Merge pull request #2888 from gangliao/cpplint

FIX: cpplint code style
cblas_new
gangliao 8 years ago committed by GitHub
commit 9b8451cc14

@ -27,7 +27,8 @@ set(IGNORE_PATTERN
.*cblas\\.h.*
.*\\.pb\\.txt
.*LtrDataProvider.*
.*MultiDataProvider.*)
.*MultiDataProvider.*
.*pb.*)
# add_style_check_target
#
@ -52,14 +53,13 @@ macro(add_style_check_target TARGET_NAME)
endif()
endforeach()
if(LINT MATCHES ON)
# cpplint code style
get_filename_component(base_filename ${filename} NAME)
set(CUR_GEN ${CMAKE_CURRENT_BINARY_DIR}/${base_filename}.cpplint)
add_custom_command(OUTPUT ${CUR_GEN}
PRE_BUILD
COMMAND env ${py_env} "${PYTHON_EXECUTABLE}" "${PROJ_ROOT}/paddle/scripts/cpplint.py"
add_custom_command(TARGET ${TARGET_NAME} PRE_BUILD
COMMAND "${PYTHON_EXECUTABLE}" "${PROJ_ROOT}/paddle/scripts/cpplint.py"
"--filter=${STYLE_FILTER}"
"--write-success=${CUR_GEN}" ${filename}
DEPENDS ${filename}
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
endif()
endforeach()

@ -185,6 +185,10 @@ function(cc_library TARGET_NAME)
add_dependencies(${TARGET_NAME} ${cc_library_DEPS})
target_link_libraries(${TARGET_NAME} ${cc_library_DEPS})
endif()
# cpplint code style
add_style_check_target(${TARGET_NAME} ${cc_library_SRCS})
else(cc_library_SRCS)
if (cc_library_DEPS)
merge_static_libs(${TARGET_NAME} ${cc_library_DEPS})

@ -1,3 +1,17 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/framework/ddim.h"
namespace paddle {
@ -68,7 +82,7 @@ DDim make_ddim(const std::vector<int>& dims) {
// XXX For some reason, putting this in an anonymous namespace causes errors
class DynamicMutableIndexer : public boost::static_visitor<int&> {
public:
DynamicMutableIndexer(int idx) : idx_(idx) {}
explicit DynamicMutableIndexer(int idx) : idx_(idx) {}
template <int D>
int& operator()(Dim<D>& dim) const {
@ -81,7 +95,7 @@ class DynamicMutableIndexer : public boost::static_visitor<int&> {
class DynamicConstIndexer : public boost::static_visitor<int> {
public:
DynamicConstIndexer(int idx) : idx_(idx) {}
explicit DynamicConstIndexer(int idx) : idx_(idx) {}
template <int D>
int operator()(const Dim<D>& dim) const {
@ -159,7 +173,7 @@ void set(DDim& ddim, int idx, int value) { ddim[idx] = value; }
struct VectorizeVisitor : public boost::static_visitor<> {
std::vector<int>& vector;
VectorizeVisitor(std::vector<int>& v) : vector(v) {}
explicit VectorizeVisitor(std::vector<int>& v) : vector(v) {}
template <typename T>
void operator()(const T& t) {
@ -204,7 +218,7 @@ int arity(const DDim& d) { return boost::apply_visitor(ArityVisitor(), d); }
struct DDimPrinter : boost::static_visitor<void> {
std::ostream& os;
DDimPrinter(std::ostream& os_) : os(os_) {}
explicit DDimPrinter(std::ostream& os_) : os(os_) {}
template <typename T>
void operator()(const T& t) {

@ -27,7 +27,7 @@ struct DDim {
DDim() : var(Dim<1>()) {}
template <int D>
DDim(const Dim<D>& in) : var(in) {}
explicit DDim(const Dim<D>& in) : var(in) {}
template <int D>
DDim& operator=(const Dim<D>& in) {

@ -1,3 +1,19 @@
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
#include "paddle/framework/net.h"
namespace paddle {

@ -1,3 +1,17 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <paddle/framework/op_registry.h>
namespace paddle {

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

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

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

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

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

@ -152,6 +152,6 @@ MemoryBlock* MemoryBlock::metadata() const {
reinterpret_cast<const Metadata*>(this) - 1));
}
} // detail
} // memory
} // paddle
} // namespace detail
} // namespace memory
} // namespace paddle

@ -17,8 +17,6 @@ limitations under the License. */
#include "paddle/memory/detail/system_allocator.h"
#include "paddle/platform/assert.h"
#include <boost/variant.hpp>
namespace paddle {
namespace memory {

@ -1,3 +1,17 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <paddle/framework/op_registry.h>
#include <paddle/framework/tensor.h>
#include <paddle/operators/add_op.h>
@ -36,7 +50,7 @@ The equation is: Out = X + Y
)DOC");
}
};
} // namespace op
} // namespace operators
} // namespace paddle
REGISTER_OP(add_two, paddle::operators::AddOp, paddle::operators::AddOpMaker);

@ -1,3 +1,19 @@
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
#include "parameter_optimizer.h"
#include <cmath>
#include <map>
@ -5,21 +21,18 @@
#include "gtest/gtest.h"
#include "lr_policy.h"
using namespace paddle;
using namespace paddle::optimizer;
Tensor* FillTensor(size_t size) {
Tensor* param = new Tensor(size);
Tensor& p = *param;
paddle::optimizer::Tensor* FillTensor(size_t size) {
paddle::optimizer::Tensor* param = new paddle::optimizer::Tensor(size);
paddle::optimizer::Tensor& p = *param;
for (size_t i = 0; i < p.size(); ++i) {
p[i] = (float)rand() / (float)RAND_MAX;
}
return param;
}
Tensor* FixedTensor(size_t size) {
Tensor* param = new Tensor(size);
Tensor& p = *param;
paddle::optimizer::Tensor* FixedTensor(size_t size) {
paddle::optimizer::Tensor* param = new paddle::optimizer::Tensor(size);
paddle::optimizer::Tensor& p = *param;
for (size_t i = 0; i < p.size(); ++i) {
p[i] = i;
}
@ -28,7 +41,8 @@ Tensor* FixedTensor(size_t size) {
class OptimizerTest : public testing::Test {
public:
// init tensor shape
virtual ~OptimizerTest() {}
// init paddle::optimizer::Tensor shape
const size_t kSize = 5;
virtual void SetUp() {
@ -38,34 +52,36 @@ public:
virtual void TearDown() {}
void CreateSGD() {
Tensor* parameter = FixedTensor(kSize);
config_.set_optimizer(OptimizerConfig::SGD);
paddle::optimizer::Tensor* parameter = FixedTensor(kSize);
config_.set_optimizer(paddle::OptimizerConfig::SGD);
config_.mutable_sgd()->set_momentum(0.0);
config_.mutable_sgd()->set_decay(0.0);
config_.mutable_sgd()->set_nesterov(false);
config_.set_lr_policy(OptimizerConfig::Const);
config_.set_lr_policy(paddle::OptimizerConfig::Const);
config_.mutable_const_lr()->set_learning_rate(0.1);
std::string str = config_.SerializeAsString();
ParameterOptimizer* opt = ParameterOptimizer::Create(str, parameter);
paddle::optimizer::ParameterOptimizer* opt =
paddle::optimizer::ParameterOptimizer::Create(str, parameter);
opts_.push_back(opt);
}
void CreateAdam() {
Tensor* parameter = FixedTensor(kSize);
config_.set_optimizer(OptimizerConfig::Adam);
paddle::optimizer::Tensor* parameter = FixedTensor(kSize);
config_.set_optimizer(paddle::OptimizerConfig::Adam);
config_.mutable_adam()->set_beta_1(0.9);
config_.mutable_adam()->set_beta_2(0.1);
config_.mutable_adam()->set_epsilon(1e-3);
config_.mutable_adam()->set_decay(0.0);
config_.set_lr_policy(OptimizerConfig::Const);
config_.set_lr_policy(paddle::OptimizerConfig::Const);
config_.mutable_const_lr()->set_learning_rate(0.1);
std::string str = config_.SerializeAsString();
ParameterOptimizer* opt = ParameterOptimizer::Create(str, parameter);
paddle::optimizer::ParameterOptimizer* opt =
paddle::optimizer::ParameterOptimizer::Create(str, parameter);
opts_.push_back(opt);
}
void TestGetWeight() {
Tensor* p = FixedTensor(kSize);
paddle::optimizer::Tensor* p = FixedTensor(kSize);
for (size_t i = 0; i < opts_.size(); ++i) {
int s = 0;
float* newp = (float*)opts_[i]->get_weight(&s);
@ -76,7 +92,7 @@ public:
}
void TestUpdate() {
Tensor* g = FixedTensor(kSize);
paddle::optimizer::Tensor* g = FixedTensor(kSize);
for (size_t i = 0; i < opts_.size(); ++i) {
opts_[i]->Update(g);
}
@ -91,8 +107,8 @@ public:
}
private:
std::vector<ParameterOptimizer*> opts_;
OptimizerConfig config_;
std::vector<paddle::optimizer::ParameterOptimizer*> opts_;
paddle::OptimizerConfig config_;
};
TEST_F(OptimizerTest, TestGetWeight) { TestGetWeight(); }

@ -1,19 +1,32 @@
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
#include "serialization.h"
#include "gtest/gtest.h"
using namespace paddle;
using namespace paddle::optimizer;
TEST(TensorToProto, Case1) {
Tensor t(3), t1(3);
paddle::optimizer::Tensor t(3), t1(3);
for (size_t i = 0; i < t.size(); ++i) {
t[i] = i;
t1[i] = 0;
}
TensorProto proto;
TensorToProto(t, &proto);
ProtoToTensor(proto, &t1);
paddle::TensorProto proto;
paddle::optimizer::TensorToProto(t, &proto);
paddle::optimizer::ProtoToTensor(proto, &t1);
for (size_t i = 0; i < t1.size(); ++i) {
EXPECT_EQ(t1[i], t[i]);
}

@ -41,8 +41,8 @@ inline size_t CpuTotalPhysicalMemory() {
if (sysctl(mib, 2, &size, &len, NULL, 0) == 0) return (size_t)size;
return 0L;
#else
long pages = sysconf(_SC_PHYS_PAGES);
long page_size = sysconf(_SC_PAGE_SIZE);
int64_t pages = sysconf(_SC_PHYS_PAGES);
int64_t page_size = sysconf(_SC_PAGE_SIZE);
return pages * page_size;
#endif
}

@ -1,3 +1,17 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/platform/place.h"
namespace paddle {
@ -7,7 +21,7 @@ namespace detail {
class PlacePrinter : public boost::static_visitor<> {
public:
PlacePrinter(std::ostream &os) : os_(os) {}
explicit PlacePrinter(std::ostream &os) : os_(os) {}
void operator()(const CPUPlace &) { os_ << "CPUPlace"; }
void operator()(const GPUPlace &p) { os_ << "GPUPlace(" << p.device << ")"; }

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

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

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