation_mode_t activeGate_; hl_activation_mode_t activeState_; diff --git a/paddle/gserver/layers/LstmLayer.h b/paddle/gserver/layers/LstmLayer.h index 4568b13ade5555e3cff703ceda1bbce3007c409d..76dfe8146bf67a0b7b4fd4835851fae6ac38d80f 100644 --- a/paddle/gserver/layers/LstmLayer.h +++ b/paddle/gserver/layers/LstmLayer.h @@ -71,7 +71,7 @@ namespace paddle { */ class LstmLayer : public Layer, public LstmCompute { -public: + public: explicit LstmLayer(const LayerConfig &config) : Layer(config) {} bool init(const LayerMap &layerMap, @@ -87,7 +87,7 @@ public: LayerStatePtr getState() override; -protected: + protected: /** * @brief Compute lstm forward one sequence by one sequence. * @param batchSize The batchSize is not equal to the batch_size in @@ -165,7 +165,7 @@ protected: */ void getPrevBatchState(size_t numSequences); -protected: + protected: /// Learned parameters, shape: (size, 4*size). /// The weight ([size, 4*size]) contains \f$W_{hi}, W_{hf}, W_{hc}, W_{ho}\f$. std::unique_ptr weight_; diff --git a/paddle/gserver/layers/LstmStepLayer.cpp b/paddle/gserver/layers/LstmStepLayer.cpp index 8faaa1c4e138fe1ec04b1911449d05528bb5b8b5..c44768ddb2b903763288465325899d86176df73a 100644 --- a/paddle/gserver/layers/LstmStepLayer.cpp +++ b/paddle/gserver/layers/LstmStepLayer.cpp @@ -22,7 +22,7 @@ namespace paddle { * LstmStepLayer used in recurrent layer group. */ class LstmStepLayer : public Layer, public LstmCompute { -protected: + protected: Argument state_; Argument gate_; Argument stateActive_; @@ -30,7 +30,7 @@ protected: MatrixPtr checkIgGrad_, checkFgGrad_, checkOgGrad_; std::unique_ptr weight_; -public: + public: explicit LstmStepLayer(const LayerConfig& config) : Layer(config) {} ~LstmStepLayer() {} diff --git a/paddle/gserver/layers/MDLstmLayer.cpp b/paddle/gserver/layers/MDLstmLayer.cpp index 7cfdb3ff25096ad06c09434cdee48b5f85d650af..22c28157c5a5b19aa54b3151a6c9a4cdcfb01765 100644 --- a/paddle/gserver/layers/MDLstmLayer.cpp +++ b/paddle/gserver/layers/MDLstmLayer.cpp @@ -19,7 +19,7 @@ limitations under the License. */ namespace paddle { class CoordIterator { -public: + public: std::vector dims_; std::vector directions_; std::vector curPos_; @@ -51,7 +51,7 @@ public: } } -public: + public: CoordIterator(std::vector dim, std::vector directions) : dims_(dim), directions_(directions), end_(false) { CHECK_EQ(dims_.size(), directions_.size()); @@ -178,7 +178,7 @@ public: * */ class MDLstmLayer : public LstmLayer { -public: + public: explicit MDLstmLayer(const LayerConfig& config) : LstmLayer(config) {} bool init(const LayerMap& layerMap, @@ -188,13 +188,13 @@ public: void backward(const UpdateCallback& callback) override; -protected: + protected: void forwardOneSequence(int start, CoordIterator& coordIter); void backwardOneSequence(int start, CoordIterator& coordIter); void forwardGate2OutputSequence(int start, CoordIterator& coordIter); void backwardGate2OutputSequence(int start, CoordIterator& coordIter); -protected: + protected: std::vector frameInputGate_; std::vector frameForgetGate_; std::vector frameOutputGate_; diff --git a/paddle/gserver/layers/MKLDNNAddtoLayer.h b/paddle/gserver/layers/MKLDNNAddtoLayer.h index e40e2f2251a1b739958773b8e6dc95a70ed58c76..0b385e804fdbc74c8612031cf415d06f15ce311a 100644 --- a/paddle/gserver/layers/MKLDNNAddtoLayer.h +++ b/paddle/gserver/layers/MKLDNNAddtoLayer.h @@ -25,7 +25,7 @@ namespace paddle { * The config file api is mkldnn_addto */ class MKLDNNAddtoLayer : public MKLDNNLayer { -protected: + protected: // layer size == ic * ih * iw == oc * oh *ow, and can not be changed size_t layerSize_; @@ -38,7 +38,7 @@ protected: std::vector> fwdBias_; std::shared_ptr bwdBias_; -public: + public: explicit MKLDNNAddtoLayer(const LayerConfig& config) : MKLDNNLayer(config) {} ~MKLDNNAddtoLayer() {} @@ -59,7 +59,7 @@ public: void updateWeights(const UpdateCallback& callback) override; -protected: + protected: void resetFwdBuffers(std::vector& inputs, MKLDNNMatrixPtr& bias, MKLDNNMatrixPtr& out); diff --git a/paddle/gserver/layers/MKLDNNBase.h b/paddle/gserver/layers/MKLDNNBase.h index d84e2859407711c13c475a19e140e2f5f51e61c2..786ceaf86086d7c04331641693181809ac019597 100644 --- a/paddle/gserver/layers/MKLDNNBase.h +++ b/paddle/gserver/layers/MKLDNNBase.h @@ -31,7 +31,7 @@ typedef enum { * */ class CPUEngine { -public: + public: static CPUEngine& Instance() { // Thread-safe in C++11. static CPUEngine myInstance; @@ -46,12 +46,12 @@ public: mkldnn::engine& getEngine() { return cpuEngine_; } -protected: + protected: CPUEngine() : cpuEngine_(mkldnn::engine::cpu, 0) {} // CPUEngine() : cpuEngine_(mkldnn::engine::cpu_lazy, 0) {} ~CPUEngine() {} -private: + private: mkldnn::engine cpuEngine_; }; @@ -60,7 +60,7 @@ private: * */ class MKLDNNStream { -public: + public: MKLDNNStream() : ready_(false) { resetState(); } virtual ~MKLDNNStream() {} @@ -89,7 +89,7 @@ public: ready_ = true; } -private: + private: bool ready_; std::shared_ptr stream_; }; diff --git a/paddle/gserver/layers/MKLDNNBatchNormLayer.h b/paddle/gserver/layers/MKLDNNBatchNormLayer.h index 93e182206a1ab1f06087cb808bb266ddea1468c9..9aa20df98f30837e1b80b4269d05d85b7d99ba76 100644 --- a/paddle/gserver/layers/MKLDNNBatchNormLayer.h +++ b/paddle/gserver/layers/MKLDNNBatchNormLayer.h @@ -27,7 +27,7 @@ typedef mkldnn::batch_normalization_backward bn_bwd; * The config file api is mkldnn_batch_norm */ class MKLDNNBatchNormLayer : public MKLDNNLayer { -protected: + protected: // save forward primitive_desc, which can be used backward std::shared_ptr fwdPD_; @@ -62,7 +62,7 @@ protected: MKLDNNMatrixPtr mean_; MKLDNNMatrixPtr var_; -public: + public: explicit MKLDNNBatchNormLayer(const LayerConfig& config) : MKLDNNLayer(config), useGlobalStats_(true), hasInitedWgt_(false) {} @@ -88,7 +88,7 @@ public: void convertWeightsFromPaddle() override; -protected: + protected: void initWeight(); /** * cal moving mean and variance. diff --git a/paddle/gserver/layers/MKLDNNConcatLayer.h b/paddle/gserver/layers/MKLDNNConcatLayer.h index f7abdabfb51df27f8db4e6d4d88c80546eeba248..d7738df6c106c68f55b313f2d119e31c6e444cbf 100644 --- a/paddle/gserver/layers/MKLDNNConcatLayer.h +++ b/paddle/gserver/layers/MKLDNNConcatLayer.h @@ -25,7 +25,7 @@ namespace paddle { * The config file api is mkldnn_concat */ class MKLDNNConcatLayer : public MKLDNNLayer { -protected: + protected: std::vector> bwds_; // input channel numbers std::vector channels_; @@ -35,7 +35,7 @@ protected: // if axis_ == 1, concat channel (default) int axis_; -public: + public: explicit MKLDNNConcatLayer(const LayerConfig& config) : MKLDNNLayer(config), axis_(1) {} @@ -75,7 +75,7 @@ public: return totalSize; } -protected: + protected: void resetFwdBuffers(std::vector& inputs, MKLDNNMatrixPtr& out); void resetFwdPD(std::shared_ptr& pd, diff --git a/paddle/gserver/layers/MKLDNNConvLayer.h b/paddle/gserver/layers/MKLDNNConvLayer.h index 29c8735fbb91e7418797874238eb87759420f181..d399035ed3ae2f411587c1fcf1799bb71c8de63e 100644 --- a/paddle/gserver/layers/MKLDNNConvLayer.h +++ b/paddle/gserver/layers/MKLDNNConvLayer.h @@ -28,7 +28,7 @@ typedef mkldnn::convolution_backward_data conv_bwdData; * The config file api is mkldnn_conv */ class MKLDNNConvLayer : public MKLDNNLayer { -protected: + protected: // padding height and width int ph_, pw_; // stride height and width @@ -59,7 +59,7 @@ protected: std::unique_ptr weight_; std::unique_ptr biases_; -public: + public: explicit MKLDNNConvLayer(const LayerConfig& config) : MKLDNNLayer(config), hasInitedWgt_(false), caffeMode_(true) {} @@ -92,7 +92,7 @@ public: << ", sw: " << sw_ << ", dh: " << dh_ << ", dw: " << dw_; } -protected: + protected: /** * load the dims settings of this conv */ diff --git a/paddle/gserver/layers/MKLDNNFcLayer.h b/paddle/gserver/layers/MKLDNNFcLayer.h index 0d41a4379d677f86f672852fec09b1241009597b..a704066cc818a6b33bd0eed4612d62b674fa72ca 100644 --- a/paddle/gserver/layers/MKLDNNFcLayer.h +++ b/paddle/gserver/layers/MKLDNNFcLayer.h @@ -28,7 +28,7 @@ typedef mkldnn::inner_product_backward_data fc_bwdData; * The config file api is mkldnn_fc */ class MKLDNNFcLayer : public MKLDNNLayer { -protected: + protected: // input layer size, can not be change after init size_t iLayerSize_; // == ic * ih * iw @@ -42,7 +42,7 @@ protected: std::unique_ptr weight_; std::unique_ptr biases_; -public: + public: explicit MKLDNNFcLayer(const LayerConfig& config) : MKLDNNLayer(config), hasInitedWgt_(false) {} @@ -68,7 +68,7 @@ public: void convertWeightsToPaddle() override; -protected: + protected: void resetFwdBuffers(MKLDNNMatrixPtr& in, MKLDNNMatrixPtr& wgt, MKLDNNMatrixPtr& bias, diff --git a/paddle/gserver/layers/MKLDNNLRNLayer.h b/paddle/gserver/layers/MKLDNNLRNLayer.h index b503ee55947294d7c44d1760058f8c26bceed142..028438f2c93b2182318c53cd348351376d491e79 100644 --- a/paddle/gserver/layers/MKLDNNLRNLayer.h +++ b/paddle/gserver/layers/MKLDNNLRNLayer.h @@ -27,7 +27,7 @@ typedef mkldnn::lrn_backward lrn_bwd; * The config file api is mkldnn_lrn */ class MKLDNNLRNLayer : public MKLDNNLayer { -protected: + protected: // save forward primitive_desc, which can be used in backward std::shared_ptr fwdPD_; // according to https://github.com/01org/mkl-dnn/blob/master/tests/gtests/ @@ -37,7 +37,7 @@ protected: int localSize_; float alpha_, beta_; // scale and pow in paddle -public: + public: explicit MKLDNNLRNLayer(const LayerConfig& config) : MKLDNNLayer(config) {} ~MKLDNNLRNLayer() {} @@ -56,7 +56,7 @@ public: std::vector& inputs, MKLDNNMatrixPtr& out) override; -protected: + protected: void resetFwdBuffers(MKLDNNMatrixPtr& in, MKLDNNMatrixPtr& out); void resetFwdPD(std::shared_ptr& pd, MKLDNNMatrixPtr in, diff --git a/paddle/gserver/layers/MKLDNNLayer.h b/paddle/gserver/layers/MKLDNNLayer.h index 4a7eb74ce3a13ed38be3548d8ce34382c594205a..2b164d0d3bc0e1446d7e4d82bb8a713195dbd927 100644 --- a/paddle/gserver/layers/MKLDNNLayer.h +++ b/paddle/gserver/layers/MKLDNNLayer.h @@ -33,7 +33,7 @@ typedef std::shared_ptr MKLDNNLayerPtr; * */ class MKLDNNLayer : public Layer { -protected: + protected: // batch size int bs_; // their sizes are always from the first input layer @@ -95,7 +95,7 @@ protected: // tmp input argument to save input grad, only used to merge grad Argument tmpInArg_; -public: + public: explicit MKLDNNLayer(const LayerConfig& config) : Layer(config), ih_(0), @@ -162,7 +162,7 @@ public: */ void addOutputArgument(int deviceId) { Layer::addOutputArgument(deviceId); } -protected: + protected: /** * Some layers may have different condition to reset the forward. * The function returns the condition that do not need reset forward. @@ -233,7 +233,7 @@ protected: */ void resetMergeGrad(MKLDNNMatrixPtr& out); -protected: + protected: /** * Set deviceId of this layer. */ @@ -340,7 +340,7 @@ protected: } } -private: + private: /** * clear all grad */ diff --git a/paddle/gserver/layers/MKLDNNPoolLayer.h b/paddle/gserver/layers/MKLDNNPoolLayer.h index 12821cda7308602dd2fe834f52c614e6112b7cea..1eb0ee4ad946f61e32b7d4f4fd376dda89d6acf7 100644 --- a/paddle/gserver/layers/MKLDNNPoolLayer.h +++ b/paddle/gserver/layers/MKLDNNPoolLayer.h @@ -27,7 +27,7 @@ typedef mkldnn::pooling_backward pool_bwd; * The config file api is mkldnn_pool */ class MKLDNNPoolLayer : public MKLDNNLayer { -protected: + protected: // padding height and width int ph_, pw_; // stride height and width @@ -44,7 +44,7 @@ protected: // test_pooling_forward.cpp, pool need workspace for backward std::shared_ptr workspace_; -public: + public: explicit MKLDNNPoolLayer(const LayerConfig& config) : MKLDNNLayer(config) {} ~MKLDNNPoolLayer() {} @@ -70,7 +70,7 @@ public: << ", sw: " << sw_; } -protected: + protected: void resetFwdBuffers(MKLDNNMatrixPtr& in, MKLDNNMatrixPtr& out); void resetFwdPD(std::shared_ptr& pd, MKLDNNMatrixPtr in, diff --git a/paddle/gserver/layers/MKLPackedRecurrentLayer.h b/paddle/gserver/layers/MKLPackedRecurrentLayer.h index 37eb362d45215edc736984f8da784fe74bb43f2b..441025a9c9d75786b17db84c74995a96b6a06ea8 100644 --- a/paddle/gserver/layers/MKLPackedRecurrentLayer.h +++ b/paddle/gserver/layers/MKLPackedRecurrentLayer.h @@ -29,7 +29,7 @@ namespace paddle { */ class MKLPackedRecurrentLayer : public RecurrentLayer { -public: + public: explicit MKLPackedRecurrentLayer(const LayerConfig& config) : RecurrentLayer(config) {} @@ -38,7 +38,7 @@ public: void backward(const UpdateCallback& callback) override; -protected: + protected: void forwardBatch(int batchSize, size_t numSequences, const int* starts) override; @@ -47,7 +47,7 @@ protected: size_t numSequences, const int* starts) override; -protected: + protected: /// packed_weight_ contains same data with /// RecurrentLayer::weight_ but is packed std::unique_ptr packed_weight_; diff --git a/paddle/gserver/layers/MKLPackedWeight.h b/paddle/gserver/layers/MKLPackedWeight.h index 28b8a7db7cc3d2be12d6ce9291de1e415cf77bbc..b01a961d007a0e2e343db7b51e50fd3ee776435e 100644 --- a/paddle/gserver/layers/MKLPackedWeight.h +++ b/paddle/gserver/layers/MKLPackedWeight.h @@ -21,7 +21,7 @@ limitations under the License. */ namespace paddle { class MKLPackedWeight { -protected: + protected: /// The pointer of weight real *weight_; /// The pointer of cblas packed gemm to weight @@ -30,7 +30,7 @@ protected: size_t width_; bool transW_; -public: + public: explicit MKLPackedWeight(MatrixPtr weight, bool transW = false) { packedWeight_ = nullptr; weight_ = weight->getData(); @@ -59,7 +59,7 @@ public: dst->getWidth()); } -protected: + protected: void pack_(real *src) { if (!packedWeight_) { packedWeight_ = cblas_sgemm_alloc(CblasBMatrix, 1, width_, height_); diff --git a/paddle/gserver/layers/MaxIdLayer.cpp b/paddle/gserver/layers/MaxIdLayer.cpp index 84e375d7441ce3ccd8a5df94df22d85d104b5d96..eecd4996e962857b09001a1bb36bc027cbaa4308 100644 --- a/paddle/gserver/layers/MaxIdLayer.cpp +++ b/paddle/gserver/layers/MaxIdLayer.cpp @@ -23,11 +23,11 @@ namespace paddle { * The config file api is maxid_layer. */ class MaxIdLayer : public Layer { -private: + private: /// a predetermined number of best states at each level size_t beamSize_; -public: + public: explicit MaxIdLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/MaxLayer.h b/paddle/gserver/layers/MaxLayer.h index 9dbc672652dc2670a775f02ecd3a9de9919c8ae0..e46f997c342ce5d6b724629dff6950c4f1680ce8 100644 --- a/paddle/gserver/layers/MaxLayer.h +++ b/paddle/gserver/layers/MaxLayer.h @@ -39,11 +39,11 @@ namespace paddle { */ class MaxLayer : public SequencePoolLayer { -protected: + protected: // maxIndex_[i][j] = k : the value at (i, j) is from input[k]. IVectorPtr maxIndex_; -public: + public: explicit MaxLayer(const LayerConfig& config) : SequencePoolLayer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/MaxOutLayer.h b/paddle/gserver/layers/MaxOutLayer.h index 1fb371836bacb9e02cc32eabfd21bf24165b0734..0eb8674b4c4f3f58b103c6b59ad13931a6992a1b 100644 --- a/paddle/gserver/layers/MaxOutLayer.h +++ b/paddle/gserver/layers/MaxOutLayer.h @@ -29,7 +29,7 @@ namespace paddle { */ class MaxOutLayer : public Layer { -protected: + protected: size_t groups_; size_t imgSizeH_, imgSizeW_; /// outputChannels_ = channels_ / groups_ @@ -38,7 +38,7 @@ protected: size_t featLen_; IVectorPtr maxoutId_; -public: + public: /// return imgSizeH_ * imgSizeW_ * outputChannels_; size_t getSize(); diff --git a/paddle/gserver/layers/MaxPoolWithMaskLayer.h b/paddle/gserver/layers/MaxPoolWithMaskLayer.h index 74cc8acf3515b10257ffb185061344fbcc94a337..c948364f6b83b0de1ee07cc185b69346f5cb1a7e 100644 --- a/paddle/gserver/layers/MaxPoolWithMaskLayer.h +++ b/paddle/gserver/layers/MaxPoolWithMaskLayer.h @@ -23,10 +23,10 @@ namespace paddle { * @brief Basic parent layer of different kinds of pooling */ class MaxPoolWithMaskLayer : public PoolLayer { -protected: + protected: Argument mask_; -public: + public: explicit MaxPoolWithMaskLayer(const LayerConfig& config) : PoolLayer(config) {} diff --git a/paddle/gserver/layers/MixedLayer.h b/paddle/gserver/layers/MixedLayer.h index a1a43c52e4f503178a66ad8aa6c12bec89566081..43ee2bd81854f2dea837734f556c197613f6fdaf 100644 --- a/paddle/gserver/layers/MixedLayer.h +++ b/paddle/gserver/layers/MixedLayer.h @@ -30,7 +30,7 @@ namespace paddle { * The config file api is mixed_layer. */ class MixedLayer : public Layer { -public: + public: explicit MixedLayer(const LayerConfig& config) : Layer(config) {} ~MixedLayer() {} @@ -52,7 +52,7 @@ public: */ LayerStatePtr getState() override; -protected: + protected: std::vector> projections_; std::vector> operators_; /// the matrix size of projection state diff --git a/paddle/gserver/layers/MultiBoxLossLayer.h b/paddle/gserver/layers/MultiBoxLossLayer.h index 9935da56446c1508549906becfd28548d5deecde..a358cded00bb01bfe5d02f9a6d8a24e4b2e51b74 100644 --- a/paddle/gserver/layers/MultiBoxLossLayer.h +++ b/paddle/gserver/layers/MultiBoxLossLayer.h @@ -41,7 +41,7 @@ namespace paddle { */ class MultiBoxLossLayer : public CostLayer { -public: + public: explicit MultiBoxLossLayer(const LayerConfig& config) : CostLayer(config) {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap); @@ -54,7 +54,7 @@ public: void backwardImp(Matrix& outputValue, Argument& label, Matrix& outputGrad) {} -protected: + protected: inline LayerPtr getPriorBoxLayer() { return inputLayers_[0]; } inline LayerPtr getLabelLayer() { return inputLayers_[1]; } inline LayerPtr getLocInputLayer(size_t index) { @@ -64,7 +64,7 @@ protected: return inputLayers_[2 + inputNum_ + index]; } -protected: + protected: size_t numClasses_; real overlapThreshold_; real negPosRatio_; diff --git a/paddle/gserver/layers/MultinomialSampler.h b/paddle/gserver/layers/MultinomialSampler.h index 1f9e818ee5d21188e3bd39d1225912a1a2ae1598..8cbb229f157c0904e63a696f860ec6739d5167c4 100644 --- a/paddle/gserver/layers/MultinomialSampler.h +++ b/paddle/gserver/layers/MultinomialSampler.h @@ -29,7 +29,7 @@ namespace paddle { * The computational complexity of generate one sample is O(1). */ class MultinomialSampler { -public: + public: MultinomialSampler(const real* prob, int size); //! protobuf always using double. @@ -53,7 +53,7 @@ public: return gen1([&g, this]() { return rand_(g); }); } -protected: + protected: /** * @brief Generation * @param[in] rand rand is a real random number distribution diff --git a/paddle/gserver/layers/MultiplexLayer.cpp b/paddle/gserver/layers/MultiplexLayer.cpp index 82857f8c3ef3e39ec451c1f26bac4996c12350a5..43ecc48cd97fb54d8dc4eb1d87ebf60f5aa040d8 100644 --- a/paddle/gserver/layers/MultiplexLayer.cpp +++ b/paddle/gserver/layers/MultiplexLayer.cpp @@ -37,7 +37,7 @@ namespace paddle { */ class MultiplexLayer : public Layer { -protected: + protected: /** * @brief A struct is used to save the copy information, includes input * layer index and copy size. @@ -64,7 +64,7 @@ protected: /// Temporary matrix pointer to point to output data. MatrixPtr tmpDest_; -public: + public: explicit MultiplexLayer(const LayerConfig& config) : Layer(config) {} ~MultiplexLayer() {} @@ -75,7 +75,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -private: + private: /** * @brief Calculate copy info for input layers. */ diff --git a/paddle/gserver/layers/NCELayer.cpp b/paddle/gserver/layers/NCELayer.cpp index d3d7b1fd9ac3c366d11c3060848e89c24a16a70b..cc48fe100f12446f9522078119ae2ead039a82cc 100644 --- a/paddle/gserver/layers/NCELayer.cpp +++ b/paddle/gserver/layers/NCELayer.cpp @@ -54,7 +54,7 @@ class NCELayer : public Layer { IVectorPtr labelIds_; -public: + public: explicit NCELayer(const LayerConfig& config) : Layer(config), numClasses_(config.num_classes()), diff --git a/paddle/gserver/layers/NormLayer.h b/paddle/gserver/layers/NormLayer.h index c89cbbfce9d9e35a6dd300864ee094ef8f9e283a..3807584415f99a7110170748501589dac85eac52 100644 --- a/paddle/gserver/layers/NormLayer.h +++ b/paddle/gserver/layers/NormLayer.h @@ -27,7 +27,7 @@ namespace paddle { * @note Normalize the input in local region */ class NormLayer : public Layer { -public: + public: explicit NormLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -49,12 +49,12 @@ public: * Need to implement in the futrue. */ class ResponseNormLayer : public NormLayer { -protected: + protected: size_t channels_, size_, outputX_, imgSize_, outputY_, imgSizeY_; real scale_, pow_; MatrixPtr denoms_; -public: + public: explicit ResponseNormLayer(const LayerConfig& config) : NormLayer(config) {} bool init(const LayerMap& layerMap, @@ -76,7 +76,7 @@ public: * Cheng-Yang Fu, Alexander C. Berg. SSD: Single Shot MultiBox Detector */ class CrossChannelNormLayer : public NormLayer { -public: + public: explicit CrossChannelNormLayer(const LayerConfig& config) : NormLayer(config) {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap); @@ -85,7 +85,7 @@ public: MatrixPtr createSampleMatrix(MatrixPtr data, size_t iter, size_t spatialDim); MatrixPtr createSpatialMatrix(MatrixPtr data, size_t iter, size_t spatialDim); -protected: + protected: size_t channels_; std::unique_ptr scale_; MatrixPtr scaleDiff_; diff --git a/paddle/gserver/layers/NormProjectionLayer.h b/paddle/gserver/layers/NormProjectionLayer.h index 898b5823a9011c4b66e045c54afba070dd5cf772..64803a1603599f2e393ec772a32d64f4d271fe71 100644 --- a/paddle/gserver/layers/NormProjectionLayer.h +++ b/paddle/gserver/layers/NormProjectionLayer.h @@ -28,7 +28,7 @@ class CMRProjectionNormLayer : public ResponseNormLayer { size_t imgSizeH_, imgSizeW_; size_t outputH_, outputW_; -public: + public: explicit CMRProjectionNormLayer(const LayerConfig& config) : ResponseNormLayer(config) {} @@ -41,7 +41,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -protected: + protected: TensorShape shape_; }; } // namespace paddle diff --git a/paddle/gserver/layers/Operator.h b/paddle/gserver/layers/Operator.h index a620926cccd3004d7bef57976047a190b4b566e2..42d525ef3e4534acea7512d5ecdbe8a0e1d110d9 100644 --- a/paddle/gserver/layers/Operator.h +++ b/paddle/gserver/layers/Operator.h @@ -34,7 +34,7 @@ namespace paddle { * @note: Operator can't have parameters. */ class Operator { -public: + public: static Operator* create(const OperatorConfig& config, bool useGpu); Operator(const OperatorConfig& config, bool useGpu) @@ -81,7 +81,7 @@ public: */ virtual LayerStatePtr getState() { return nullptr; } -protected: + protected: /// Config of operator OperatorConfig config_; bool useGpu_; diff --git a/paddle/gserver/layers/OuterProdLayer.cpp b/paddle/gserver/layers/OuterProdLayer.cpp index 75f4abf93e5db11dc688f8f2e0b2a36bf70fbccc..11a910f3316114b309efe9007a156e842b3d6229 100644 --- a/paddle/gserver/layers/OuterProdLayer.cpp +++ b/paddle/gserver/layers/OuterProdLayer.cpp @@ -28,12 +28,12 @@ namespace paddle { */ class OuterProdLayer : public Layer { -protected: + protected: MatrixPtr tmpMtx0; MatrixPtr tmpRow0; MatrixPtr tmpRow1; -public: + public: explicit OuterProdLayer(const LayerConfig& config) : Layer(config) {} ~OuterProdLayer() {} diff --git a/paddle/gserver/layers/PadLayer.h b/paddle/gserver/layers/PadLayer.h index 7e09d7f8a0d4dfd5300298ad0514b69781d87016..46b8a595978489c630b3ff2429ecb19d7c12521a 100644 --- a/paddle/gserver/layers/PadLayer.h +++ b/paddle/gserver/layers/PadLayer.h @@ -24,7 +24,7 @@ namespace paddle { * the 4th dimenstion according padc_, padh_ and padw_. */ class PadLayer : public Layer { -public: + public: explicit PadLayer(const LayerConfig& config) : Layer(config) {} ~PadLayer() {} @@ -34,7 +34,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -protected: + protected: void setOutDims(const size_t batchSize); void setTensorDim(const size_t batchSize); diff --git a/paddle/gserver/layers/ParameterReluLayer.h b/paddle/gserver/layers/ParameterReluLayer.h index 3725fa4a1199285b703590255af492ebffdaab2c..4553413fcdbecbc83e1f50e8ffbe874fdf05d828 100644 --- a/paddle/gserver/layers/ParameterReluLayer.h +++ b/paddle/gserver/layers/ParameterReluLayer.h @@ -36,7 +36,7 @@ namespace paddle { */ class ParameterReluLayer : public Layer { -protected: + protected: std::unique_ptr weight_; /** @@ -51,7 +51,7 @@ protected: */ size_t partialSum_; -public: + public: explicit ParameterReluLayer(const LayerConfig& config) : Layer(config) {} ~ParameterReluLayer() {} diff --git a/paddle/gserver/layers/Pool3DLayer.h b/paddle/gserver/layers/Pool3DLayer.h index 59ee73f7cb9fb4287c12f3c7d0cacfc812484770..32605f8b7028cfb4909c885e83017a8cffa79575 100644 --- a/paddle/gserver/layers/Pool3DLayer.h +++ b/paddle/gserver/layers/Pool3DLayer.h @@ -26,7 +26,7 @@ namespace paddle { * Pools the input within regions */ class Pool3DLayer : public Layer { -public: + public: explicit Pool3DLayer(const LayerConfig& config) : Layer(config) {} ~Pool3DLayer() {} @@ -36,7 +36,7 @@ public: void backward(const UpdateCallback& callback) override; size_t getSize(); -protected: + protected: int channels_; int sizeX_, sizeY_, sizeZ_; int strideW_, strideH_, strideD_; diff --git a/paddle/gserver/layers/PoolLayer.h b/paddle/gserver/layers/PoolLayer.h index 58d5fb0a095e8326f9b6f9cb2a97bb88022ceed8..99f8f148e2eb00f7e431e7d8c5acbf9e27574017 100644 --- a/paddle/gserver/layers/PoolLayer.h +++ b/paddle/gserver/layers/PoolLayer.h @@ -26,7 +26,7 @@ namespace paddle { * Pools the input within regions */ class PoolLayer : public Layer { -protected: + protected: size_t channels_, sizeX_, stride_, outputX_, imgSize_; int confPadding_; @@ -40,7 +40,7 @@ protected: bool excludeMode_; -public: + public: explicit PoolLayer(const LayerConfig& config) : Layer(config) {} /** diff --git a/paddle/gserver/layers/PoolProjection.h b/paddle/gserver/layers/PoolProjection.h index c99287dbf0f4503c180b9b4e9e46abafa67bf64d..8004cc1550337160b7f022c97a23ed8eb9d43ca4 100644 --- a/paddle/gserver/layers/PoolProjection.h +++ b/paddle/gserver/layers/PoolProjection.h @@ -20,7 +20,7 @@ limitations under the License. */ namespace paddle { class PoolProjection : public Projection { -protected: + protected: size_t imgSizeY_, imgSize_; size_t outputY_, outputX_; size_t strideY_, stride_; @@ -30,7 +30,7 @@ protected: std::string poolType_; bool excludeMode_; -public: + public: PoolProjection(const ProjectionConfig& config, ParameterPtr parameter, bool useGpu); @@ -45,7 +45,7 @@ public: }; class MaxPoolProjection : public PoolProjection { -public: + public: MaxPoolProjection(const ProjectionConfig& config, ParameterPtr parameter, bool useGpu) @@ -56,7 +56,7 @@ public: }; class AvgPoolProjection : public PoolProjection { -public: + public: AvgPoolProjection(const ProjectionConfig& config, ParameterPtr parameter, bool useGpu) diff --git a/paddle/gserver/layers/PoolProjectionLayer.h b/paddle/gserver/layers/PoolProjectionLayer.h index 5a97a7769aaeebcfd4fe2c10d8ac0cc8892f68e3..9ad144cc2ad426caa522bf1061a750d47e64a755 100644 --- a/paddle/gserver/layers/PoolProjectionLayer.h +++ b/paddle/gserver/layers/PoolProjectionLayer.h @@ -24,13 +24,13 @@ namespace paddle { * @brief Basic parent layer of different kinds of pooling */ class PoolProjectionLayer : public PoolLayer { -protected: + protected: size_t imgSizeH_, imgSizeW_; size_t outputH_, outputW_; std::unique_ptr poolProjection_; ProjectionConfig projectionConfig_; -public: + public: explicit PoolProjectionLayer(const LayerConfig& config) : PoolLayer(config) { PoolConfig* conf = projectionConfig_.mutable_pool_conf(); *conf = config_.inputs(0).pool_conf(); diff --git a/paddle/gserver/layers/PowerLayer.cpp b/paddle/gserver/layers/PowerLayer.cpp index 18f650fcdaded5ad7199510594b873fc18c3d7b5..7e8d60db8fe588026c6040099745c3aefd7237b5 100644 --- a/paddle/gserver/layers/PowerLayer.cpp +++ b/paddle/gserver/layers/PowerLayer.cpp @@ -32,10 +32,10 @@ namespace paddle { */ class PowerLayer : public Layer { -protected: + protected: MatrixPtr tmpMtx; -public: + public: explicit PowerLayer(const LayerConfig& config) : Layer(config) {} ~PowerLayer() {} diff --git a/paddle/gserver/layers/PrintLayer.cpp b/paddle/gserver/layers/PrintLayer.cpp index 5a527d598dd5e11ae0b74a32c9b9884e73ed45a8..6fbcc447f92208439bddd14d421d62cab30d81f4 100644 --- a/paddle/gserver/layers/PrintLayer.cpp +++ b/paddle/gserver/layers/PrintLayer.cpp @@ -17,7 +17,7 @@ limitations under the License. */ namespace paddle { class PrintLayer : public Layer { -public: + public: explicit PrintLayer(const LayerConfig& config) : Layer(config) {} void forward(PassType passType) override { diff --git a/paddle/gserver/layers/PriorBox.cpp b/paddle/gserver/layers/PriorBox.cpp index 56a4d942f0fdcb981f52f6ce0f644ec57a0e3c9a..39d2c2d737fa90737635efdb209610e156c8662f 100644 --- a/paddle/gserver/layers/PriorBox.cpp +++ b/paddle/gserver/layers/PriorBox.cpp @@ -28,7 +28,7 @@ namespace paddle { */ class PriorBoxLayer : public Layer { -public: // NOLINT + public: // NOLINT explicit PriorBoxLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap) override; @@ -36,7 +36,7 @@ public: // NOLINT void forward(PassType passType) override; void backward(const UpdateCallback& callback) override {} -protected: // NOLINT + protected: // NOLINT int numPriors_; std::vector minSize_; std::vector maxSize_; diff --git a/paddle/gserver/layers/Projection.h b/paddle/gserver/layers/Projection.h index 1f0b96c79ec7313cd9c5ff9139a455b3269b222b..88a41355cfce711e1e9522655058d0f1198e4e76 100644 --- a/paddle/gserver/layers/Projection.h +++ b/paddle/gserver/layers/Projection.h @@ -37,7 +37,7 @@ namespace paddle { * to output Argument. */ class Projection { -public: + public: static Projection* create(const ProjectionConfig& config, ParameterPtr parameter, bool useGpu); @@ -98,7 +98,7 @@ public: */ size_t getOutputSize() const { return config_.output_size(); } -protected: + protected: /** * Create layer function. Function is called in forward or backward. * \param function, Layer::forward_ or Layer::backward_ @@ -119,7 +119,7 @@ protected: func->init(config); } -protected: + protected: /// Config of projection ProjectionConfig config_; /// Parameter of projection diff --git a/paddle/gserver/layers/ROIPoolLayer.h b/paddle/gserver/layers/ROIPoolLayer.h index b1735e9748dc3956aade010f33303b55d4f9f439..801a9b3aebe6d718ea38b76246a6056891d0b1f6 100644 --- a/paddle/gserver/layers/ROIPoolLayer.h +++ b/paddle/gserver/layers/ROIPoolLayer.h @@ -33,7 +33,7 @@ namespace paddle { */ class ROIPoolLayer : public Layer { -protected: + protected: size_t channels_; size_t width_; size_t height_; @@ -44,7 +44,7 @@ protected: // Since there is no int matrix, use real maxtrix instead. MatrixPtr maxIdxs_; -public: + public: explicit ROIPoolLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/RecurrentLayer.h b/paddle/gserver/layers/RecurrentLayer.h index 8fd4fe6b78ae6474f3cfcec605f25b72af8295bb..94e633e65777aad540738ea67ea1b4e03dd75954 100644 --- a/paddle/gserver/layers/RecurrentLayer.h +++ b/paddle/gserver/layers/RecurrentLayer.h @@ -40,7 +40,7 @@ namespace paddle { */ class RecurrentLayer : public Layer { -public: + public: explicit RecurrentLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -56,7 +56,7 @@ public: LayerStatePtr getState() override; -protected: + protected: /** * @brief If user do not set --rnn_use_batch=true, it will * compute rnn forward one sequence by one sequence in default. @@ -110,7 +110,7 @@ protected: size_t numSequences, const int* starts); -protected: + protected: std::unique_ptr weight_; std::unique_ptr bias_; diff --git a/paddle/gserver/layers/RecurrentLayerGroup.cpp b/paddle/gserver/layers/RecurrentLayerGroup.cpp index 44b57185c5a5fa7703ca477b990a73cdad2c2aa1..6694e8f2996fdd2c98da1507e5fb3b90b271c850 100644 --- a/paddle/gserver/layers/RecurrentLayerGroup.cpp +++ b/paddle/gserver/layers/RecurrentLayerGroup.cpp @@ -27,7 +27,7 @@ namespace paddle { * between RecurrentLayerGroupBegin and RecurrentLayerGroupEnd. */ class RecurrentLayerGroup : public Layer { -public: + public: explicit RecurrentLayerGroup(const LayerConfig& config) : Layer(config) {} void initSubNetwork(NeuralNetwork* rootNetwork, @@ -58,7 +58,7 @@ public: callback(*network_); } -private: + private: std::unique_ptr network_; }; diff --git a/paddle/gserver/layers/ResizeLayer.cpp b/paddle/gserver/layers/ResizeLayer.cpp index 831f4c3b7e103bc51d870cfa44616980adca08e8..d4ae9945934a40719d253d4b53915530423448af 100644 --- a/paddle/gserver/layers/ResizeLayer.cpp +++ b/paddle/gserver/layers/ResizeLayer.cpp @@ -24,7 +24,7 @@ namespace paddle { * resize matrix: (height * width / size) * size */ class ResizeLayer : public Layer { -public: + public: explicit ResizeLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/RotateLayer.h b/paddle/gserver/layers/RotateLayer.h index 3b619921ab741e1236a495e497e18e265bd6e110..7ecbff20167dd95f782f2d61dc34697ab3273934 100644 --- a/paddle/gserver/layers/RotateLayer.h +++ b/paddle/gserver/layers/RotateLayer.h @@ -32,7 +32,7 @@ namespace paddle { */ class RotateLayer : public Layer { -public: + public: explicit RotateLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, const ParameterMap& parameterMap); @@ -40,7 +40,7 @@ public: void forward(PassType passType); void backward(const UpdateCallback& callback = nullptr); -private: + private: int batchSize_; int size_; int height_; diff --git a/paddle/gserver/layers/RowConvLayer.h b/paddle/gserver/layers/RowConvLayer.h index ba0af1de68a5f77d9ffefac6ef5193bb9d1b4f83..3b74df0b1af5caef1a1abd3d3c5b3ae3b67c429b 100644 --- a/paddle/gserver/layers/RowConvLayer.h +++ b/paddle/gserver/layers/RowConvLayer.h @@ -22,7 +22,7 @@ namespace paddle { * \brief Row Convolution Layer. */ class RowConvLayer : public Layer { -public: + public: explicit RowConvLayer(const LayerConfig& config) : Layer(config) {} ~RowConvLayer() {} @@ -32,7 +32,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -protected: + protected: // Row convolution weight, context_lenght_ * fan_out. // fan_out is the size of output feature. std::unique_ptr weight_; diff --git a/paddle/gserver/layers/RowL2NormLayer.cpp b/paddle/gserver/layers/RowL2NormLayer.cpp index 7ff0c9bae927cae2bc6a332bc0bde013e07edd0a..d5e6e10a0276adb74ec31c13d9e8acc77414a85b 100644 --- a/paddle/gserver/layers/RowL2NormLayer.cpp +++ b/paddle/gserver/layers/RowL2NormLayer.cpp @@ -26,12 +26,12 @@ namespace paddle { */ class RowL2NormLayer : public Layer { -protected: + protected: MatrixPtr inSquare_; MatrixPtr l2NormReciprocal_; MatrixPtr dotSum_; -public: + public: explicit RowL2NormLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/SamplingIdLayer.cpp b/paddle/gserver/layers/SamplingIdLayer.cpp index 2edd915d226edfd7e48df1a066d5a6f51f259511..dbce63588126c012e3b9713e8be749e0001ddec7 100644 --- a/paddle/gserver/layers/SamplingIdLayer.cpp +++ b/paddle/gserver/layers/SamplingIdLayer.cpp @@ -31,7 +31,7 @@ class SamplingIdLayer : public Layer { std::uniform_real_distribution rand1_; std::vector tmpCpuInput_; -public: + public: explicit SamplingIdLayer(const LayerConfig& config) : Layer(config), rand1_(0, 1) {} diff --git a/paddle/gserver/layers/ScaleShiftLayer.cpp b/paddle/gserver/layers/ScaleShiftLayer.cpp index 799d1fe51a65da10bef637894931627315daf0a2..8af78a2e27d2b50572f8bdd6e98696f3d1967eb1 100644 --- a/paddle/gserver/layers/ScaleShiftLayer.cpp +++ b/paddle/gserver/layers/ScaleShiftLayer.cpp @@ -30,11 +30,11 @@ namespace paddle { */ class ScaleShiftLayer : public Layer { -protected: + protected: std::unique_ptr scale_; std::unique_ptr offset_; -public: + public: explicit ScaleShiftLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/ScaleSubRegionLayer.h b/paddle/gserver/layers/ScaleSubRegionLayer.h index 6e861be4858cfc21a42ef7293652d5cdf81be5f5..fe431698bc6cd5e52e2c545756b40be8b307e644 100644 --- a/paddle/gserver/layers/ScaleSubRegionLayer.h +++ b/paddle/gserver/layers/ScaleSubRegionLayer.h @@ -29,7 +29,7 @@ namespace paddle { * region. */ class ScaleSubRegionLayer : public Layer { -public: + public: explicit ScaleSubRegionLayer(const LayerConfig& config) : Layer(config) {} ~ScaleSubRegionLayer() {} @@ -40,7 +40,7 @@ public: void backward(const UpdateCallback& callback = nullptr); -protected: + protected: TensorShape shape_; TensorShape indicesShape_; size_t imgH_; diff --git a/paddle/gserver/layers/ScalingLayer.cpp b/paddle/gserver/layers/ScalingLayer.cpp index 1d98a7373d172d40cddc9b4611cb00434f17e00b..15e07daebee194a789da52d37a192e031348300c 100644 --- a/paddle/gserver/layers/ScalingLayer.cpp +++ b/paddle/gserver/layers/ScalingLayer.cpp @@ -32,7 +32,7 @@ namespace paddle { */ class ScalingLayer : public Layer { -public: + public: explicit ScalingLayer(const LayerConfig& config) : Layer(config) {} ~ScalingLayer() {} diff --git a/paddle/gserver/layers/ScalingProjection.cpp b/paddle/gserver/layers/ScalingProjection.cpp index 99b5b68f543842d23f20b626fddd66b677ebe059..4d871cafc4d0194a61044d76a766236209c33d47 100644 --- a/paddle/gserver/layers/ScalingProjection.cpp +++ b/paddle/gserver/layers/ScalingProjection.cpp @@ -17,7 +17,7 @@ limitations under the License. */ namespace paddle { class ScalingProjection : public Projection { -public: + public: ScalingProjection(const ProjectionConfig& config, const ParameterPtr& parameter, bool useGpu) @@ -48,7 +48,7 @@ public: } } -protected: + protected: std::unique_ptr weight_; }; diff --git a/paddle/gserver/layers/SelectiveFullyConnectedLayer.h b/paddle/gserver/layers/SelectiveFullyConnectedLayer.h index 81564074185a5d9fc80d4d3a64af998098ab5472..4b32ce8b162c2a8b1a6c34adc0885a7701f5f91e 100644 --- a/paddle/gserver/layers/SelectiveFullyConnectedLayer.h +++ b/paddle/gserver/layers/SelectiveFullyConnectedLayer.h @@ -33,11 +33,11 @@ namespace paddle { * The config file api is selective_fc_layer. */ class SelectiveFullyConnectedLayer : public Layer { -protected: + protected: WeightList weights_; std::unique_ptr biases_; -private: + private: /** * Get selected columns each forward. */ @@ -60,7 +60,7 @@ private: /// if true, means output_.value is the same as Fc Layer bool fullOutput_; -public: + public: explicit SelectiveFullyConnectedLayer(const LayerConfig& config) : Layer(config), selCols_(nullptr) {} @@ -94,7 +94,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -private: + private: /** * @brief Make SelectiveFC act as FullyConnectedLayer */ diff --git a/paddle/gserver/layers/SequenceConcatLayer.cpp b/paddle/gserver/layers/SequenceConcatLayer.cpp index cf573f3f33fcd70c6768b164f158cb1f545414fc..c84c3ce4f080cc19f4937f04585accb5b2b347f9 100644 --- a/paddle/gserver/layers/SequenceConcatLayer.cpp +++ b/paddle/gserver/layers/SequenceConcatLayer.cpp @@ -29,10 +29,10 @@ namespace paddle { */ class SequenceConcatLayer : public Layer { -protected: + protected: std::unique_ptr biases_; -public: + public: explicit SequenceConcatLayer(const LayerConfig& config) : Layer(config) {} ~SequenceConcatLayer() {} diff --git a/paddle/gserver/layers/SequenceLastInstanceLayer.cpp b/paddle/gserver/layers/SequenceLastInstanceLayer.cpp index 6c4ae775c16ac76e237fb8f8ee5ec9ed8f11802e..28d0a9296d4accd4152e886ccae12a776fdb8f7f 100644 --- a/paddle/gserver/layers/SequenceLastInstanceLayer.cpp +++ b/paddle/gserver/layers/SequenceLastInstanceLayer.cpp @@ -38,12 +38,12 @@ namespace paddle { */ class SequenceLastInstanceLayer : public SequencePoolLayer { -protected: + protected: MatrixPtr tmpSrc_; MatrixPtr tmpDest_; std::vector instanceIds_; -public: + public: explicit SequenceLastInstanceLayer(const LayerConfig& config) : SequencePoolLayer(config) {} diff --git a/paddle/gserver/layers/SequencePoolLayer.h b/paddle/gserver/layers/SequencePoolLayer.h index 254e4cc6b3aacf21565cb03e5bdb52a2beb9fea8..01183060afd58376bb718dda64d8106cce4899f9 100644 --- a/paddle/gserver/layers/SequencePoolLayer.h +++ b/paddle/gserver/layers/SequencePoolLayer.h @@ -41,7 +41,7 @@ namespace paddle { */ class SequencePoolLayer : public Layer { -protected: + protected: int type_; std::unique_ptr biases_; enum SequenceLevel { kNonSeq = 0, kSeq = 1 }; @@ -51,7 +51,7 @@ protected: // Whether the input sequence is reversed or not. bool reversed_ = false; -public: + public: explicit SequencePoolLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/SequenceReshapeLayer.cpp b/paddle/gserver/layers/SequenceReshapeLayer.cpp index fb96669917236b98809f1cda0d023600f1e76731..319310af8c4ac3bdefd814ad05b7fde6070f2340 100644 --- a/paddle/gserver/layers/SequenceReshapeLayer.cpp +++ b/paddle/gserver/layers/SequenceReshapeLayer.cpp @@ -29,12 +29,12 @@ namespace paddle { */ class SequenceReshapeLayer : public Layer { -protected: + protected: std::unique_ptr biases_; MatrixPtr reshapedOutputGrad; -public: + public: explicit SequenceReshapeLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/SequenceSliceLayer.cpp b/paddle/gserver/layers/SequenceSliceLayer.cpp index 1b7c33477ea64c1cdb7c8e85d7a5302b299d7552..a6d810b583aab6e44faa583795686f06e17beeb9 100644 --- a/paddle/gserver/layers/SequenceSliceLayer.cpp +++ b/paddle/gserver/layers/SequenceSliceLayer.cpp @@ -21,7 +21,7 @@ limitations under the License. */ namespace paddle { class SequenceSliceLayer : public Layer { -public: + public: explicit SequenceSliceLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -30,7 +30,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -private: + private: /* * TODO(caoying) * In PaddePaddle, currently all matrices are real number types, diff --git a/paddle/gserver/layers/SequenceToBatch.h b/paddle/gserver/layers/SequenceToBatch.h index 8743a5ef10f61970d3d48b105b9da29bcd10ba83..5200e702d9bc947746567c19ca7d552750828131 100644 --- a/paddle/gserver/layers/SequenceToBatch.h +++ b/paddle/gserver/layers/SequenceToBatch.h @@ -39,7 +39,7 @@ namespace paddle { * */ class SequenceToBatch { -public: + public: explicit SequenceToBatch(bool useGpu) : useGpu_(useGpu) {} /* resize and calculate the batchIndex_ */ @@ -82,7 +82,7 @@ public: numBatch_ = seq2batch.numBatch_; } -protected: + protected: void sequence2BatchCopy(Matrix &batch, Matrix &sequence, IVector &seq2BatchIdx, diff --git a/paddle/gserver/layers/SliceProjection.cpp b/paddle/gserver/layers/SliceProjection.cpp index 5627ad1eb3a49a73261bc2197cbd3735489509d2..b474f2db759adfad337f9485a5a38588b6839c54 100644 --- a/paddle/gserver/layers/SliceProjection.cpp +++ b/paddle/gserver/layers/SliceProjection.cpp @@ -44,14 +44,14 @@ namespace paddle { * The config file api is slice_projection. */ class SliceProjection : public Projection { -public: + public: SliceProjection(const ProjectionConfig& config, const ParameterPtr& parameter, bool useGpu); virtual void forward(); virtual void backward(const UpdateCallback& callback); -protected: + protected: std::vector> slices_; }; diff --git a/paddle/gserver/layers/SlopeInterceptLayer.cpp b/paddle/gserver/layers/SlopeInterceptLayer.cpp index c94a07e5da7442bba1ce7e9c09c4ffea3e5cd4ac..f7f4735c1b72d4ac6540714573fd7e15ef99ea5b 100644 --- a/paddle/gserver/layers/SlopeInterceptLayer.cpp +++ b/paddle/gserver/layers/SlopeInterceptLayer.cpp @@ -36,7 +36,7 @@ namespace paddle { */ class SlopeInterceptLayer : public Layer { -public: + public: explicit SlopeInterceptLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/SpatialPyramidPoolLayer.h b/paddle/gserver/layers/SpatialPyramidPoolLayer.h index 6cb5fdf83e2b88ce4adb392807a1fdbac253c51c..421bdfe09c46f656f500daff195c755274bf8bb7 100644 --- a/paddle/gserver/layers/SpatialPyramidPoolLayer.h +++ b/paddle/gserver/layers/SpatialPyramidPoolLayer.h @@ -29,7 +29,7 @@ namespace paddle { */ class SpatialPyramidPoolLayer : public Layer { -protected: + protected: size_t channels_; size_t imgSizeW_; size_t imgSizeH_; @@ -40,7 +40,7 @@ protected: std::vector projOutput_; std::vector> projCol_; -public: + public: explicit SpatialPyramidPoolLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/SubNestedSequenceLayer.cpp b/paddle/gserver/layers/SubNestedSequenceLayer.cpp index db240ab0c96510263d90b291f6396ac51a73fbbd..e2bb00bbfacb26dc736a63877119b379f22b5983 100644 --- a/paddle/gserver/layers/SubNestedSequenceLayer.cpp +++ b/paddle/gserver/layers/SubNestedSequenceLayer.cpp @@ -21,7 +21,7 @@ limitations under the License. */ namespace paddle { class SubNestedSequenceLayer : public Layer { -public: + public: explicit SubNestedSequenceLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -30,7 +30,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback = nullptr) override; -private: + private: /* * This functions generates the indices of rows in a batch according to the * indices of selected sub-sequence in each sequence. diff --git a/paddle/gserver/layers/SubSequenceLayer.cpp b/paddle/gserver/layers/SubSequenceLayer.cpp index 808627f09273950bb6f52a4a6e497bcb8ea170f7..ba49f5710f9d0bb985cf1e80d5c4a972d8f046a6 100644 --- a/paddle/gserver/layers/SubSequenceLayer.cpp +++ b/paddle/gserver/layers/SubSequenceLayer.cpp @@ -27,12 +27,12 @@ namespace paddle { */ class SubSequenceLayer : public Layer { -protected: + protected: std::unique_ptr biases_; MatrixPtr tmpSrc_; MatrixPtr tmpDest_; -public: + public: explicit SubSequenceLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/SumToOneNormLayer.cpp b/paddle/gserver/layers/SumToOneNormLayer.cpp index ffbe14925300ad1ffbd33f43a6c0afadddd231e6..00764717e8b6be30230e44626974033e929352da 100644 --- a/paddle/gserver/layers/SumToOneNormLayer.cpp +++ b/paddle/gserver/layers/SumToOneNormLayer.cpp @@ -32,13 +32,13 @@ namespace paddle { */ class SumToOneNormLayer : public Layer { -protected: + protected: /// reciprocalRowSum_ = \f$1 / \sum_{k=1}^N in[k]\f$ MatrixPtr reciprocalRowSum_; /// dotSum = output_.grad \f$.*\f$ output_.value MatrixPtr dotSum_; -public: + public: explicit SumToOneNormLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/SwitchOrderLayer.h b/paddle/gserver/layers/SwitchOrderLayer.h index 882437f4434c2e61a5b08328d2f79c1e7f589204..8a551a2bba698374841e73dc4dbad403034dd300 100644 --- a/paddle/gserver/layers/SwitchOrderLayer.h +++ b/paddle/gserver/layers/SwitchOrderLayer.h @@ -22,7 +22,7 @@ namespace paddle { * \brief This layer calculate softmax in image channel dimension. */ class SwitchOrderLayer : public Layer { -public: + public: explicit SwitchOrderLayer(const LayerConfig& config) : Layer(config) {} ~SwitchOrderLayer() {} @@ -34,7 +34,7 @@ public: void setInDims(); void setOutDims(); -protected: + protected: std::vector> nchw2nhwc_; std::vector> nhwc2nchw_; TensorShape inDims_; diff --git a/paddle/gserver/layers/TableProjection.h b/paddle/gserver/layers/TableProjection.h index ffb05e68f068a7b9abb0db5cea6133e64300cb55..60286149f4227fbc758dca7864c6d1f67782c7ae 100644 --- a/paddle/gserver/layers/TableProjection.h +++ b/paddle/gserver/layers/TableProjection.h @@ -32,7 +32,7 @@ namespace paddle { * @note If \f$ids[i] = -1\f$, it will be ignored. */ class TableProjection : public Projection { -public: + public: TableProjection(const ProjectionConfig& config, const ParameterPtr& parameter, bool useGpu); @@ -43,7 +43,7 @@ public: virtual void forward(); virtual void backward(const UpdateCallback& callback); -protected: + protected: std::unique_ptr table_; }; diff --git a/paddle/gserver/layers/TensorLayer.h b/paddle/gserver/layers/TensorLayer.h index 8a323aa15f6f3761c45b6ca7e3be8f15621a189e..5c1ee40ceda9387138a82368ec4edcbae4bd3419 100644 --- a/paddle/gserver/layers/TensorLayer.h +++ b/paddle/gserver/layers/TensorLayer.h @@ -37,11 +37,11 @@ namespace paddle { */ class TensorLayer : public Layer { -protected: + protected: WeightList weights_; std::unique_ptr biases_; -public: + public: explicit TensorLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/TransLayer.h b/paddle/gserver/layers/TransLayer.h index 03d094862459c80aee8899c0352ffce732db08af..1cd8fd91f785d5a43fc7d7663e657702b32fa534 100644 --- a/paddle/gserver/layers/TransLayer.h +++ b/paddle/gserver/layers/TransLayer.h @@ -29,7 +29,7 @@ namespace paddle { * The config file api is trans_layer. */ class TransLayer : public Layer { -public: + public: explicit TransLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, diff --git a/paddle/gserver/layers/TransposedFullMatrixProjection.cpp b/paddle/gserver/layers/TransposedFullMatrixProjection.cpp index 755389f7074c252c0fad396e629c6ffedc74b531..45f59779896f993aface284e3485e1e3d801f4c5 100644 --- a/paddle/gserver/layers/TransposedFullMatrixProjection.cpp +++ b/paddle/gserver/layers/TransposedFullMatrixProjection.cpp @@ -24,14 +24,14 @@ namespace paddle { * The config file api is trans_full_matrix_projection. */ class TransposedFullMatrixProjection : public Projection { -public: + public: TransposedFullMatrixProjection(const ProjectionConfig& config, ParameterPtr parameter, bool useGPu); virtual void forward(); virtual void backward(const UpdateCallback& callback); -protected: + protected: std::unique_ptr weight_; }; diff --git a/paddle/gserver/layers/UpsampleLayer.h b/paddle/gserver/layers/UpsampleLayer.h index 25efbac5e9e6e92653f7c2b2f4dca9221737e5d6..c9d079c3141c37517866bfdad10d9b2cdb89f7d5 100644 --- a/paddle/gserver/layers/UpsampleLayer.h +++ b/paddle/gserver/layers/UpsampleLayer.h @@ -30,7 +30,7 @@ namespace paddle { */ class UpsampleLayer : public Layer { -public: + public: explicit UpsampleLayer(const LayerConfig& config) : Layer(config) {} ~UpsampleLayer() {} @@ -42,7 +42,7 @@ public: size_t getOutputSize(); -protected: + protected: size_t scale_, scaleY_; size_t upsampleSize_, upsampleSizeY_; size_t padOutX_, padOutY_; diff --git a/paddle/gserver/layers/ValidationLayer.h b/paddle/gserver/layers/ValidationLayer.h index f412d685c0541537bd4318fec2dae06215c4afbe..be41128ef4530f32a63c757648c2f393fd118ea6 100644 --- a/paddle/gserver/layers/ValidationLayer.h +++ b/paddle/gserver/layers/ValidationLayer.h @@ -23,7 +23,7 @@ DECLARE_int32(trainer_id); namespace paddle { class ValidationLayer : public Layer { -public: + public: explicit ValidationLayer(const LayerConfig& config) : Layer(config) {} bool init(const LayerMap& layerMap, @@ -51,7 +51,7 @@ public: * AucValidation */ class AucValidation : public ValidationLayer { -public: + public: explicit AucValidation(const LayerConfig& config) : ValidationLayer(config), cpuOutput_(nullptr), @@ -72,7 +72,7 @@ public: }; std::vector predictArray_; -private: + private: bool passBegin_; std::unique_ptr evaluator_; MatrixPtr cpuOutput_; @@ -84,7 +84,7 @@ private: * positive-negative pair rate Validation */ class PnpairValidation : public ValidationLayer { -public: + public: explicit PnpairValidation(const LayerConfig& config) : ValidationLayer(config) {} @@ -95,7 +95,7 @@ public: void onPassEnd() override; -private: + private: bool passBegin_; std::unique_ptr evaluator_; }; diff --git a/paddle/gserver/layers/WarpCTCLayer.h b/paddle/gserver/layers/WarpCTCLayer.h index 6f6be359c0aa46a4f3775f8405e1aa51ca1ae147..3017ca794ecc14f5a3cbd0b302a4953a191a5065 100644 --- a/paddle/gserver/layers/WarpCTCLayer.h +++ b/paddle/gserver/layers/WarpCTCLayer.h @@ -26,7 +26,7 @@ namespace paddle { * The config file api is warp_ctc_layer. */ class WarpCTCLayer : public Layer { -public: + public: explicit WarpCTCLayer(const LayerConfig& config) : Layer(config) {} ~WarpCTCLayer() {} @@ -35,7 +35,7 @@ public: void forward(PassType passType) override; void backward(const UpdateCallback& callback) override; -protected: + protected: /** * sequence matrix and batch matrix copy: * sequence (s0, s0, s0, s0; s1, s1; s2, s2, s2; s3) @@ -49,7 +49,7 @@ protected: const ICpuGpuVectorPtr& seqStartPositions, bool normByTimes); -protected: + protected: size_t numClasses_; size_t blank_; size_t maxSequenceLength_; diff --git a/paddle/gserver/tests/MKLDNNTester.h b/paddle/gserver/tests/MKLDNNTester.h index c1faa6fd90e06d8c742e97c9ce51eeba3c24a550..41ac46b70ab08d4071f4e6abfca94667268015d7 100644 --- a/paddle/gserver/tests/MKLDNNTester.h +++ b/paddle/gserver/tests/MKLDNNTester.h @@ -44,7 +44,7 @@ class MKLDNNTester { std::vector paraValues; }; -protected: + protected: std::vector configs_; vector layerNames_; vector> dataLayers_; @@ -65,7 +65,7 @@ protected: /// passType, PASS_TRAIN, PASS_TEST or PASS_GC (Gradient Check pass) PassType passType_; -public: + public: explicit MKLDNNTester(size_t iter = 3, float epsilon = 1e-4) { iter_ = iter; eps_ = epsilon; @@ -75,7 +75,7 @@ public: ~MKLDNNTester() {} -public: + public: void run(const TestConfig& dnn, const TestConfig& ref, size_t batchSize, @@ -97,7 +97,7 @@ public: bool use_mkldnn, size_t iter = 2); -private: + private: void reset(const TestConfig& dnn, const TestConfig& ref, size_t batchSize); void setInputImgSize(); void runOnce(); diff --git a/paddle/gserver/tests/test_MultinomialSampler.cpp b/paddle/gserver/tests/test_MultinomialSampler.cpp index 4a295ea9d51788f988fe79f8439cc7769f661d8e..043025239e744601cbef3ca5c241509872963bd8 100644 --- a/paddle/gserver/tests/test_MultinomialSampler.cpp +++ b/paddle/gserver/tests/test_MultinomialSampler.cpp @@ -27,7 +27,7 @@ using namespace paddle; // NOLINT using namespace std; // NOLINT class MultinomialSamplerTester : public MultinomialSampler { -public: + public: MultinomialSamplerTester(real* prob, int size) : MultinomialSampler(prob, size) {} diff --git a/paddle/gserver/tests/test_RecurrentGradientMachine.cpp b/paddle/gserver/tests/test_RecurrentGradientMachine.cpp index 72324fcf29cc60867005da25b35a8075fd590a89..9770567b88a2af946b30439300540ed61694ba10 100644 --- a/paddle/gserver/tests/test_RecurrentGradientMachine.cpp +++ b/paddle/gserver/tests/test_RecurrentGradientMachine.cpp @@ -26,7 +26,7 @@ DECLARE_int32(seed); using namespace paddle; // NOLINT using namespace std; // NOLINT class TrainerForTest : public paddle::Trainer { -public: + public: void startTrain() { GradientMachine& gm = *this->trainerInternal_.getGradientMachine(); gm.start(); diff --git a/paddle/gserver/tests/test_RecurrentLayer.cpp b/paddle/gserver/tests/test_RecurrentLayer.cpp index e5ce922f15749cb18b93f64e0e08f437c5633065..b54e37b7dbf8bffeb949f709e6a4f9ec86ea13c3 100644 --- a/paddle/gserver/tests/test_RecurrentLayer.cpp +++ b/paddle/gserver/tests/test_RecurrentLayer.cpp @@ -225,7 +225,7 @@ TEST(Layer, RecurrentLayer) { #include "paddle/gserver/layers/RecurrentLayer.h" template class TestRecurrentLayer { -public: + public: LayerConfig config_; bool useGpu_; bool useBatch_; diff --git a/paddle/math/Allocator.h b/paddle/math/Allocator.h index ae60f6fe5fa142bdffeafc31b5816b8fcc94ad5c..c43a83891eb6b7eae278169736149ad1d89e950e 100644 --- a/paddle/math/Allocator.h +++ b/paddle/math/Allocator.h @@ -27,7 +27,7 @@ namespace paddle { * This is the base class of all Allocator class. */ class Allocator { -public: + public: virtual ~Allocator() {} virtual void* alloc(size_t size) = 0; virtual void free(void* ptr) = 0; @@ -38,7 +38,7 @@ public: * @brief CPU allocator implementation. */ class CpuAllocator : public Allocator { -public: + public: ~CpuAllocator() {} /** @@ -76,7 +76,7 @@ public: * @brief GPU allocator implementation. */ class GpuAllocator : public Allocator { -public: + public: ~GpuAllocator() {} /** @@ -107,7 +107,7 @@ public: * @brief CPU pinned memory allocator implementation. */ class CudaHostAllocator : public Allocator { -public: + public: ~CudaHostAllocator() {} /** diff --git a/paddle/math/BaseMatrix.h b/paddle/math/BaseMatrix.h index 00ce5a19491048f3339d608ac37669816a9ad3f5..1958629aa0354fcc332b1e5677a64c29397e0d26 100644 --- a/paddle/math/BaseMatrix.h +++ b/paddle/math/BaseMatrix.h @@ -43,7 +43,7 @@ typedef bool_constant true_type; address += row * ld + col; class MatrixOffset { -public: + public: size_t aCol_; size_t aRow_; size_t bCol_; @@ -72,14 +72,14 @@ public: template class BaseMatrixT : public TensorExpression, T> { -public: + public: size_t height_, width_; size_t stride_; T* data_; bool trans_; bool useGpu_; -public: + public: virtual ~BaseMatrixT() {} BaseMatrixT(size_t height, size_t width, T* data, bool trans, bool useGpu) : height_(height), diff --git a/paddle/math/CpuSparseMatrix.h b/paddle/math/CpuSparseMatrix.h index 22b6b71688bd555cf8bf8a29088ad01b092d67cf..172792c2950ce56281715cb7f3eb076da252d77e 100644 --- a/paddle/math/CpuSparseMatrix.h +++ b/paddle/math/CpuSparseMatrix.h @@ -22,7 +22,7 @@ limitations under the License. */ namespace paddle { class CpuSparseMatrix : public Matrix { -public: + public: CpuSparseMatrix(size_t height, size_t width, size_t nnz, /* used to allocate space */ @@ -291,10 +291,10 @@ public: LOG(FATAL) << "not supported!"; } -private: + private: MatrixPtr clone(size_t height = 0, size_t width = 0, bool useGpu = false); -protected: + protected: void sparseResize(); /*for csr , record row start position, for csc, record row index for every no * zero value*/ @@ -310,10 +310,10 @@ protected: static ThreadLocal> cpuLocalMats_; // BaseMatrixT interface -public: + public: bool isSparse() const { return true; } -private: + private: using Matrix::mul; using Matrix::copyFrom; using Matrix::rowMax; @@ -329,7 +329,7 @@ private: namespace paddle { class CpuSparseMatrix : public Matrix { -public: + public: CpuSparseMatrix(size_t height, size_t width, size_t nnz, /* used to allocate space */ diff --git a/paddle/math/ExecViaCpu.h b/paddle/math/ExecViaCpu.h index 9b2a3c2b8accd384aac896e86ef8315a744633e1..ec2337545e9e3efdf31d3d786a096a67283715f2 100644 --- a/paddle/math/ExecViaCpu.h +++ b/paddle/math/ExecViaCpu.h @@ -31,17 +31,17 @@ namespace paddle { template class CopyToCpu { -public: + public: explicit CopyToCpu(Arg& arg) : arg_(arg) {} Arg& copiedArg() const { return arg_; } -private: + private: Arg& arg_; }; template <> class CopyToCpu { -public: + public: explicit CopyToCpu(Matrix& arg) : arg_(arg) { if (arg.useGpu()) { CHECK(!arg.isTransposed()) << "Not supported"; @@ -59,14 +59,14 @@ public: } Matrix& copiedArg() const { return copied_ ? *copied_ : arg_; } -private: + private: Matrix& arg_; MatrixPtr copied_; }; template <> class CopyToCpu { -public: + public: explicit CopyToCpu(const Matrix& arg) : arg_(arg) { if (arg.useGpu()) { CHECK(!arg.isTransposed()) << "Not supported"; @@ -79,14 +79,14 @@ public: } const Matrix& copiedArg() const { return copied_ ? *copied_ : arg_; } -private: + private: const Matrix& arg_; MatrixPtr copied_; }; template <> class CopyToCpu { -public: + public: explicit CopyToCpu(IVector& arg) : arg_(arg) { if (arg.useGpu()) { copied_ = IVector::create(arg.getSize(), /* useGpu= */ false); @@ -100,14 +100,14 @@ public: } IVector& copiedArg() const { return copied_ ? *copied_ : arg_; } -private: + private: IVector& arg_; IVectorPtr copied_; }; template <> class CopyToCpu { -public: + public: explicit CopyToCpu(const IVector& arg) : arg_(arg) { if (arg.useGpu()) { copied_ = IVector::create(arg.getSize(), /* useGpu= */ false); @@ -116,7 +116,7 @@ public: } const IVector& copiedArg() const { return copied_ ? *copied_ : arg_; } -private: + private: const IVector& arg_; IVectorPtr copied_; }; @@ -128,7 +128,7 @@ class GpuFuncWrapperImp; template class GpuFuncWrapperBase { -public: + public: typedef R ResultType; R operator()(F&& f, Args... args) { return f(CopyToCpu::type>(args) diff --git a/paddle/math/MKLDNNMatrix.h b/paddle/math/MKLDNNMatrix.h index e1fb81679adf4658a58ceee73c8d5da6c0b61050..d4a78f3e54b73add3c00e17f13d91359839d3d14 100644 --- a/paddle/math/MKLDNNMatrix.h +++ b/paddle/math/MKLDNNMatrix.h @@ -35,7 +35,7 @@ typedef std::shared_ptr MKLDNNMatrixPtr; * */ class MKLDNNMatrix : public CpuMatrix, public mkldnn::memory { -public: + public: MKLDNNMatrix(CpuMatrixPtr m, mkldnn::memory::primitive_desc pd) : CpuMatrix(m->getData(), m->getHeight(), m->getWidth(), false), mkldnn::memory(pd, m->getData()), @@ -107,7 +107,7 @@ public: dst.copyFrom(*m_); } -public: + public: /** * Reorder this MKLDNNMatrix from other format. * Support inplace reorder. @@ -226,7 +226,7 @@ public: */ mkldnn::engine getEngine() { return getPrimitiveDesc().get_engine(); } -protected: + protected: /** * Do reorder once. * Can support inplace. @@ -248,7 +248,7 @@ protected: set_data_handle(data); } -private: + private: // save the CpuMatrixPtr in case the buffer released outside CpuMatrixPtr m_; }; diff --git a/paddle/math/Matrix.h b/paddle/math/Matrix.h index 04e9614eabc47c4c661ace2106e8ca96f45a1d49..4c3b2c95361065372f5969a2da73bce0eb9d123f 100644 --- a/paddle/math/Matrix.h +++ b/paddle/math/Matrix.h @@ -77,7 +77,7 @@ typedef std::shared_ptr CpuSparseMatrixPtr; * instead. */ class Matrix : public BaseMatrix { -protected: + protected: Matrix(MemoryHandlePtr memHandle, size_t height, size_t width, @@ -95,11 +95,11 @@ protected: static ThreadLocal tmpMat_; -public: + public: size_t elementCnt_; // maximal number of elements which can be held in data_ MemoryHandlePtr memoryHandle_; -public: + public: virtual ~Matrix() {} static MatrixPtr create(MemoryHandlePtr memHandle, @@ -412,7 +412,7 @@ public: LOG(FATAL) << "Not implemented"; } -public: + public: /// Only set all variables to 0 or NULL but not free them. virtual void clear() { height_ = 0; @@ -1228,7 +1228,7 @@ inline std::ostream& operator<<(std::ostream& os, const Matrix& mat) { } class GpuMatrix : public Matrix { -public: + public: GpuMatrix(); GpuMatrix(size_t height, size_t width, bool trans = false); @@ -1660,11 +1660,11 @@ public: }; class CpuMatrix : public Matrix { -private: + private: MatrixPtr sftmaxSum_; MatrixPtr sftmaxDot_; -public: + public: CpuMatrix(size_t height, size_t width, bool trans = false); CpuMatrix(real* data, size_t height, size_t width, bool trans = false) : Matrix(data, height, width, trans, false) {} @@ -1892,7 +1892,7 @@ public: real* getRow(size_t row) { return BaseMatrix::rowBuf(row); } virtual real* getRowBuf(size_t row) { return getRow(row); } -public: + public: /// add b to each sample of this. void addBias(Matrix& b, real scale); void addSharedBias(Matrix& b, real scale); @@ -2128,7 +2128,7 @@ public: }; class SharedCpuMatrix : public CpuMatrix { -public: + public: #ifndef PADDLE_MOBILE_INFERENCE /* blockNum is number of partitions of the matrix */ SharedCpuMatrix(int blockNum, size_t height, size_t width, bool trans = false) @@ -2160,12 +2160,12 @@ public: ~SharedCpuMatrix() {} -public: + public: virtual void mul(CpuSparseMatrix* a, CpuMatrix* b, real scaleAB, real scaleT); virtual void add(Matrix& b, real p1, real p2); virtual void add(real p1, real p2); -private: + private: using Matrix::mul; void initShared(int blockNum); void initBlock(int blockNum); diff --git a/paddle/math/MatrixBitCode.cpp b/paddle/math/MatrixBitCode.cpp index 61a9923bc2e6f358738f80de4a30d83c0cc00656..f7a949294b54a5a874e1239a13ca9dce3ba18e94 100644 --- a/paddle/math/MatrixBitCode.cpp +++ b/paddle/math/MatrixBitCode.cpp @@ -27,7 +27,7 @@ struct SimpleCode { inline bool calcBit(int bit) const { return c_ & (1 << bit); } inline int getLength() const { return findLastSet(c_) - 1; } -private: + private: size_t c_; }; @@ -39,7 +39,7 @@ struct SimpleCodeTable { size_t size() const { return numClasses_; } int getMaxCodeLength() const { return findLastSet(numClasses_ - 1); } -private: + private: size_t numClasses_; int maxCodeLength_; }; diff --git a/paddle/math/MemoryHandle.h b/paddle/math/MemoryHandle.h index 03ee413c1218376635c4696ebb774c584aa67aa4..516e09dbed47ac6b039ccb094614c9588eeb3cd5 100644 --- a/paddle/math/MemoryHandle.h +++ b/paddle/math/MemoryHandle.h @@ -20,16 +20,16 @@ limitations under the License. */ namespace paddle { class MemoryHandle { -protected: + protected: explicit MemoryHandle(size_t size); virtual ~MemoryHandle() {} -public: + public: void* getBuf() const { return buf_; } size_t getSize() const { return size_; } size_t getAllocSize() const { return allocSize_; } -protected: + protected: PoolAllocator* allocator_; size_t size_; // the requested size size_t allocSize_; // the allocated size @@ -43,7 +43,7 @@ protected: * The raw handle will be released at destructor */ class GpuMemoryHandle : public MemoryHandle { -public: + public: explicit GpuMemoryHandle(size_t size); virtual ~GpuMemoryHandle(); }; @@ -54,7 +54,7 @@ public: * The raw handle will be released at destructor */ class CpuMemoryHandle : public MemoryHandle { -public: + public: explicit CpuMemoryHandle(size_t size); virtual ~CpuMemoryHandle(); }; diff --git a/paddle/math/PoolAllocator.h b/paddle/math/PoolAllocator.h index 90141fef3fd43fe221874cc50e688f6db9e2dee6..7239cf1c4494e207081e325a7e6067ba26a9c852 100644 --- a/paddle/math/PoolAllocator.h +++ b/paddle/math/PoolAllocator.h @@ -27,7 +27,7 @@ namespace paddle { * @brief Memory pool allocator implementation. */ class PoolAllocator { -public: + public: /** * @brief constructor. * @param allocator a Allocator object. @@ -47,7 +47,7 @@ public: void free(void* ptr, size_t size); std::string getName() { return name_; } -private: + private: void freeAll(); void printAll(); std::unique_ptr allocator_; diff --git a/paddle/math/RowBuffer.h b/paddle/math/RowBuffer.h index 2e4d11a86bf8bd1308b2972f549bc7c201044785..6950afaa21d60615b27c06a151b0afbb296653bf 100644 --- a/paddle/math/RowBuffer.h +++ b/paddle/math/RowBuffer.h @@ -26,7 +26,7 @@ namespace paddle { * If not set memory handler, then the data could be auto growth. */ class RowBuffer { -public: + public: /** * @brief RowBuffer create a auto-growth row buffer. The row length is width. * @param width the length of each row, a.k.a matrix width. @@ -129,7 +129,7 @@ public: */ inline size_t getWidth() const { return width_; } -private: + private: //! TODO(yuyang18): Add resize method to CpuMemHandlePtr, then we can get rid //! of std::vector here. CpuMemHandlePtr preallocatedBuf_; diff --git a/paddle/math/SparseMatrix.h b/paddle/math/SparseMatrix.h index 7c525f4edf3d53544c195f8e253c27a03854a793..9181fa29233677d8f4fac503905cc31eb66cb6c1 100644 --- a/paddle/math/SparseMatrix.h +++ b/paddle/math/SparseMatrix.h @@ -25,7 +25,7 @@ namespace paddle { typedef std::shared_ptr<_hl_sparse_matrix_s> hl_sparse_matrix_s_ptr; class GpuSparseMatrix : public Matrix { -public: + public: MemoryHandlePtr sMemoryHandle_; int* rows_; int* cols_; @@ -36,7 +36,7 @@ public: SparseValueType valueType_; SparseFormat format_; -public: + public: GpuSparseMatrix(size_t height, size_t width, size_t nnz, /* used to allocate space */ @@ -73,7 +73,7 @@ public: bool trans, MemoryHandlePtr sMemoryHandle); -protected: + protected: struct Element { int row; int col; @@ -82,7 +82,7 @@ protected: : row(rowIn), col(colIn), val(valIn) {} }; -public: + public: ~GpuSparseMatrix() {} void resize(size_t newHeight, @@ -211,13 +211,13 @@ public: */ void rowMax(IVector& maxIds, Matrix& maxVal); -protected: + protected: void sparseResize(); void copyRow(int offsets, size_t colNum, const sparse_non_value_t* row); void copyRow(int offsets, size_t colNum, const sparse_float_value_t* row); -public: + public: void mul(const Matrix& a, const Matrix& b, real scaleAB, real scaleT); void copyFrom(CpuSparseMatrix& src, hl_stream_t stream); @@ -228,10 +228,10 @@ public: void trimFromCSC(const CpuSparseMatrix& src); // BaseMatrixT interface -public: + public: bool isSparse() const { return true; } -private: + private: using Matrix::mul; using Matrix::copyFrom; using Matrix::rowMax; @@ -248,7 +248,7 @@ private: namespace paddle { class GpuSparseMatrix : public Matrix { -public: + public: GpuSparseMatrix(size_t height, size_t width, size_t nnz, /* used to allocate space */ diff --git a/paddle/math/SparseRowMatrix.h b/paddle/math/SparseRowMatrix.h index 3920de32df7de925d6e22e17b93b15bff8785675..cf6779e8b0b1d6b0c13b21a08ffff5af76e57ba6 100644 --- a/paddle/math/SparseRowMatrix.h +++ b/paddle/math/SparseRowMatrix.h @@ -29,7 +29,7 @@ namespace paddle { * Sparse Row */ class SparseRowCpuMatrix : public CpuMatrix { -public: + public: struct IndexDict { // In the following, global id means the row id in the original matrix. // Local id means the row id in the local storage which only contains @@ -53,7 +53,7 @@ public: virtual ~SparseRowCpuMatrix() {} -public: + public: /** * Get the row buf * @@ -163,7 +163,7 @@ public: return indexDictHandle_->localIndices; } -protected: + protected: template void apply(Func f) { f(buf_->data(), localIndices_->size() * width_); @@ -204,7 +204,7 @@ class SyncThreadPool; /// For prefetching parameters from remote Parameter server class SparsePrefetchRowCpuMatrix : public SparseRowCpuMatrix { -public: + public: SparsePrefetchRowCpuMatrix(CpuMemHandlePtr dataHandle, size_t height, size_t width, @@ -229,13 +229,13 @@ public: */ void setupIndices(); -protected: + protected: void addRows(const unsigned int* ids, size_t len); SyncThreadPool* pool_; }; class SparseAutoGrowRowCpuMatrix : public SparseRowCpuMatrix { -public: + public: SparseAutoGrowRowCpuMatrix(size_t height, size_t width, IndexDictPtr indexDictHandle = nullptr, @@ -258,7 +258,7 @@ public: }; class CacheRowCpuMatrix : public SparseAutoGrowRowCpuMatrix { -public: + public: CacheRowCpuMatrix(size_t height, size_t width, IndexDictPtr indexDictHandle = nullptr, @@ -287,7 +287,7 @@ public: virtual void mul(CpuSparseMatrix* a, CpuMatrix* b, real scaleAB, real scaleT); -public: + public: CpuVectorPtr sourceDataVec_; real* sourceData_; }; @@ -299,7 +299,7 @@ public: * ids are hashed by worker thread id. */ class SparseRowIdsCpuMatrix : public CpuMatrix { -public: + public: SparseRowIdsCpuMatrix(CpuMemHandlePtr dataHandle, size_t height, size_t width, @@ -310,7 +310,7 @@ public: std::vector& getIds(size_t threadId) { return idsArray_[threadId]; } -private: + private: std::vector> idsArray_; }; @@ -320,13 +320,13 @@ private: namespace paddle { class SparseRowCpuMatrix : public CpuMatrix { -public: + public: void reserveStore() {} void clearIndices() {} }; class SparsePrefetchRowCpuMatrix : public SparseRowCpuMatrix { -public: + public: void setupIndices() {} void addRows(MatrixPtr input) {} void addRows(IVectorPtr ids) {} diff --git a/paddle/math/Storage.h b/paddle/math/Storage.h index ba8f4689a1e896304aa14821b40fc8ff0c304bb2..61a9aa2a07442d9e4ede80c961e17e079eb8b3ba 100644 --- a/paddle/math/Storage.h +++ b/paddle/math/Storage.h @@ -25,7 +25,7 @@ namespace paddle { * @brief Storage manager for multiple devices. */ class StorageEngine { -public: + public: /** * @return Storage singleton */ @@ -41,7 +41,7 @@ public: */ PoolAllocator* getCpuAllocator(); -protected: + protected: StorageEngine(); ~StorageEngine(); RWLock lock_; diff --git a/paddle/math/TensorApply.h b/paddle/math/TensorApply.h index 7d79cae5a11851b190afbb9ac94efdf2ba2510b7..8b642047bffa33b47dfb8ffc8e3fd2a9b7dbae3a 100644 --- a/paddle/math/TensorApply.h +++ b/paddle/math/TensorApply.h @@ -21,7 +21,7 @@ namespace paddle { */ template class TensorApply { -public: + public: explicit INLINE TensorApply(const Derived& p) : data_(p.data_), stride_(p.stride_), @@ -52,7 +52,7 @@ public: */ template class TensorApply { -public: + public: explicit INLINE TensorApply(const Derived& p) : data_(p.data_), stride_(p.stride_), @@ -77,7 +77,7 @@ public: template class TensorApply, T> { -public: + public: explicit TensorApply(const TensorExpression& expr) : expr_(expr.derived()) {} @@ -97,7 +97,7 @@ public: */ template class TensorApply, T> { -public: + public: explicit INLINE TensorApply(const TensorUnaryOp& expr) : op_(expr.op_), expr_(expr.expr_) {} @@ -118,7 +118,7 @@ public: */ template class TensorApply, T> { -public: + public: explicit INLINE TensorApply( const TensorBinaryOp& expr) : op_(expr.op_), lhs_(expr.lhs_), rhs_(expr.rhs_) { @@ -153,7 +153,7 @@ public: */ template class TensorApply, T> { -public: + public: explicit INLINE TensorApply( const TensorTernaryOp& expr) : expr1_(expr.expr1_), expr2_(expr.expr2_), expr3_(expr.expr3_) { @@ -192,7 +192,7 @@ public: */ template class TensorApply, T> { -public: + public: explicit INLINE TensorApply(const TensorConstant& expr) : op_(expr.op_), expr_(expr.expr_) {} diff --git a/paddle/math/TensorAssign.h b/paddle/math/TensorAssign.h index 113d98c16b22b06971040b1a1ce52c696f6c3c14..7d4726ddba43202970c37dd1a08f842104b24ada 100644 --- a/paddle/math/TensorAssign.h +++ b/paddle/math/TensorAssign.h @@ -25,7 +25,7 @@ namespace paddle { */ template class TensorAssignOp { -public: + public: explicit TensorAssignOp(const LhsType& lhs, const RhsType& rhs) : lhs_(lhs), rhs_(rhs) { #ifndef __CUDA_ARCH__ @@ -49,7 +49,7 @@ public: } INLINE bool useGpu() const { return lhs_.useGpu(); } -private: + private: TensorApply lhs_; TensorApply rhs_; }; diff --git a/paddle/math/TensorExpression.h b/paddle/math/TensorExpression.h index 83229ae65dd1f4ed6b885c3d6195b3758b8ba039..f6da9adfca50e49ca260e20313c8979a38e1b06b 100644 --- a/paddle/math/TensorExpression.h +++ b/paddle/math/TensorExpression.h @@ -40,7 +40,7 @@ class TensorAssignOp; */ template class TensorExpression { -public: + public: /** * Element wise unary expression. */ @@ -355,7 +355,7 @@ public: return TensorAssignOp(derived(), expr); } -protected: + protected: const Derived& derived() const { return *static_cast(this); } }; @@ -365,7 +365,7 @@ protected: template class TensorUnaryOp : public TensorExpression, T> { -public: + public: explicit TensorUnaryOp(const OP op, const ExprType& expr) : op_(op), expr_(expr) {} @@ -379,7 +379,7 @@ public: template class TensorBinaryOp : public TensorExpression, T> { -public: + public: explicit TensorBinaryOp(const OP op, const LhsType& lhs, const RhsType& rhs) : op_(op), lhs_(lhs), rhs_(rhs) {} @@ -395,7 +395,7 @@ template class TensorTernaryOp : public TensorExpression< TensorTernaryOp, T> { -public: + public: explicit TensorTernaryOp(const ExprType1& expr1, const ExprType2& expr2, const ExprType3& expr3) @@ -412,7 +412,7 @@ public: template class TensorConstant : public TensorExpression, T> { -public: + public: explicit TensorConstant(const OP op, const ExprType& expr) : op_(op), expr_(expr) {} diff --git a/paddle/math/Vector.h b/paddle/math/Vector.h index 3efbc769dff5aa1dbc9d5015b0cbac313710d70d..964b42cae52af9b487ab17103bc5e999514e4dd1 100644 --- a/paddle/math/Vector.h +++ b/paddle/math/Vector.h @@ -40,13 +40,13 @@ class Matrix; template class BaseVector : public BaseMatrixT { -public: + public: BaseVector(size_t size, T* data, bool useGpu) : BaseMatrixT(1, size, data, false, useGpu), size_(this->width_) {} ~BaseVector() {} -protected: + protected: size_t& size_; }; @@ -57,7 +57,7 @@ protected: */ template class VectorT : public BaseVector { -protected: + protected: VectorT(size_t size, MemoryHandlePtr memoryHandle, size_t offset, bool useGpu) : BaseVector(size, reinterpret_cast(memoryHandle->getBuf()) + offset, @@ -71,7 +71,7 @@ protected: VectorT(size_t size, T* data, bool useGpu) : BaseVector(size, data, useGpu) {} -public: + public: virtual ~VectorT() {} static std::shared_ptr> create(size_t size, bool useGpu); @@ -281,7 +281,7 @@ public: } } -protected: + protected: friend class GpuVectorT; friend class CpuVectorT; virtual void copyTo(CpuVectorT* dest) const = 0; @@ -297,7 +297,7 @@ std::ostream& operator<<(std::ostream& os, const VectorT& vec) { template class GpuVectorT : public VectorT { -public: + public: explicit GpuVectorT(size_t size); GpuVectorT(size_t size, GpuMemHandlePtr memHandle, size_t offset) : VectorT(size, memHandle, offset, true) {} @@ -343,14 +343,14 @@ public: TensorGpuApply(*this, expr); } -protected: + protected: virtual void copyTo(CpuVectorT* dest) const; virtual void copyTo(GpuVectorT* dest) const; }; template class CpuVectorT : public VectorT { -public: + public: explicit CpuVectorT(size_t size); CpuVectorT(size_t size, MemoryHandlePtr memoryHandle, size_t offset) : VectorT(size, memoryHandle, offset, false) {} @@ -415,7 +415,7 @@ public: template class ParallelCpuVectorT : public CpuVectorT { -public: + public: ParallelCpuVectorT(size_t size, SyncThreadPool* pool) : CpuVectorT(size), pool_(pool) {} @@ -434,7 +434,7 @@ public: virtual void exec(SyncThreadPool::JobFunc jobFunc); -private: + private: typedef std::function& vec)> ExecFunc; void parallelExec(ExecFunc func); SyncThreadPool* pool_; @@ -445,7 +445,7 @@ private: */ template class CpuGpuVectorT { -public: + public: /** * @brief An enum type of SyncedFlag using to * mark data memory is in CPU or GPU. @@ -670,7 +670,7 @@ public: setSync(flag); } -protected: + protected: void resizeOrCreate(size_t size, bool useGpu); /** diff --git a/paddle/math/tests/TensorCheck.h b/paddle/math/tests/TensorCheck.h index f4332ede36356bc666612a240448c1be71e5170e..40ac04ef5d4baa0239bb03b04c3a6cce0fcac5a5 100644 --- a/paddle/math/tests/TensorCheck.h +++ b/paddle/math/tests/TensorCheck.h @@ -32,7 +32,7 @@ using paddle::CpuVectorT; using paddle::GpuVectorT; class AssertEqual { -public: + public: AssertEqual(real err = 0) : err_(err) {} inline bool operator()(real a, real b) { @@ -51,7 +51,7 @@ public: return true; } -private: + private: real err_; }; @@ -60,71 +60,71 @@ class CopyToCpu; template <> class CopyToCpu { -public: + public: explicit CopyToCpu(const CpuMatrix& arg) : arg_(arg) {} const CpuMatrix& copiedArg() const { return arg_; } -private: + private: const CpuMatrix& arg_; }; template <> class CopyToCpu { -public: + public: explicit CopyToCpu(const GpuMatrix& arg) : arg_(arg.getHeight(), arg.getWidth()) { arg_.copyFrom(arg); } CpuMatrix& copiedArg() { return arg_; } -private: + private: CpuMatrix arg_; }; template <> class CopyToCpu { -public: + public: explicit CopyToCpu(const Matrix& arg) : arg_(arg.getHeight(), arg.getWidth()) { arg_.copyFrom(arg); } CpuMatrix& copiedArg() { return arg_; } -private: + private: CpuMatrix arg_; }; template class CopyToCpu> { -public: + public: explicit CopyToCpu(const CpuVectorT& arg) : arg_(arg) {} const CpuVectorT& copiedArg() const { return arg_; } -private: + private: const CpuVectorT& arg_; }; template class CopyToCpu> { -public: + public: explicit CopyToCpu(const GpuVectorT& arg) : arg_(arg.getSize()) { arg_.copyFrom(arg); } CpuVectorT& copiedArg() { return arg_; } -private: + private: CpuVectorT arg_; }; template class CopyToCpu> { -public: + public: explicit CopyToCpu(const VectorT& arg) : arg_(arg.getSize()) { arg_.copyFrom(arg); } CpuVectorT& copiedArg() { return arg_; } -private: + private: CpuVectorT arg_; }; diff --git a/paddle/math/tests/TestUtils.h b/paddle/math/tests/TestUtils.h index d2b9706432f84fa082e071eb09d2ffe7402a085f..e1966ec8a74747960420ec80fdfbb957f7cf177f 100644 --- a/paddle/math/tests/TestUtils.h +++ b/paddle/math/tests/TestUtils.h @@ -56,31 +56,31 @@ using paddle::GpuSparseMatrix; template class ReplaceType { -public: + public: typedef T1 type; }; template <> class ReplaceType { -public: + public: typedef CpuMatrix type; }; template <> class ReplaceType { -public: + public: typedef GpuMatrix type; }; template <> class ReplaceType { -public: + public: typedef CpuMatrix type; }; template <> class ReplaceType { -public: + public: typedef GpuMatrix type; }; @@ -180,25 +180,25 @@ R call(C& obj, R (FC::*f)(FArgs...), Args&&... args) { template class ReturnType { -public: + public: typedef T type; }; template <> class ReturnType { -public: + public: typedef GpuMatrix type; }; template <> class ReturnType { -public: + public: typedef GpuIVector type; }; template <> class ReturnType { -public: + public: typedef GpuSparseMatrix type; }; @@ -234,7 +234,7 @@ GpuSparseMatrix autoArgs(CpuSparseMatrix& v) { } class AutoCompare { -public: + public: /** * err is the allowed calculation error. * The smaller the value of err, @@ -285,7 +285,7 @@ public: TensorCheck(compare, cpu, gpu); } -protected: + protected: CpuMatrix cpu; GpuMatrix gpu; AssertEqual compare; diff --git a/paddle/math/tests/test_ExecViaCpu.cpp b/paddle/math/tests/test_ExecViaCpu.cpp index 513c7b440e0aa6f20cc8209a3624f32f4892225b..72256cb9d4c93159418d27c7ca0d4f8b9a412a64 100644 --- a/paddle/math/tests/test_ExecViaCpu.cpp +++ b/paddle/math/tests/test_ExecViaCpu.cpp @@ -39,7 +39,7 @@ real f(Matrix& mat1, } class Functor { -public: + public: real operator()(Matrix& mat1, const Matrix& mat2, IVector& vec1, @@ -49,7 +49,7 @@ public: return a_; } -private: + private: real a_; }; diff --git a/paddle/math/tests/test_TrainingAlgorithm.cpp b/paddle/math/tests/test_TrainingAlgorithm.cpp index fb146176ca8eb97a9cdbaf9ebd5c4997a8439718..fb58d26734cab5d7d7bbbbe1cf8a920e4195b4bb 100644 --- a/paddle/math/tests/test_TrainingAlgorithm.cpp +++ b/paddle/math/tests/test_TrainingAlgorithm.cpp @@ -28,14 +28,14 @@ DEFINE_double(max_diff, 1e-13, "max diff allowed"); #endif class SetMaxDiff { -public: + public: explicit SetMaxDiff(double max_diff) { max_diff_ = FLAGS_max_diff; FLAGS_max_diff = max_diff; } ~SetMaxDiff() { FLAGS_max_diff = max_diff_; } -private: + private: double max_diff_; }; diff --git a/paddle/math/tests/test_perturbation.cpp b/paddle/math/tests/test_perturbation.cpp index ef99dab60a874846d04c5ce07d38b2857640ad7b..969400666f12e4c6001f270be3ec144e7e4d0702 100644 --- a/paddle/math/tests/test_perturbation.cpp +++ b/paddle/math/tests/test_perturbation.cpp @@ -32,7 +32,7 @@ const int TGT_SIZE = 21; const int CHANNELS = 3; class PerturbationTest : public testing::Test { -protected: + protected: virtual void SetUp() { generateTestImages(gpuImages_); } virtual void TearDown() {} diff --git a/paddle/optimizer/adadelta_optimizer.h b/paddle/optimizer/adadelta_optimizer.h index 74df9d54be734fedec8aeddff5f50b1d1aefb1d3..5beb62295a83ba4826e9a6b9caf21de78d2e8ced 100644 --- a/paddle/optimizer/adadelta_optimizer.h +++ b/paddle/optimizer/adadelta_optimizer.h @@ -20,7 +20,7 @@ namespace paddle { namespace optimizer { class AdadeltaOptimizer : public ParameterOptimizer { -public: + public: AdadeltaOptimizer( Tensor *parameter, LrPolicy *lr, double rho, double epsilon, double decay) : ParameterOptimizer(parameter, lr), @@ -40,7 +40,7 @@ public: std::string SerializeState(); void DeserializeState(const std::string &state); -private: + private: Tensor *accum_gradient_; Tensor *accum_delta_; Tensor *update_delta_; diff --git a/paddle/optimizer/adagrad_optimizer.h b/paddle/optimizer/adagrad_optimizer.h index 1d58402d78ff9ada8b084a472d46c96580d01e5b..b6fc06739970984cf4bbd27d3e6e1e9066bc350f 100644 --- a/paddle/optimizer/adagrad_optimizer.h +++ b/paddle/optimizer/adagrad_optimizer.h @@ -20,7 +20,7 @@ namespace paddle { namespace optimizer { class AdagradOptimizer : public ParameterOptimizer { -public: + public: AdagradOptimizer(Tensor *parameter, LrPolicy *lr, double epsilon, @@ -36,7 +36,7 @@ public: std::string SerializeState(); void DeserializeState(const std::string &state); -private: + private: Tensor *accum_gradient_; double epsilon_; double decay_; diff --git a/paddle/optimizer/adam_optimizer.h b/paddle/optimizer/adam_optimizer.h index 7977226c8602745d5733021a51fc03d932b0921a..fce10960068364b40592b26a6b439494d75cfa03 100644 --- a/paddle/optimizer/adam_optimizer.h +++ b/paddle/optimizer/adam_optimizer.h @@ -20,7 +20,7 @@ namespace paddle { namespace optimizer { class AdamOptimizer : public ParameterOptimizer { -public: + public: AdamOptimizer(Tensor *parameter, LrPolicy *lr, double beta_1, @@ -42,7 +42,7 @@ public: std::string SerializeState(); void DeserializeState(const std::string &state); -private: + private: Tensor *momentums_; Tensor *velocitys_; double beta_1_; diff --git a/paddle/optimizer/lr_policy.h b/paddle/optimizer/lr_policy.h index 14422d1f42fc45d5e9a560c45259d4003a0b3d11..d639c9f22c8ad77267f68e2c3b35257211bf90df 100644 --- a/paddle/optimizer/lr_policy.h +++ b/paddle/optimizer/lr_policy.h @@ -20,7 +20,7 @@ namespace paddle { namespace optimizer { class LrPolicy { -public: + public: virtual ~LrPolicy() {} virtual double LearningRate(const uint64_t num_sample_passed) = 0; virtual std::string SerializeState() = 0; @@ -29,7 +29,7 @@ public: // constant learning rate policy class ConstLr final : public LrPolicy { -public: + public: ConstLr(double lr) : learning_rate_(lr){}; double LearningRate(const uint64_t num_sample_passed) { return learning_rate_; @@ -45,12 +45,12 @@ public: learning_rate_ = state.learning_rate(); } -private: + private: double learning_rate_; }; class LinearLr final : public LrPolicy { -public: + public: LinearLr(double lr, double lr_decay_a, double lr_decay_b) : learning_rate_(lr), lr_decay_a_(lr_decay_a), lr_decay_b_(lr_decay_b) {} double LearningRate(const uint64_t num_sample_passed) { @@ -72,7 +72,7 @@ public: lr_decay_b_ = state.lr_decay_b(); } -private: + private: double learning_rate_; double lr_decay_a_; double lr_decay_b_; diff --git a/paddle/optimizer/parameter_optimizer.h b/paddle/optimizer/parameter_optimizer.h index c7cf8db3ee05c75c171b68bcbcb06a5ae8fa5b48..d5abca82d55c12aed0f4fca0c4c1f21d20586155 100644 --- a/paddle/optimizer/parameter_optimizer.h +++ b/paddle/optimizer/parameter_optimizer.h @@ -26,7 +26,7 @@ namespace paddle { namespace optimizer { class ParameterOptimizer { -public: + public: /** * @brief update hook for algorithm need to traverse parameter more than * once. @@ -45,7 +45,7 @@ public: virtual std::string SerializeState() = 0; virtual void DeserializeState(const std::string &state) = 0; -protected: + protected: Tensor *parameter_; // learning rate policy LrPolicy *lr_policy_; diff --git a/paddle/optimizer/parameter_optimizer_test.cc b/paddle/optimizer/parameter_optimizer_test.cc index d663e2fd007febd3b9f0f43d213d63d2b20656b8..1d9572999e9e0f10092eecbc1b41369a89629da7 100644 --- a/paddle/optimizer/parameter_optimizer_test.cc +++ b/paddle/optimizer/parameter_optimizer_test.cc @@ -38,7 +38,7 @@ paddle::optimizer::Tensor* FixedTensor(size_t size) { } class OptimizerTest : public testing::Test { -public: + public: virtual ~OptimizerTest() {} // init paddle::optimizer::Tensor shape const size_t kSize = 5; @@ -115,7 +115,7 @@ public: } } -private: + private: std::vector opts_; paddle::OptimizerConfig config_; }; diff --git a/paddle/optimizer/sgd_optimizer.h b/paddle/optimizer/sgd_optimizer.h index f504d98adb8a01fd69ff313075b4c417222c765e..a8957cde54abd6667143d2a8265d732c849294e3 100644 --- a/paddle/optimizer/sgd_optimizer.h +++ b/paddle/optimizer/sgd_optimizer.h @@ -20,7 +20,7 @@ namespace paddle { namespace optimizer { class SGDOptimizer : public ParameterOptimizer { -public: + public: SGDOptimizer(Tensor* parameter, LrPolicy* lr, double m, double d, bool n) : ParameterOptimizer(parameter, lr), momentums_(nullptr), @@ -39,7 +39,7 @@ public: std::string SerializeState(); void DeserializeState(const std::string& state); -private: + private: Tensor* momentums_; double momentum_; double decay_; diff --git a/paddle/optimizer/tensor.h b/paddle/optimizer/tensor.h index fd32398a237e7e08a198707347cd3c0a4ed77bb3..d2cef99074335be6f9852d60daa103b9b45a550d 100644 --- a/paddle/optimizer/tensor.h +++ b/paddle/optimizer/tensor.h @@ -26,7 +26,7 @@ namespace optimizer { template class TensorT { -public: + public: TensorT(size_t size) : height_(1), width_(size) { // new T[size]() initializes all element to zero value. data_ptr_ = std::shared_ptr(new T[size](), std::default_delete()); @@ -54,7 +54,7 @@ public: // TODO: replace with tensorshape size_t size() const { return this->width_ * this->height_; } -protected: + protected: size_t height_; size_t width_; std::shared_ptr data_ptr_; diff --git a/paddle/parameter/AverageOptimizer.h b/paddle/parameter/AverageOptimizer.h index 4ad3c18d56abf16d1274c5b3b8e0347b85e64dea..f0fe2fd28e4be7df8ebc52fd9b9b5540f3d76949 100644 --- a/paddle/parameter/AverageOptimizer.h +++ b/paddle/parameter/AverageOptimizer.h @@ -21,7 +21,7 @@ namespace paddle { // After Optimization, parameter values are further averaged within // time range. class AverageOptimizer : public ParameterOptimizer { -public: + public: // if *useParameterApply* set, use PARAMETER_APPLY to store averaged parameter // else use PARAMETER_VALUE, and value backup in PARAMETER_GRADIENT AverageOptimizer(const OptimizationConfig& optConfig, @@ -65,7 +65,7 @@ public: virtual void setNoDecay() { optimizer_->setNoDecay(); } -protected: + protected: std::unique_ptr optimizer_; bool useApply_; @@ -98,7 +98,7 @@ protected: // Average Optimizer with Sparse support. class AverageSparseOptimizer : public AverageOptimizer { -public: + public: AverageSparseOptimizer(const OptimizationConfig& optConfig, ParameterOptimizer* optimizer, bool useParameterApply) @@ -130,7 +130,7 @@ public: t0Vec_.assign(t0Vec_.size(), 0); } -protected: + protected: /** * counting batches, clear after catch up with * t(timer_) is current time, diff --git a/paddle/parameter/FirstOrderOptimizer.h b/paddle/parameter/FirstOrderOptimizer.h index 047989fcad52afc1d4d4c347258d0fb2f069f3d4..86b9a591aff7a58aafa194c64cb09cd6636d0454 100644 --- a/paddle/parameter/FirstOrderOptimizer.h +++ b/paddle/parameter/FirstOrderOptimizer.h @@ -22,7 +22,7 @@ namespace paddle { // Plain SGD optimization. class SgdOptimizer : public ParameterOptimizer { -public: + public: explicit SgdOptimizer(const OptimizationConfig& optConfig) : ParameterOptimizer(optConfig) { addParameterType(PARAMETER_MOMENTUM); @@ -77,7 +77,7 @@ class SparseMomentumParameterOptimizer : public ParameterOptimizer { \gamma_t: learning rate at the t'th step */ -public: + public: explicit SparseMomentumParameterOptimizer( const OptimizationConfig& optConfig); virtual void init(size_t numRows, const ParameterConfig* config); @@ -89,7 +89,7 @@ public: const ParameterConfig& config) const; virtual void finishBatch(); -private: + private: real alpha_; real beta_; real tau_; @@ -98,7 +98,7 @@ private: real momentum_; real decayRate_; -protected: + protected: int64_t timer_; mutable std::vector t0Vec_; bool isParameterSparse_; @@ -109,7 +109,7 @@ protected: * http://www.magicbroom.info/Papers/DuchiHaSi10.pdf */ class AdagradParameterOptimizer : public ParameterOptimizer { -public: + public: explicit AdagradParameterOptimizer(const OptimizationConfig& optConfig) : ParameterOptimizer(optConfig) { addParameterType(PARAMETER_MOMENTUM); @@ -129,7 +129,7 @@ public: virtual TraverseCallback needSpecialTraversal( const ParameterConfig& config) const; -protected: + protected: int64_t numUpdates_; static const int64_t kMaxNumAccumulates = 16384; }; @@ -139,7 +139,7 @@ protected: * http://www.matthewzeiler.com/pubs/googleTR2012/googleTR2012.pdf */ class AdaDeltaParameterOptimizer : public ParameterOptimizer { -public: + public: explicit AdaDeltaParameterOptimizer(const OptimizationConfig& optConfig) : ParameterOptimizer(optConfig) { addParameterType(PARAMETER_MOMENTUM); @@ -158,14 +158,14 @@ public: const ParameterConfig& config, size_t sparseId) const; -protected: + protected: real rou_; real epsilon_; }; // RMSProp Parameter Optimization. class RMSPropParameterOptimizer : public ParameterOptimizer { -public: + public: explicit RMSPropParameterOptimizer(const OptimizationConfig& optConfig) : ParameterOptimizer(optConfig) { addParameterType(PARAMETER_MOMENTUM); @@ -191,7 +191,7 @@ public: const ParameterConfig& config, size_t sparseId) const; -protected: + protected: real rou_; real epsilon_; @@ -208,7 +208,7 @@ protected: // Decayed AdaGrad Optimization. class DecayedAdagradParameterOptimizer : public ParameterOptimizer { -public: + public: explicit DecayedAdagradParameterOptimizer(const OptimizationConfig& optConfig) : ParameterOptimizer(optConfig) { addParameterType(PARAMETER_MOMENTUM); @@ -233,7 +233,7 @@ public: const ParameterConfig& config, size_t sparseId) const; -protected: + protected: real rou_; real epsilon_; @@ -253,7 +253,7 @@ protected: * Reference Paper: http://arxiv.org/abs/1412.6980 Algorithm 1 */ class AdamParameterOptimizer : public ParameterOptimizer { -public: + public: explicit AdamParameterOptimizer(const OptimizationConfig& optConfig) : ParameterOptimizer(optConfig), beta1_(optConfig.adam_beta1()), @@ -275,7 +275,7 @@ public: const ParameterConfig& config, size_t sparseId) const; -protected: + protected: real beta1_; real beta2_; real epsilon_; @@ -288,7 +288,7 @@ protected: * Reference Paper: http://arxiv.org/abs/1412.6980 Algorithm 2 */ class AdamaxParameterOptimizer : public ParameterOptimizer { -public: + public: explicit AdamaxParameterOptimizer(const OptimizationConfig& optConfig) : ParameterOptimizer(optConfig), beta1_(optConfig.adam_beta1()), @@ -305,7 +305,7 @@ public: const ParameterConfig& config, size_t sparseId) const; -protected: + protected: real beta1_; real beta2_; int64_t step_; @@ -315,7 +315,7 @@ protected: // Used in pserver, // when PARAMETER_DELTA stores in PARAMETER_GRADIENT. class AddOptimizer : public ParameterOptimizer { -public: + public: explicit AddOptimizer(const OptimizationConfig& optConfig) : ParameterOptimizer(optConfig) {} @@ -333,7 +333,7 @@ public: // A optimizer which does nothing. class DummyOptimizer : public ParameterOptimizer { -public: + public: explicit DummyOptimizer(const OptimizationConfig& optConfig) : ParameterOptimizer(optConfig) {} @@ -344,7 +344,7 @@ public: // Do gradient clipping before sgd update class OptimizerWithGradientClipping : public ParameterOptimizer { -public: + public: OptimizerWithGradientClipping(const OptimizationConfig& optConfig, ParameterOptimizer* optimizer) : ParameterOptimizer(optConfig), optimizer_(optimizer) { @@ -374,7 +374,7 @@ public: virtual void setNoDecay() { optimizer_->setNoDecay(); } -protected: + protected: std::unique_ptr optimizer_; }; diff --git a/paddle/parameter/LearningRateScheduler.cpp b/paddle/parameter/LearningRateScheduler.cpp index b6b58e3ddad6a0e8811bf56502c3f2f0c8728f5c..d57d2189a45dc8cbcea7a8a5f25c5ec7ac71cca3 100644 --- a/paddle/parameter/LearningRateScheduler.cpp +++ b/paddle/parameter/LearningRateScheduler.cpp @@ -28,20 +28,20 @@ LearningRateScheduler* LearningRateScheduler::create( // LRS stands for LearningRateScheduler class BaseLRS : public LearningRateScheduler { -public: + public: explicit BaseLRS(const OptimizationConfig& config) : learningRate_(config.learning_rate()), a_(config.learning_rate_decay_a()), b_(config.learning_rate_decay_b()) {} -protected: + protected: real learningRate_; real a_; real b_; }; class ConstLRS : public BaseLRS { -public: + public: explicit ConstLRS(const OptimizationConfig& config) : BaseLRS(config) {} virtual real calcLearningRate(int64_t numSamplesProcessed, int64_t pass) { return learningRate_; @@ -50,7 +50,7 @@ public: REGISTER_LEARNING_RATE_SCHEDULER(constant, ConstLRS); class PolyLRS : public BaseLRS { -public: + public: explicit PolyLRS(const OptimizationConfig& config) : BaseLRS(config) {} virtual real calcLearningRate(int64_t numSamplesProcessed, int64_t pass) { return learningRate_ * pow(1.0 + a_ * numSamplesProcessed, -b_); @@ -59,7 +59,7 @@ public: REGISTER_LEARNING_RATE_SCHEDULER(poly, PolyLRS); class CaffePolyLRS : public BaseLRS { -public: + public: explicit CaffePolyLRS(const OptimizationConfig& config) : BaseLRS(config) {} virtual real calcLearningRate(int64_t numSamplesProcessed, int64_t pass) { if (numSamplesProcessed > a_) { @@ -78,7 +78,7 @@ public: REGISTER_LEARNING_RATE_SCHEDULER(caffe_poly, CaffePolyLRS); class ExpLRS : public BaseLRS { -public: + public: explicit ExpLRS(const OptimizationConfig& config) : BaseLRS(config) {} virtual real calcLearningRate(int64_t numSamplesProcessed, int64_t pass) { double decayRatio = (double)numSamplesProcessed / b_; @@ -88,7 +88,7 @@ public: REGISTER_LEARNING_RATE_SCHEDULER(exp, ExpLRS); class DiscreteExpLRS : public BaseLRS { -public: + public: explicit DiscreteExpLRS(const OptimizationConfig& config) : BaseLRS(config) {} virtual real calcLearningRate(int64_t numSamplesProcessed, int64_t pass) { int numDecays = floor(numSamplesProcessed / b_); @@ -98,7 +98,7 @@ public: REGISTER_LEARNING_RATE_SCHEDULER(discexp, DiscreteExpLRS); class LinearLRS : public BaseLRS { -public: + public: explicit LinearLRS(const OptimizationConfig& config) : BaseLRS(config) {} virtual real calcLearningRate(int64_t numSamplesProcessed, int64_t pass) { return std::max(learningRate_ - a_ * numSamplesProcessed, b_); @@ -113,7 +113,7 @@ REGISTER_LEARNING_RATE_SCHEDULER(linear, LinearLRS); then learning_rate = learning_rate_base * rate_i */ class ManualLRS : public BaseLRS { -public: + public: explicit ManualLRS(const OptimizationConfig& config) : BaseLRS(config), currentSegment_(0), lastNum_(0) { std::vector pieces; @@ -151,7 +151,7 @@ public: return learningRate_ * rates_.back(); } -protected: + protected: std::vector rates_; std::vector segments_; size_t currentSegment_; @@ -161,7 +161,7 @@ protected: REGISTER_LEARNING_RATE_SCHEDULER(manual, ManualLRS); class PassManualLRS : public ManualLRS { -public: + public: explicit PassManualLRS(const OptimizationConfig& config) : ManualLRS(config) {} virtual real calcLearningRate(int64_t numSamplesProcessed, int64_t pass) { diff --git a/paddle/parameter/LearningRateScheduler.h b/paddle/parameter/LearningRateScheduler.h index aea99a1c204b46e937135cbde22360a12d087ae2..3fad97040248dcf8a22988c38153df31f267ed37 100644 --- a/paddle/parameter/LearningRateScheduler.h +++ b/paddle/parameter/LearningRateScheduler.h @@ -26,7 +26,7 @@ namespace paddle { }) class LearningRateScheduler { -public: + public: static LearningRateScheduler* create(const OptimizationConfig& config); virtual ~LearningRateScheduler() {} virtual real calcLearningRate(int64_t numSamplesProcessed, int64_t pass) = 0; diff --git a/paddle/parameter/OptimizerWithRegularizer.h b/paddle/parameter/OptimizerWithRegularizer.h index 7219d96d924dfa26d3ab52b8c6a2ce1249e4f45c..bd29b3966324b2e206cfe56cc15678539d1e870e 100644 --- a/paddle/parameter/OptimizerWithRegularizer.h +++ b/paddle/parameter/OptimizerWithRegularizer.h @@ -20,7 +20,7 @@ namespace paddle { // add regularizer for objective function to do optimization class OptimizerWithRegularizer : public ParameterOptimizer { -public: + public: static ParameterOptimizer* create(const OptimizationConfig& optConfig, const ParameterConfig& paraConfig, bool isParameterSparse, @@ -67,7 +67,7 @@ public: regularizer_->update(vecs, config, optimizer_->getLearningRate(), 0, 1); } -protected: + protected: std::unique_ptr optimizer_; Regularizer* regularizer_; @@ -84,7 +84,7 @@ protected: // Regularized Loss function for every num of batches class OptimizerWithRegularizerEveryNumBatches : public OptimizerWithRegularizer { -public: + public: OptimizerWithRegularizerEveryNumBatches(const OptimizationConfig& optConfig, ParameterOptimizer* optimizer, Regularizer* regularizer) @@ -112,7 +112,7 @@ public: virtual TraverseCallback startCatchUpWith() const; virtual void finishCatchUpWith() { baseTimer_ = timer_; } -protected: + protected: bool isRegularizationBatch(const ParameterConfig& config) const { return ((timer_ + 1) % config.num_batches_regularization() == 0); } @@ -125,7 +125,7 @@ protected: // Regularized Loss function with Sparse support class OptimizerWithRegularizerSparse : public OptimizerWithRegularizer { -public: + public: OptimizerWithRegularizerSparse(const OptimizationConfig& optConfig, ParameterOptimizer* optimizer, Regularizer* regularizer) @@ -145,7 +145,7 @@ public: t0Vec_.assign(t0Vec_.size(), 0); } -protected: + protected: /** * t0Vec_ are last occur time of i rows * if one block is update by multi threads, diff --git a/paddle/parameter/Parameter.h b/paddle/parameter/Parameter.h index 24ac10f3fe5977553332a9a8402d6795577b5ad8..ef519bf35a4f051b4477eb04b5eb2c5f0b5e29e8 100644 --- a/paddle/parameter/Parameter.h +++ b/paddle/parameter/Parameter.h @@ -58,7 +58,7 @@ class Parameter; typedef std::shared_ptr ParameterPtr; class Parameter { -public: + public: Parameter(const ParameterConfig& config, bool useGpu, bool doInit = true); const std::string& getName() const { return config_.name(); } @@ -311,7 +311,7 @@ public: } } -protected: + protected: /** * @brief create matrix to matType. * @@ -326,7 +326,7 @@ protected: void clearUpdate() { updateCounter_ = 0; } -protected: + protected: ParameterConfig config_; bool useGpu_; @@ -363,7 +363,7 @@ protected: std::vector> updaterHooks_; -public: + public: void setSharedCount(int cnt) { sharedCount_ = cnt; } int getSharedCount() { return sharedCount_; } diff --git a/paddle/parameter/ParameterOptimizer.h b/paddle/parameter/ParameterOptimizer.h index a8d0ca72f21d04e0e65a9dd6a07e8f53b23e4223..019afa1358ae255fd096e84e5eb1d7b0b9d6859f 100644 --- a/paddle/parameter/ParameterOptimizer.h +++ b/paddle/parameter/ParameterOptimizer.h @@ -30,12 +30,12 @@ namespace paddle { * may be called many times, should be no state change between calls. */ class ParameterOptimizer { -public: + public: typedef std::function TraverseCallback; -public: + public: explicit ParameterOptimizer(const OptimizationConfig& optConfig) : applyDecay_(true), optConfig_(optConfig), @@ -175,7 +175,7 @@ public: static ParameterOptimizer* create(const OptimizationConfig& optConfig, bool inPserver = false); -protected: + protected: typedef std::vector TraverseCallbackVec; static TraverseCallback composeCallbacks( diff --git a/paddle/parameter/ParameterUpdaterBase.h b/paddle/parameter/ParameterUpdaterBase.h index 717e1c6721b6e4d3ff81172eb06213677c3bff98..493512886cad3ea9b74026d6dfcc4fc90f6aadb9 100644 --- a/paddle/parameter/ParameterUpdaterBase.h +++ b/paddle/parameter/ParameterUpdaterBase.h @@ -21,7 +21,7 @@ namespace paddle { class ParameterOptimizer; class ParameterUpdater { -public: + public: ParameterUpdater() : parameterTypes_{PARAMETER_VALUE, PARAMETER_GRADIENT} {} virtual ~ParameterUpdater() {} @@ -89,7 +89,7 @@ public: virtual void setForwardbackwardTime(uint64_t delta) {} #endif -protected: + protected: virtual void updateImpl(Parameter* para) = 0; std::vector parameterTypes_; @@ -101,7 +101,7 @@ protected: // part of all Parameters. It's useful when we need different // update strategy for different Parameter. class ParameterUpdaterComposite : public ParameterUpdater { -public: + public: ParameterUpdaterComposite() {} virtual ~ParameterUpdaterComposite() {} @@ -173,7 +173,7 @@ public: [&](int tid, size_t numThreads) { updaters_[tid]->restore(); }); } -protected: + protected: virtual void updateImpl(Parameter* para) {} std::vector> updaters_; std::unique_ptr syncThreadPool_; diff --git a/paddle/parameter/ParameterUpdaterHook.cpp b/paddle/parameter/ParameterUpdaterHook.cpp index e6aec3c34820764b3515f47f13a432961de1a673..989185b66a5b7785bb0572fba59a72adeef9797b 100644 --- a/paddle/parameter/ParameterUpdaterHook.cpp +++ b/paddle/parameter/ParameterUpdaterHook.cpp @@ -37,7 +37,7 @@ namespace paddle { */ class StaticPruningHook : public IParameterUpdaterHook { -public: + public: explicit StaticPruningHook(const ParameterUpdaterHookConfig &hookConfig) : initCount_(0) { sparsityRatio_ = hookConfig.sparsity_ratio(); @@ -96,7 +96,7 @@ public: paraVec->dotMul(*maskVec_); } -private: + private: SameThreadChecker updateThreadChecker_; std::atomic initCount_; VectorPtr maskVec_; @@ -116,12 +116,12 @@ IParameterUpdaterHook::~IParameterUpdaterHook() {} * May be extracted to Util.h to unify the hasher. */ class StringIntPairHasher { -public: + public: size_t operator()(const std::pair &k) const { return intHasher_(strHasher_(k.first) + k.second); } -private: + private: std::hash strHasher_; std::hash intHasher_; }; diff --git a/paddle/parameter/ParameterUpdaterHook.h b/paddle/parameter/ParameterUpdaterHook.h index d30530ec393c097bf77e5e376e3c4dc84b321ed8..cb96e4cf007572e9688c11719017a9d2771ecd51 100644 --- a/paddle/parameter/ParameterUpdaterHook.h +++ b/paddle/parameter/ParameterUpdaterHook.h @@ -29,7 +29,7 @@ class Parameter; * parameter optimization. */ class IParameterUpdaterHook { -public: + public: virtual ~IParameterUpdaterHook(); /** @@ -53,7 +53,7 @@ public: */ virtual void init(Parameter* para) = 0; -protected: + protected: /** * Ctor. */ diff --git a/paddle/parameter/Regularizer.h b/paddle/parameter/Regularizer.h index 6bed7b0ddfe7b72c697af60f5243f9037999d54a..fa5384e23251b918cc914df36c16ad790a5c59c5 100644 --- a/paddle/parameter/Regularizer.h +++ b/paddle/parameter/Regularizer.h @@ -20,7 +20,7 @@ namespace paddle { // Regularizer function for parameter, e.g. L1/L2 class Regularizer { -public: + public: virtual void update(const VectorPtr vecs[], const ParameterConfig& paraConfig, real learningRate, // learningrate from optimizer diff --git a/paddle/parameter/Weight.h b/paddle/parameter/Weight.h index 7314c29d0db92db06d5b921c09de39d3b0029ef3..113dd6530c82fe1e831ad4a35e9cbcb9880b9243 100644 --- a/paddle/parameter/Weight.h +++ b/paddle/parameter/Weight.h @@ -23,12 +23,12 @@ limitations under the License. */ namespace paddle { class Weight { -private: + private: MatrixPtr weight_; MatrixPtr weightGrad_; ParameterPtr parameter_; -public: + public: Weight(size_t height, size_t width, ParameterPtr parameter); Weight(size_t height, size_t width, ParameterPtr parameter, size_t offset); diff --git a/paddle/parameter/tests/test_common.cpp b/paddle/parameter/tests/test_common.cpp index 6e10becabbbbb8861095fed5aab9ac1e05bcac91..89dcc6c751eb2ec07bfe8297c93d56c824086211 100644 --- a/paddle/parameter/tests/test_common.cpp +++ b/paddle/parameter/tests/test_common.cpp @@ -24,7 +24,7 @@ limitations under the License. */ using namespace paddle; // NOLINT class CommonTest : public ::testing::Test { -protected: + protected: CommonTest() : testStat_("test") {} virtual ~CommonTest() {} virtual void SetUp() { @@ -51,7 +51,7 @@ protected: virtual void TreaDown() { LOG(INFO) << "All Test Finished."; } -protected: + protected: std::vector> valueUint_; std::vector sizeVec_; real learningRate_; diff --git a/paddle/pserver/BaseClient.h b/paddle/pserver/BaseClient.h index a932d34712f56de1cbbf84a9db4476f862febca0..d50230e73a3a7d128cbfd1d70517fddd228fb1bb 100644 --- a/paddle/pserver/BaseClient.h +++ b/paddle/pserver/BaseClient.h @@ -32,7 +32,7 @@ namespace paddle { * connections. */ class BaseClient { -protected: + protected: typedef std::unique_ptr ThreadPtr; typedef std::vector> InputIovs; typedef std::vector SendRequest; @@ -49,7 +49,7 @@ protected: SendDataRequestVec parallelDataRequests; }; -public: + public: explicit BaseClient(bool separate = false, int numPorts = FLAGS_ports_num); virtual ~BaseClient(); @@ -141,7 +141,7 @@ public: return dataType; } -protected: + protected: /// for a > 0, b > 0: /// return the smallest x s.t. b*x >= a static int divup(int a, int b) { return (a + b - 1) / b; } @@ -264,7 +264,7 @@ protected: */ virtual void recv(int threadId) = 0; -protected: + protected: bool stopping_; /// nodes * ports that means the number of real pservers int serviceNum_; diff --git a/paddle/pserver/LightNetwork.h b/paddle/pserver/LightNetwork.h index 2aaa26a5c708f9c01f006136619f599bcfe0db71..bcfc9655e989e80e08e9dce9b8734c0643cbf661 100644 --- a/paddle/pserver/LightNetwork.h +++ b/paddle/pserver/LightNetwork.h @@ -41,7 +41,7 @@ class SocketServer : public Thread { // rdmaCpu controls the cpu affinity of RDMA server daemon, // which could benifit performance. rdmaCpu = -1 means TCP // is used instead of RDMA transport. -public: + public: SocketServer(const std::string& addr, int port, int rdmaCpu); ~SocketServer(); @@ -50,7 +50,7 @@ public: typedef std::function& outputIovs)> ResponseCallback; -protected: + protected: // // The derived class needs to implement this function // to handle the request received by SocketWorker @@ -70,13 +70,13 @@ protected: friend class SocketWorker; -private: + private: void rdmaServer(); void tcpServer(); void detach() {} // detach accept thread is forbidden -protected: + protected: enum ChannelType tcpRdma_; // for rdma int rdmaCpu_; @@ -96,7 +96,7 @@ protected: * @note all parameter processing will run in the context of this worker */ class SocketWorker : public Thread { -public: + public: SocketWorker(std::unique_ptr&& channel, SocketServer* server) : channel_(std::move(channel)), server_(server) {} @@ -104,7 +104,7 @@ public: virtual void run(); -protected: + protected: std::unique_ptr channel_; SocketServer* server_; enum ChannelType tcpRdma_; @@ -118,12 +118,12 @@ protected: * single cpu core for better load balance performance */ class RdmaClientDaemons { -private: + private: RdmaClientDaemons(); static std::unique_ptr daemons_; -public: + public: static RdmaClientDaemons* get() { std::call_once(RdmaClientDaemons::initDataFlag_, &RdmaClientDaemons::getInstance); @@ -141,10 +141,10 @@ public: ~RdmaClientDaemons(); -public: + public: friend class SocketClient; -private: + private: static std::once_flag initDataFlag_; static void getInstance() { if (!daemons_.get()) daemons_.reset(new RdmaClientDaemons()); @@ -162,19 +162,19 @@ private: * read data */ class SocketClient { -public: + public: SocketClient(const std::string& serverAddr, int serverPort, enum ChannelType channelType); SocketChannel* getChannel() { return channel_.get(); } -protected: + protected: std::unique_ptr channel_; struct sxi_socket* socketDaemon_; enum ChannelType tcpRdma_; -private: + private: void RdmaClient(const std::string& serverAddr, int serverPort); void TcpClient(const std::string& serverAddr, int serverPort); }; diff --git a/paddle/pserver/ParameterClient2.h b/paddle/pserver/ParameterClient2.h index d63273ccbc8ed30d9df50d9f8b1a4d1e4fba6720..c96bb787151a525556c8217629109de201762cff 100644 --- a/paddle/pserver/ParameterClient2.h +++ b/paddle/pserver/ParameterClient2.h @@ -50,11 +50,11 @@ struct PServerVector { * @brief A class to help to prepare server-side operations. */ class PreparedOperations { -protected: + protected: class ResultsAdder; struct LocalOperationResult; -public: + public: /** * Offers an easy way to prepare operations that will be performed on * server-side. @@ -93,7 +93,7 @@ public: return ResultsAdder(&localResults_.back()); } -protected: + protected: void addOperationHelper(Operation* op) {} /** @@ -151,7 +151,7 @@ protected: * @brief ResultsAdder offers easy ways to quickly store operation results. */ class ResultsAdder { - public: + public: explicit ResultsAdder(LocalOperationResult* localResult) : localResult_(localResult) {} template @@ -172,11 +172,11 @@ protected: addResult(args...); } - protected: + protected: LocalOperationResult* localResult_; }; -protected: + protected: DoOperationRequest request_; std::vector inputIovs_; struct LocalOperationResult { @@ -214,7 +214,7 @@ struct ParameterSegments { * waiting until all parameters are received to CPU host end. */ class ParameterClient2 : public BaseClient { -public: + public: /** Constructor. * @param separate True if sending and recieving activities are separated * into 2 threads, otherwise false. @@ -232,7 +232,7 @@ public: static int calcParameterBlockSize(const std::vector& parameters, size_t serviceNum); -public: + public: bool init(const std::vector& parameters); /// service functions @@ -514,7 +514,7 @@ public: void setForwardbackwardTime(uint64_t delta) { forwardbackwordTime_ = delta; } #endif -protected: + protected: template void multiCall(const char* funcName, const ProtoIn& request, @@ -529,7 +529,7 @@ protected: } } -private: + private: void destroy(); /** @@ -573,7 +573,7 @@ private: /// start necessary threads for threadPool void initThreads(); -protected: + protected: /// start port number of pserver /// it deduce all ports for dense and sparse with some rules int port_; diff --git a/paddle/pserver/ParameterServer2.h b/paddle/pserver/ParameterServer2.h index 3ed06b6b045802bcfd48bcff6bd0c1b34e9bbb86..0b8ef5c170c01ec8a5d53f01db9888f82ca68eec 100644 --- a/paddle/pserver/ParameterServer2.h +++ b/paddle/pserver/ParameterServer2.h @@ -71,7 +71,7 @@ namespace paddle { * to prevent from being polluted. */ class ParameterServer2 : public ProtoServer { -protected: + protected: /// parameter_ mutex. RWLock parameterMutex_; @@ -169,7 +169,7 @@ protected: template class ReadWriteBuffer : public std::vector> { - public: + public: static_assert(sizeof(T) % AlignBytes == 0 || AlignBytes % sizeof(T) == 0, "Type T must be able to aligned."); @@ -229,7 +229,7 @@ protected: return r; } - private: + private: size_t curOffset_; }; @@ -298,17 +298,17 @@ protected: /// barrier performance tuning sync-sgd required std::atomic batchId_; -public: + public: struct Buffer { real* base; size_t size; }; -protected: + protected: /// async gradient commit control bool asyncGrdientCommitCheckAndStat(const SendParameterRequest& request); -public: + public: /// disable default parameter for overloading /// @rdmaCpu:the id of cpu core hosting RDMA server(0-N) /// -1 means using TCP transport instead of RDMA @@ -437,7 +437,7 @@ public: void saveValueVector(const SaveValueRequest& request, ProtoResponseCallback callback); -public: + public: /** * @brief initialize parameter server */ @@ -512,7 +512,7 @@ public: SendParameterResponse* response, std::vector* outputBuffers); -protected: + protected: void mergeSegments(BlockSegments* segments); /// set the unused segments to zero @@ -641,7 +641,7 @@ protected: const VectorPtr vecs[], const ParameterOptimizer::TraverseCallback& callback); -public: + public: typedef void (ParameterServer2::*OperatorFunction)(const Operation& operation, OperationResult* result); diff --git a/paddle/pserver/ParameterServerController.h b/paddle/pserver/ParameterServerController.h index 3a9bc74edf240a12fe1f7bd266f0311555349311..1308d62fb1787f19123fe37d49f8e14039c5a39a 100644 --- a/paddle/pserver/ParameterServerController.h +++ b/paddle/pserver/ParameterServerController.h @@ -28,7 +28,7 @@ namespace paddle { * by gflags or proto. */ class ParameterServerController final { -public: + public: DISABLE_COPY(ParameterServerController); /** @@ -67,7 +67,7 @@ public: */ void wait(); -private: + private: std::vector> parameterServers_; }; diff --git a/paddle/pserver/ProtoServer.h b/paddle/pserver/ProtoServer.h index 3f78799dbfe1d4b80249e8cb27f269e6358903dd..2943867de5885ab1af1aa0f69e93a931092b28e3 100644 --- a/paddle/pserver/ProtoServer.h +++ b/paddle/pserver/ProtoServer.h @@ -34,7 +34,7 @@ namespace paddle { * for single NIC hardward with --port=N(N>1) for small cluster job. */ class ProtoServer : public SocketServer { -public: + public: /// rdmaCpu controls the cpu affinity of RDMA server daemon, /// which could benifit performance. rdmaCpu = -1 means TCP /// is used instead of RDMA transport. @@ -87,7 +87,7 @@ public: std::unique_ptr msgReader, ProtoResponseCallbackEx callback)> func); -protected: + protected: /** * @brief handle rpc request * @param[in] msgReader Message reader for reading data from connection @@ -111,7 +111,7 @@ protected: void registerServiceFunctionImp(const std::string& funcName, ServiceFunction func); -protected: + protected: /// Tuning bare network overhead: the beginning of receiving request ThreadLocal handleRequestBegin_; @@ -120,7 +120,7 @@ protected: }; class ProtoClient : public SocketClient { -public: + public: ProtoClient(const std::string& serverAddr, int serverPort, enum ChannelType channelType = F_TCP) diff --git a/paddle/pserver/SocketChannel.h b/paddle/pserver/SocketChannel.h index c0f30d0db760045a8c0cb001fcadaae8f0c03f9d..8b45ac56090ef82e77514566e7df6b366958655e 100644 --- a/paddle/pserver/SocketChannel.h +++ b/paddle/pserver/SocketChannel.h @@ -33,7 +33,7 @@ enum ChannelType { /// reading a set of blocks of data from SocketChannel. class MsgReader { -public: + public: MsgReader(SocketChannel* channel, size_t numIovs); ~MsgReader() { /// ensure all data blocks have been processed @@ -75,7 +75,7 @@ public: void readBlocks(const std::vector& bufs); void readNextBlock(void* buf); -protected: + protected: SocketChannel* channel_; std::vector blockLengths_; size_t currentBlockIndex_; @@ -84,7 +84,7 @@ protected: /// APIs for reading and writing byte stream data or naive iov data /// from the APIs both RDMA and TCP exhibits byte stream style class SocketChannel { -public: + public: SocketChannel(int socket, const std::string& peerName) : tcpSocket_(socket), peerName_(peerName) { tcpRdma_ = F_TCP; @@ -137,7 +137,7 @@ public: /// return null to indicate socket is closed std::unique_ptr readMessage(); -protected: + protected: struct MessageHeader { int64_t totalLength; /// include the header int64_t numIovs; diff --git a/paddle/pserver/SparseParameterDistribution.h b/paddle/pserver/SparseParameterDistribution.h index 13f199548d56262e77e91e45052f3e435dea407c..e168f36c75e9452fff547f139a67a553cc6b796a 100644 --- a/paddle/pserver/SparseParameterDistribution.h +++ b/paddle/pserver/SparseParameterDistribution.h @@ -31,7 +31,7 @@ namespace paddle { * if unbalanced distribution exhibts by default. */ class SparseParameterDistribution { -public: + public: /// serviceNum means the number of ParameterServers explicit SparseParameterDistribution(size_t serviceNum); ~SparseParameterDistribution() {} @@ -39,7 +39,7 @@ public: void probeDistribution(int serverId, size_t data); void checkAndResetDistribution(); -private: + private: std::vector data_; std::atomic totBytes_; diff --git a/paddle/pserver/test/SocketTest.cpp b/paddle/pserver/test/SocketTest.cpp index 6019dccaadf7fab5a1db7183c07cbbd9562dab2e..206cd17c379f529579c103893cfb492524bc6f8d 100644 --- a/paddle/pserver/test/SocketTest.cpp +++ b/paddle/pserver/test/SocketTest.cpp @@ -30,12 +30,12 @@ struct MessageHeader { }; class Thread { -public: + public: void start(); virtual void run() = 0; virtual ~Thread() {} -protected: + protected: std::unique_ptr thread_; }; @@ -44,13 +44,13 @@ void Thread::start() { } class SocketChannel { -public: + public: explicit SocketChannel(int socket) : socket_(socket) {} int getSocketFd() const { return socket_; } uint64_t readAll(void* buf, size_t size); uint64_t writeAll(const void* buf, size_t size); -protected: + protected: int socket_; }; @@ -79,7 +79,7 @@ uint64_t SocketChannel::writeAll(const void* buf, size_t size) { } class SocketWorker : public Thread { -public: + public: explicit SocketWorker(int socket) : channel_(socket) {} virtual void run(); @@ -88,19 +88,19 @@ public: // write n bytes -protected: + protected: SocketChannel channel_; std::string buffer_; }; class SocketServer : public Thread { -public: + public: explicit SocketServer(int port) : port_(port), socket_(0), maxPendingConnections_(100) {} virtual void run(); -protected: + protected: int port_; int socket_; int maxPendingConnections_; @@ -161,11 +161,11 @@ void SocketWorker::run() { } class SocketClient { -public: + public: SocketClient(const std::string& serverAddr, int serverPort); SocketChannel* getChannel() const { return channel_.get(); } -protected: + protected: std::unique_ptr channel_; }; diff --git a/paddle/pserver/test/test_ParameterServer2.cpp b/paddle/pserver/test/test_ParameterServer2.cpp index e742cd0871da865e02a60a125a936eea8f15e575..01d179258dffaf996a57022801ee3bd60a268f77 100644 --- a/paddle/pserver/test/test_ParameterServer2.cpp +++ b/paddle/pserver/test/test_ParameterServer2.cpp @@ -26,7 +26,7 @@ DEFINE_string(server_addr, "127.0.0.1", "assign server address"); DEFINE_int32(server_cpu, 0, "assign server cpu"); class ParameterServer2Tester : public ParameterServer2 { -public: + public: ParameterServer2Tester(std::string serverAddr, int port, int rdmaCpu = -1, @@ -88,7 +88,7 @@ public: void waitPassFinishTest(); void synchronizeTest(); -protected: + protected: ParameterClient2 client_; vector clientConfigs_; vector parameters_; diff --git a/paddle/pserver/test/test_ProtoServer.cpp b/paddle/pserver/test/test_ProtoServer.cpp index d68a8d2180cc3081346106132799498f6dc3fa20..a66b14a1cc58d11988e4936a9c35d98b8bf5edc1 100644 --- a/paddle/pserver/test/test_ProtoServer.cpp +++ b/paddle/pserver/test/test_ProtoServer.cpp @@ -28,7 +28,7 @@ DEFINE_bool(benchmark, false, "Do benchmark. Skip some tests"); using namespace paddle; // NOLINT class MyServer : public ProtoServer { -public: + public: explicit MyServer(int port, int rdmaCpu = -1) : ProtoServer(FLAGS_server_addr, port, rdmaCpu), status_(PSERVER_STATUS_NOT_SET) { @@ -62,7 +62,7 @@ public: callback(response); } -protected: + protected: PServerStatus status_; std::string buffer_; }; diff --git a/paddle/trainer/NewRemoteParameterUpdater.h b/paddle/trainer/NewRemoteParameterUpdater.h index 6223ba427c9b94494c2bee8f0847442f1b0574c9..02693c675e6f5cb574e52e9681963a5904676028 100644 --- a/paddle/trainer/NewRemoteParameterUpdater.h +++ b/paddle/trainer/NewRemoteParameterUpdater.h @@ -29,7 +29,7 @@ namespace paddle { * New remote parameter updater for dense parameters that use cclient of go. */ class NewRemoteParameterUpdater : public ParameterUpdater { -public: + public: NewRemoteParameterUpdater(const OptimizationConfig& config, const std::string pserverSpec); NewRemoteParameterUpdater(const OptimizationConfig& config, @@ -61,13 +61,13 @@ public: virtual void startPass(); virtual bool finishPass(); -protected: + protected: /** * work need to do after finishBatch */ virtual void updateImpl(Parameter* para); -private: + private: int parameterSize() { return (int)parameters_.size(); } /** @@ -104,7 +104,7 @@ private: } } -protected: + protected: const OptimizationConfig& trainerConfig_; /// internal parameter client object for exchanging data with pserver paddle_pserver_client parameterClient_; diff --git a/paddle/trainer/ParamUtil.h b/paddle/trainer/ParamUtil.h index 2e05595848760c9abd7d916003656c8103151abf..10746b4d58e3a82c081987a6aaad9e0b42272a03 100644 --- a/paddle/trainer/ParamUtil.h +++ b/paddle/trainer/ParamUtil.h @@ -56,7 +56,7 @@ struct ParameterUtilConfig { * Utility class for loading and saving parameters */ class ParameterUtil { -public: + public: /** * Ctor. * @@ -115,7 +115,7 @@ public: } } -private: + private: std::shared_ptr config_; std::unique_ptr intConfig_; GradientMachinePtr gserver_; diff --git a/paddle/trainer/ParameterUpdater.h b/paddle/trainer/ParameterUpdater.h index 9e9e948b8856d2712f8894b3d14db9c795d5f694..ef7ab92eca77bab2a8481561713f8034d2b8505d 100644 --- a/paddle/trainer/ParameterUpdater.h +++ b/paddle/trainer/ParameterUpdater.h @@ -36,7 +36,7 @@ namespace paddle { * @brief Parameter Updater for SGD, and local(not cluster) run. */ class SgdLocalUpdater : public ParameterUpdater { -public: + public: /** * @brief Ctor. Initialize optimizer locally by optConfig. * @param optConfig optimization config. @@ -131,7 +131,7 @@ public: } } -protected: + protected: /** * @brief update method. Update value from gradient. * @param para parameter that will be updated. @@ -159,7 +159,7 @@ protected: * @deprecated */ class SgdCpuUpdater : public SgdLocalUpdater, public Deprecated { -public: + public: explicit SgdCpuUpdater(const OptimizationConfig& optConfig) : SgdLocalUpdater(optConfig), Deprecated( @@ -178,7 +178,7 @@ public: optimizer_->finishBatch(); } -protected: + protected: /** * @brief do nothing. * @param para @@ -192,7 +192,7 @@ protected: * It will do model average in cpu to reduce gpu memory comsuption. */ class SgdUpdaterWithCpuAverager : public SgdLocalUpdater { -public: + public: /** * @brief Ctor. * @@ -233,12 +233,12 @@ public: */ virtual void restore(); -protected: + protected: virtual void updateImpl(Parameter* para); void updateFunc(Parameter* para); -protected: + protected: std::unique_ptr averager_; /** diff --git a/paddle/trainer/RemoteParameterUpdater.h b/paddle/trainer/RemoteParameterUpdater.h index 5e82c944751629632ea8d16992bd8f4178a2fbd5..3a40a46354efd6b92278884c8f5b72504a3ff283 100644 --- a/paddle/trainer/RemoteParameterUpdater.h +++ b/paddle/trainer/RemoteParameterUpdater.h @@ -53,7 +53,7 @@ namespace paddle { * backward and communication is not supported. */ class RemoteParameterUpdater : public ParameterUpdater { -public: + public: RemoteParameterUpdater( const OptimizationConfig& config, int expectedPassCount, @@ -101,7 +101,7 @@ public: virtual void apply(); virtual void restore(); -protected: + protected: /** * control all pservers with all trainers for sync-sgd */ @@ -128,7 +128,7 @@ protected: */ void copyParametersFromDevice(ParameterType parameterType); -protected: + protected: /// Optimization config used to guide initialization and finishBatch OptimizationConfig config_; /// internal parameter client object for exchanging data with pserver @@ -178,7 +178,7 @@ protected: * It contains separate send and recv thread for pipeline usage. */ class ConcurrentRemoteParameterUpdater : public RemoteParameterUpdater { -public: + public: ConcurrentRemoteParameterUpdater( OptimizationConfig config, int expectedPassCount, @@ -194,7 +194,7 @@ public: */ virtual void finishBatch(real cost); -protected: + protected: virtual void updateImpl(Parameter* para); /// internal thread called in send thread void send(Parameter* para); // para == NULL indicate end of a minibatch @@ -221,7 +221,7 @@ protected: return (numBatches_ + 1) % config_.num_batches_per_send_parameter() == 0; } -private: + private: /// send thread used for overlapping std::unique_ptr sendThread_; /// recv thread used for overlapping @@ -263,7 +263,7 @@ private: * to encapsulate sparse specified message for all pservers. */ class SparseRemoteParameterUpdater : public ParameterUpdater { -public: + public: SparseRemoteParameterUpdater(const OptimizationConfig& config, int expectedPassCount, bool testing); @@ -303,7 +303,7 @@ public: } #endif -protected: + protected: /// update implimentation, not implemented virtual void updateImpl(Parameter* para) {} @@ -313,7 +313,7 @@ protected: /// start controller thread void startController(); -protected: + protected: /// optimization config OptimizationConfig config_; /// internal parameter client @@ -335,7 +335,7 @@ protected: * it directly call internal dense and sparse udpater individually. */ class SparseRemoteParameterUpdaterComposite : public ParameterUpdaterComposite { -public: + public: enum { UPDATER_SPARSE_REMOTE = 0, // execute in sync thread pool(tid:0) UPDATER_NORMAL = 1, // execute in Owner thread(tid:1) @@ -364,7 +364,7 @@ public: }; class ParameterUpdaterCreators { -public: + public: /** * @brief add a creator to create custom ParameterUpdater while training. * The creator is a function with type (alogrithm, optConfig, isLocal, @@ -407,7 +407,7 @@ public: return nullptr; } -private: + private: static std::vector> constructors_; diff --git a/paddle/trainer/Tester.h b/paddle/trainer/Tester.h index e892744db278586f2fd5b3cb527aa7c17752c477..801c77e3116369732bf4b03107adce6a71dc2184 100644 --- a/paddle/trainer/Tester.h +++ b/paddle/trainer/Tester.h @@ -38,7 +38,7 @@ namespace paddle { * It is a private class for Trainer. */ class Tester { -public: + public: /** * Ctor * @param config Trainer Config. @@ -87,7 +87,7 @@ public: */ void test(); -protected: + protected: std::shared_ptr testParameterClient_; std::shared_ptr config_; std::unique_ptr intconfig_; @@ -107,7 +107,7 @@ protected: real cost; } testContext_; -private: + private: /** * Test one batch by batchId. It is only used for testOnePass. * diff --git a/paddle/trainer/ThreadParameterUpdater.h b/paddle/trainer/ThreadParameterUpdater.h index bc08a9e9f0eda1cab7776ba76c67e88add1028a9..b5e6a7ce3c8457364b10c921bca3386fbb6f6cbf 100644 --- a/paddle/trainer/ThreadParameterUpdater.h +++ b/paddle/trainer/ThreadParameterUpdater.h @@ -39,7 +39,7 @@ namespace paddle { class. */ class SgdThreadUpdater : public ParameterUpdater { -public: + public: explicit SgdThreadUpdater(const OptimizationConfig& optConfig); virtual ~SgdThreadUpdater() {} @@ -57,7 +57,7 @@ public: virtual void apply(); virtual void restore(); -protected: + protected: // This is the function that will be eventualy called by the GradientMachine. // used only for GPU update. virtual void updateImpl(Parameter* para); diff --git a/paddle/trainer/Trainer.h b/paddle/trainer/Trainer.h index fac589d1d711affcd008f90edf87d865c8362f69..78127b7be5cef34f51a4b540852c139625b571dd 100644 --- a/paddle/trainer/Trainer.h +++ b/paddle/trainer/Trainer.h @@ -41,7 +41,7 @@ namespace paddle { * train/test a NeuralNetwork. */ class Trainer { -public: + public: /** * Ctor. * @return @@ -138,7 +138,7 @@ public: */ ParameterUtil* getParameterUtilPtr(); -protected: + protected: /** * Train one pass of data. * @@ -159,10 +159,10 @@ protected: void createTester(); -private: + private: std::unique_ptr createTesterConfig(); -protected: + protected: std::shared_ptr config_; std::shared_ptr stats_; diff --git a/paddle/trainer/TrainerConfigHelper.h b/paddle/trainer/TrainerConfigHelper.h index f1366cc041b0d983e65a1bf5b02ec2128324c5a8..b21dda964e70fce6e5e9672cc131595ad5af3bbc 100644 --- a/paddle/trainer/TrainerConfigHelper.h +++ b/paddle/trainer/TrainerConfigHelper.h @@ -37,7 +37,7 @@ class DataConfig; * Define a macro to unify 'final' keyword */ class TrainerConfigHelper /*final*/ { -public: + public: DISABLE_COPY(TrainerConfigHelper); /** @@ -193,7 +193,7 @@ public: */ static std::shared_ptr createFromFlagConfig(); -private: + private: static std::string getConfigNameFromPassId(int passId, const std::string& modelPath); diff --git a/paddle/trainer/TrainerInternal.h b/paddle/trainer/TrainerInternal.h index 7018faab24744f7a087a53130acc56ec6314101e..48ee53a5e60f950bfc3cc299c754b0e72601c818 100644 --- a/paddle/trainer/TrainerInternal.h +++ b/paddle/trainer/TrainerInternal.h @@ -34,7 +34,7 @@ namespace paddle { * the core training class for driving training logic */ class TrainerInternal { -public: + public: struct ParaStat { real maxAbsGrad; real avgAbsGrad; @@ -126,7 +126,7 @@ public: UpdateCallback updateCallback, bool doPipelineUpdate); -protected: + protected: std::shared_ptr parameterUpdater_; GradientMachinePtr gradientMachine_; std::shared_ptr config_; diff --git a/paddle/trainer/TrainerInternalConfig.h b/paddle/trainer/TrainerInternalConfig.h index b47692720efc2ed4f2db84f61ca81fcb52d234c0..43aae381029784278ad58c9398f64af24dffa1df 100644 --- a/paddle/trainer/TrainerInternalConfig.h +++ b/paddle/trainer/TrainerInternalConfig.h @@ -37,7 +37,7 @@ namespace paddle { * through one mini-batch. */ class TrainerStats { -public: + public: /** * @brief reset all stats. * @@ -147,7 +147,7 @@ public: return os.str(); } -private: + private: int64_t numProcessed_; real totalCost_; real currentCost_; diff --git a/paddle/trainer/tests/picojson.h b/paddle/trainer/tests/picojson.h index eaa8b9baf6e4e753a441ab77811f494cbdab80cf..75349537b1c7f10d23bae788e8414a753c7ccab0 100644 --- a/paddle/trainer/tests/picojson.h +++ b/paddle/trainer/tests/picojson.h @@ -125,7 +125,7 @@ enum { INDENT_WIDTH = 2 }; struct null {}; class value { -public: + public: typedef std::vector array; typedef std::map object; union _storage { @@ -139,11 +139,11 @@ public: object* object_; }; -protected: + protected: int type_; _storage u_; -public: + public: value(); value(int type, bool); explicit value(bool b); @@ -179,7 +179,7 @@ public: void serialize(Iter os, bool prettify = false) const; std::string serialize(bool prettify = false) const; -private: + private: template value(const T*); // intentionally defined to block implicit conversion of // pointer to bool @@ -588,13 +588,13 @@ inline std::string value::_serialize(int indent) const { template class input { -protected: + protected: Iter cur_, end_; int last_ch_; bool ungot_; int line_; -public: + public: input(const Iter& first, const Iter& last) : cur_(first), end_(last), last_ch_(-1), ungot_(false), line_(1) {} int getc() { @@ -873,7 +873,7 @@ inline bool _parse(Context& ctx, input& in) { } class deny_parse_context { -public: + public: bool set_null() { return false; } bool set_bool(bool) { return false; } #ifdef PICOJSON_USE_INT64 @@ -898,10 +898,10 @@ public: }; class default_parse_context { -protected: + protected: value* out_; -public: + public: default_parse_context(value* out) : out_(out) {} bool set_null() { *out_ = value(); @@ -949,18 +949,18 @@ public: return _parse(ctx, in); } -private: + private: default_parse_context(const default_parse_context&); default_parse_context& operator=(const default_parse_context&); }; class null_parse_context { -public: + public: struct dummy_str { void push_back(int) {} }; -public: + public: null_parse_context() {} bool set_null() { return true; } bool set_bool(bool) { return true; } @@ -985,7 +985,7 @@ public: return _parse(*this, in); } -private: + private: null_parse_context(const null_parse_context&); null_parse_context& operator=(const null_parse_context&); }; diff --git a/paddle/trainer/tests/test_TrainerOnePass.cpp b/paddle/trainer/tests/test_TrainerOnePass.cpp index b2a93d4d5eea37ad716b59427f2aa4409d2f537d..de12c4d649c6041f497c0eeac0904ebfc0d5bf97 100644 --- a/paddle/trainer/tests/test_TrainerOnePass.cpp +++ b/paddle/trainer/tests/test_TrainerOnePass.cpp @@ -38,7 +38,7 @@ DECLARE_int32(num_passes); DECLARE_int32(saving_period); class TrainerForTest : public paddle::Trainer { -public: + public: inline const std::shared_ptr& getParameterUpdaterForTest() { return this->trainerInternal_.getParameterUpdater(); } diff --git a/paddle/utils/ClassRegistrar.h b/paddle/utils/ClassRegistrar.h index 1ac27bafabd1945d1d01e3bead22b0dd200d8688..5f40a0b25e92c7adcfe3f8c4be96016be801da3b 100644 --- a/paddle/utils/ClassRegistrar.h +++ b/paddle/utils/ClassRegistrar.h @@ -41,7 +41,7 @@ namespace paddle { */ template class ClassRegistrar { -public: + public: typedef std::function ClassCreator; // Register a class using a creation function. @@ -74,7 +74,7 @@ public: } } -protected: + protected: std::map creatorMap_; }; diff --git a/paddle/utils/CpuId.h b/paddle/utils/CpuId.h index 869be5be541dafd699a87a8e8893aadadf59b711..ed58211d13ac1e0f80d6728950f0b88dc0ae625f 100644 --- a/paddle/utils/CpuId.h +++ b/paddle/utils/CpuId.h @@ -35,7 +35,7 @@ enum simd_t { // clang-format on class SIMDFlags final { -public: + public: DISABLE_COPY(SIMDFlags); SIMDFlags(); @@ -46,7 +46,7 @@ public: return !((simd_flags_ & flags) ^ flags); } -private: + private: int simd_flags_ = SIMD_NONE; }; diff --git a/paddle/utils/CustomStackTrace.h b/paddle/utils/CustomStackTrace.h index 52a6df94979fd3d8d7d540ed0e3898bb3375d975..b60077ea2d946366910780eeb773635972211e04 100644 --- a/paddle/utils/CustomStackTrace.h +++ b/paddle/utils/CustomStackTrace.h @@ -49,7 +49,7 @@ namespace paddle { */ template class CustomStackTrace { -public: + public: /** * @brief Pop out an item from the top of the stack if item == top. * Else, just set status to popping. @@ -136,7 +136,7 @@ public: p.push(item); } -private: + private: /** * Get thread local attribute, and save them into a map (threadId => TYPE*) * @@ -174,7 +174,7 @@ private: return this->getThreadLocal(this->isPushing_, this->pushingBuffers_); } -private: + private: mutable std::mutex mtx_; std::unordered_map*> stackBuffers_; diff --git a/paddle/utils/Error.h b/paddle/utils/Error.h index 7cde98306026ca1de76089749aaea265d151da33..1fc8482e3a1bef869d4df147bbd3cab6e62ccf49 100644 --- a/paddle/utils/Error.h +++ b/paddle/utils/Error.h @@ -95,7 +95,7 @@ namespace paddle { * log(FATAL) and CHECK in Paddle, 'check' method will be removed. */ class Error { -public: + public: /** * Construct a no-error value. */ @@ -138,7 +138,7 @@ public: */ bool isOK() const { return msg_ == nullptr; } -private: + private: std::shared_ptr msg_; }; diff --git a/paddle/utils/GlobalConstants.h b/paddle/utils/GlobalConstants.h index 0ec1c28dfbb2a7db9fa84c9eb2bc4dad806b78e9..3f45e82268435e4c22d1879e909b0c90838d6693 100644 --- a/paddle/utils/GlobalConstants.h +++ b/paddle/utils/GlobalConstants.h @@ -78,7 +78,7 @@ enum ParameterType { using namespace enumeration_wrapper; // NOLINT class TrainAlgorithm { -public: + public: static const std::string SGD; static const std::string AsyncSGD; static const std::string OWLQN; diff --git a/paddle/utils/Locks.h b/paddle/utils/Locks.h index e87abb9139f1c3f250f8b8fe1afdd8883f682647..65f983685f5e178345a6a875a79a6573ce1ccca1 100644 --- a/paddle/utils/Locks.h +++ b/paddle/utils/Locks.h @@ -42,7 +42,7 @@ namespace paddle { * Use unlock() to unlock the lock. */ class RWLock { -public: + public: RWLock() { pthread_rwlock_init(&rwlock_, NULL); } ~RWLock() { pthread_rwlock_destroy(&rwlock_); } RWLock(const RWLock&) = delete; @@ -62,7 +62,7 @@ public: void lock_shared() { pthread_rwlock_rdlock(&rwlock_); } void unlock() { pthread_rwlock_unlock(&rwlock_); } -protected: + protected: pthread_rwlock_t rwlock_; }; @@ -71,7 +71,7 @@ protected: * using RAII management mechanism. */ class ReadLockGuard { -public: + public: /** * @brief Construct Function. Lock on rwlock in read mode. */ @@ -86,7 +86,7 @@ public: */ ~ReadLockGuard() { rwlock_->unlock(); } -protected: + protected: RWLock* rwlock_; }; @@ -98,7 +98,7 @@ protected: */ class SpinLockPrivate; class SpinLock { -public: + public: DISABLE_COPY(SpinLock); SpinLock(); ~SpinLock(); @@ -107,7 +107,7 @@ public: void lock(); void unlock(); -private: + private: SpinLockPrivate* m; }; @@ -116,7 +116,7 @@ private: */ class SemaphorePrivate; class Semaphore { -public: + public: //! Disable copy & assign Semaphore(const Semaphore& other) = delete; Semaphore& operator=(const Semaphore&& other) = delete; @@ -124,7 +124,7 @@ public: //! Enable move. Semaphore(Semaphore&& other) : m(std::move(other.m)) {} -public: + public: /** * @brief Construct Function. * @param[in] initValue the initial value of the @@ -156,7 +156,7 @@ public: */ void post(); -private: + private: SemaphorePrivate* m; }; @@ -166,7 +166,7 @@ private: */ class ThreadBarrierPrivate; class ThreadBarrier { -public: + public: DISABLE_COPY(ThreadBarrier); /** @@ -184,7 +184,7 @@ public: */ void wait(); -private: + private: ThreadBarrierPrivate* m; }; @@ -192,7 +192,7 @@ private: * A wrapper for condition variable with mutex. */ class LockedCondition : public std::condition_variable { -public: + public: /** * @brief execute op and notify one thread which was blocked. * @param[in] op a thread can do something in op before notify. @@ -235,7 +235,7 @@ public: */ std::mutex* mutex() { return &mutex_; } -protected: + protected: std::mutex mutex_; }; diff --git a/paddle/utils/PythonUtil.h b/paddle/utils/PythonUtil.h index daebaffc855518425ae43942c22ec150d2e327f0..6f8d7e09309503e47aca7ae2d20774c748703b21 100644 --- a/paddle/utils/PythonUtil.h +++ b/paddle/utils/PythonUtil.h @@ -55,12 +55,12 @@ std::string callPythonFunc(const std::string& moduleName, * NOTE: the lock of this guard is reentrant or recursive. */ class PyGuard { -public: + public: PyGuard(); PyGuard(const PyGuard& other) = delete; PyGuard& operator=(const PyGuard& other) = delete; -private: + private: std::lock_guard guard_; }; @@ -133,7 +133,7 @@ std::string getPyCallStack(); * Implements getAttr method for object. */ class ObjectHelper { -public: + public: explicit ObjectHelper(const PyObjectPtr& obj) : obj_(obj) {} /** @@ -192,7 +192,7 @@ public: return PyObject_IsTrue(tmp.get()); } -private: + private: const PyObjectPtr& obj_; }; @@ -202,7 +202,7 @@ private: * The python sequence means list or tuple. */ class SequenceHelper { -public: + public: explicit SequenceHelper(const PyObjectPtr& seq) : seq_(seq.get()) { CHECK(PySequence_Check(seq_)); } @@ -248,12 +248,12 @@ public: } } -private: + private: PyObject* seq_; }; class DictHelper { -public: + public: explicit DictHelper(PyObject* d) : dict_(d) {} explicit DictHelper(const PyObjectPtr& d) : dict_(d.get()) {} @@ -275,7 +275,7 @@ public: this->set(key, list); } -private: + private: inline void checkDict() { CHECK(PyDict_Check(this->dict_)); } PyObject* dict_; @@ -289,7 +289,7 @@ inline static bool isCallable(const PyObjectPtr& obj) { * Wrap a callable object. */ class CallableHelper { -public: + public: explicit CallableHelper(const PyObjectPtr& obj) : obj_(obj) { CHECK(py::isCallable(obj_)); } @@ -315,7 +315,7 @@ public: return PyObject_Call(obj_.get(), args.get(), kwargs.get()); } -private: + private: const PyObjectPtr& obj_; PyObjectPtr args; PyObjectPtr kwargs; diff --git a/paddle/utils/Queue.h b/paddle/utils/Queue.h index f054738f87c02d2d749eec8d6c7bb55b506a6d91..189e1a14f7b2d133408a50418d96431164248f0e 100644 --- a/paddle/utils/Queue.h +++ b/paddle/utils/Queue.h @@ -56,7 +56,7 @@ namespace paddle { */ template class Queue { -public: + public: /** * @brief Construct Function. Default capacity of Queue is zero. */ @@ -147,7 +147,7 @@ public: }); } -private: + private: std::deque elements_; int numElements_; std::mutex queueLock_; @@ -185,7 +185,7 @@ private: */ template class BlockingQueue { -public: + public: /** * @brief Construct Function. * @param[in] capacity the max numer of elements the queue can have. @@ -244,7 +244,7 @@ public: return queue_.empty(); } -private: + private: std::mutex mutex_; std::condition_variable notEmpty_; std::condition_variable notFull_; diff --git a/paddle/utils/Stat.h b/paddle/utils/Stat.h index 79fd3b8cf043e62922dfd046754ee8ac261990c5..100e9eba909466fcca57f755405ab63b638a8ebd 100644 --- a/paddle/utils/Stat.h +++ b/paddle/utils/Stat.h @@ -33,7 +33,7 @@ namespace paddle { class Stat; class StatInfo { -public: + public: explicit StatInfo(Stat* stat = nullptr) : stat_(stat) { total_ = 0; max_ = 0; @@ -61,7 +61,7 @@ class Stat; typedef std::shared_ptr StatPtr; class StatSet { -public: + public: explicit StatSet(const std::string& name) : name_(name) {} ~StatSet() {} @@ -102,7 +102,7 @@ public: // pserver code logic, -_- ). void reset(bool clearRawData = true); -private: + private: std::unordered_map statSet_; const std::string name_; RWLock lock_; @@ -112,7 +112,7 @@ extern StatSet globalStat; /*@brief : a simple stat*/ class Stat { -public: + public: explicit Stat(const std::string& statName) : destructStat_(nullptr), name_(statName), openThreadInfo_(false) {} ~Stat() {} @@ -137,7 +137,7 @@ public: friend class StatInfo; -private: + private: void mergeThreadStat(StatInfo& allThreadStat); std::mutex lock_; @@ -164,7 +164,7 @@ inline uint64_t nowInMicroSec() { * A simple help class to measure time interval */ class Timer { -public: + public: explicit Timer(bool autoStart = true) : total_(0), startStamp_(0) { if (autoStart) { start(); @@ -181,13 +181,13 @@ public: void reset() { total_ = 0; } -protected: + protected: uint64_t total_; uint64_t startStamp_; }; class TimerOnce { -public: + public: TimerOnce(Stat* stat, const char* info = "", uint64_t threshold = -1, @@ -208,7 +208,7 @@ public: stat_->addSample(span); } -private: + private: Stat* stat_; const char* info_; Timer timer_; @@ -280,11 +280,11 @@ inline StatSet& registerTimerArg2(uint64_t threshold = -1, #endif // DISABLE_TIMER class GpuProfiler final { -public: + public: GpuProfiler(std::string statName, std::string info); ~GpuProfiler(); -private: + private: std::lock_guard guard_; }; diff --git a/paddle/utils/Thread.h b/paddle/utils/Thread.h index ef36a8c5b2b0e95d759da8a781d781b71d067b7a..2ee6eba1a68202282537788160a77f7689a2ffdb 100644 --- a/paddle/utils/Thread.h +++ b/paddle/utils/Thread.h @@ -29,7 +29,7 @@ namespace paddle { */ class Thread { -public: + public: /** * @brief Construct Function. Default thread pointer is null. */ @@ -62,7 +62,7 @@ public: */ virtual void run() = 0; -protected: + protected: std::unique_ptr thread_; }; @@ -73,7 +73,7 @@ protected: * Use addJob() to add a new job to the job queue. */ class ThreadWorker : protected Thread { -public: + public: typedef std::function JobFunc; /** @@ -116,7 +116,7 @@ public: finishCV_.wait([this] { return empty_; }); } -protected: + protected: /** * @brief Execute jobs in the job queue sequentianlly, * @note If finish all the jobs in the job queue, @@ -150,7 +150,7 @@ protected: * JobFunc can use tid to divide input data. */ class SyncThreadPool { -public: + public: typedef std::function JobFunc; /** @@ -236,7 +236,7 @@ public: } } -protected: + protected: /** * @brief Start all the workers in the pool, call their run() function. */ @@ -285,7 +285,7 @@ protected: } } -protected: + protected: pid_t ownerThreadId_; bool stopping_; ThreadBarrier jobStartBarrier_; @@ -323,7 +323,7 @@ protected: */ template class MultiThreadWorker { -public: + public: typedef T ResultType; typedef std::shared_ptr ResultPtrType; typedef std::function JobFunc; @@ -424,7 +424,7 @@ public: */ bool testResult() { return results_.empty(); } -protected: + protected: /** * @brief Do the jobs in the job queue sequentianlly * and enqueue the result into the result queue. @@ -476,7 +476,7 @@ protected: * thread pool. */ class AsyncThreadPool { -public: + public: typedef std::function JobFunc; AsyncThreadPool() { LOG(FATAL) << "Not implemented"; } @@ -594,7 +594,7 @@ public: } } -protected: + protected: /** * @brief Execute the jobs in the job queue. */ @@ -606,7 +606,7 @@ protected: } } -private: + private: std::vector> workers_; Queue jobs_; bool stopping_; diff --git a/paddle/utils/ThreadLocal.h b/paddle/utils/ThreadLocal.h index 0a27b8b97b83a9066af23039a317c437ea56777a..c5b07506d36875ead65887ea2e221e762be0d621 100644 --- a/paddle/utils/ThreadLocal.h +++ b/paddle/utils/ThreadLocal.h @@ -49,7 +49,7 @@ namespace paddle { */ template class ThreadLocal { -public: + public: ThreadLocal() { CHECK_EQ(pthread_key_create(&threadSpecificKey_, dataDestructor), 0); } @@ -92,7 +92,7 @@ public: */ operator T*() { return get(); } -private: + private: static void dataDestructor(void* p) { delete (T*)p; } pthread_key_t threadSpecificKey_; @@ -111,7 +111,7 @@ private: */ template class ThreadLocalD { -public: + public: ThreadLocalD() { CHECK_EQ(pthread_key_create(&threadSpecificKey_, NULL), 0); } ~ThreadLocalD() { pthread_key_delete(threadSpecificKey_); @@ -150,7 +150,7 @@ public: */ T& operator*() { return *get(); } -private: + private: static void dataDestructor(void* p) { delete (T*)p; } void updateMap(T* p) { @@ -172,7 +172,7 @@ private: * @brief Thread-safe C-style random API. */ class ThreadLocalRand { -public: + public: /** * initSeed just like srand, * called by main thread, @@ -205,7 +205,7 @@ public: */ static int getDefaultSeed() { return defaultSeed_; } -protected: + protected: static unsigned int defaultSeed_; static ThreadLocal seed_; }; @@ -214,7 +214,7 @@ protected: * @brief Thread-safe C++ style random engine. */ class ThreadLocalRandomEngine { -public: + public: /** * get random_engine for each thread. * @@ -222,7 +222,7 @@ public: */ static std::default_random_engine& get(); -protected: + protected: static ThreadLocal engine_; }; diff --git a/paddle/utils/Util.h b/paddle/utils/Util.h index 9579881ea3b92abab0189631184bab515afb67a3..e6f05e30d308b8b94935897e947350934a5971ee 100644 --- a/paddle/utils/Util.h +++ b/paddle/utils/Util.h @@ -179,7 +179,7 @@ void loadFileList(const std::string& fileListFileName, */ void registerInitFunction(std::function func, int priority = 0); class InitFunction { -public: + public: explicit InitFunction(std::function func, int priority = 0) { registerInitFunction(func, priority); } @@ -191,7 +191,7 @@ public: * When the SetDevice object is destructed, it will restore device environment. */ class SetDevice { -public: + public: explicit SetDevice(int deviceId) { isSet_ = deviceId >= 0; devId_ = 0; @@ -206,7 +206,7 @@ public: } } -protected: + protected: bool isSet_; int devId_; }; @@ -240,7 +240,7 @@ inline void enablePeerAccess(int d1, int d2) { * } */ class AsyncGpuBlock { -public: + public: AsyncGpuBlock() : syncFlag_(hl_get_sync_flag()) { hl_set_sync_flag(false); } ~AsyncGpuBlock() { if (syncFlag_) { @@ -249,7 +249,7 @@ public: } } -private: + private: bool syncFlag_; }; @@ -378,7 +378,7 @@ std::string join(const std::string& part1, * A Checker for each invoke of method in same thread. */ class SameThreadChecker { -public: + public: SameThreadChecker() {} /** @@ -400,7 +400,7 @@ public: << invokeThreadId_ << " current invoked in " << curThreadId; } -private: + private: std::once_flag onceFlag_; std::thread::id invokeThreadId_; }; @@ -421,7 +421,7 @@ private: */ template class WeakKVCache { -public: + public: WeakKVCache() {} std::shared_ptr get(const KType& key, @@ -442,7 +442,7 @@ public: return retVal; } -private: + private: std::mutex lock_; std::unordered_map, Hash> storage_; }; @@ -453,7 +453,7 @@ private: */ template class ScopedCallbacks { -public: + public: ScopedCallbacks(CallbackType enter, CallbackType exit, Args&... args) : exit_(std::bind(exit, args...)) { enter(args...); @@ -464,7 +464,7 @@ public: ~ScopedCallbacks() { exit_(); } -private: + private: std::function exit_; }; @@ -475,7 +475,7 @@ private: */ template class AlignedAllocator { -public: + public: /// std campatible typedefs. typedef T* pointer; typedef const T* const_pointer; @@ -552,12 +552,12 @@ public: return this->allocate(n); } -private: + private: AlignedAllocator& operator=(const AlignedAllocator&); // disable }; class Deprecated { -public: + public: explicit Deprecated(const std::string& msg = "") { if (msg.empty()) { LOG(WARNING) << "This class is deprecated, please do not use this class."; diff --git a/paddle/utils/arch/linux/Locks.cpp b/paddle/utils/arch/linux/Locks.cpp index a4e6c8f7b8397adc262588612c250bac5ef5eaa6..409af8bce3621c51bfd7a69c6b4ec1f9cc6be8e4 100644 --- a/paddle/utils/arch/linux/Locks.cpp +++ b/paddle/utils/arch/linux/Locks.cpp @@ -19,7 +19,7 @@ limitations under the License. */ namespace paddle { class SemaphorePrivate { -public: + public: sem_t sem; }; @@ -45,7 +45,7 @@ void Semaphore::post() { sem_post(&m->sem); } #ifdef PADDLE_USE_PTHREAD_SPINLOCK class SpinLockPrivate { -public: + public: inline SpinLockPrivate() { pthread_spin_init(&lock_, 0); } inline ~SpinLockPrivate() { pthread_spin_destroy(&lock_); } @@ -63,7 +63,7 @@ public: // clang-format on class SpinLockPrivate { -public: + public: inline void lock() { while (lock_.test_and_set(std::memory_order_acquire)) { } @@ -86,7 +86,7 @@ void SpinLock::unlock() { m->unlock(); } #ifdef PADDLE_USE_PTHREAD_BARRIER class ThreadBarrierPrivate { -public: + public: pthread_barrier_t barrier_; inline explicit ThreadBarrierPrivate(int count) { @@ -101,7 +101,7 @@ public: #else class ThreadBarrierPrivate { -public: + public: pthread_mutex_t mutex_; pthread_cond_t cond_; int count_; diff --git a/paddle/utils/arch/osx/Locks.cpp b/paddle/utils/arch/osx/Locks.cpp index e03992363fd6051a1970664d63406b2e7a47fce3..f3905091bd024ab02c3f5d39cfed6dbc38fabbbc 100644 --- a/paddle/utils/arch/osx/Locks.cpp +++ b/paddle/utils/arch/osx/Locks.cpp @@ -21,7 +21,7 @@ limitations under the License. */ namespace paddle { class SemaphorePrivate { -public: + public: ~SemaphorePrivate() { dispatch_release(sem); } dispatch_semaphore_t sem; @@ -45,7 +45,7 @@ void Semaphore::wait() { void Semaphore::post() { dispatch_semaphore_signal(m->sem); } class SpinLockPrivate { -public: + public: std::atomic_flag lock_ = ATOMIC_FLAG_INIT; char padding_[64 - sizeof(lock_)]; // Padding to cache line size }; @@ -61,7 +61,7 @@ void SpinLock::lock() { void SpinLock::unlock() { m->lock_.clear(std::memory_order_release); } class ThreadBarrierPrivate { -public: + public: pthread_mutex_t mutex_; pthread_cond_t cond_; int count_; diff --git a/tools/codestyle/cpplint_pre_commit.hook b/tools/codestyle/cpplint_pre_commit.hook index 94d1e23ce716f7f1d723bad5f1f4c60030f19eb7..b194af76dc529fd52b0aedfab9c41d625fe64c0d 100755 --- a/tools/codestyle/cpplint_pre_commit.hook +++ b/tools/codestyle/cpplint_pre_commit.hook @@ -4,8 +4,12 @@ TOTAL_ERRORS=0 # The trick to remove deleted files: https://stackoverflow.com/a/2413151 for file in $(git diff --cached --name-status | awk '$1 != "D" {print $2}'); do - cpplint $file; - TOTAL_ERRORS=$(expr $TOTAL_ERRORS + $?); + if [[ $file =~ ^(paddle/api/.*|paddle/capi/.*|paddle/contrib/.*|paddle/cuda/.*|paddle/function/.*|paddle/gserver/.*|paddle/math/.*|paddle/optimizer/.*|paddle/parameter/.*|paddle/pserver/.*|paddle/trainer/.*|paddle/utils/.*) ]]; then + continue; + else + cpplint $file; + TOTAL_ERRORS=$(expr $TOTAL_ERRORS + $?); + fi done exit $TOTAL_ERRORS