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PaddleDetection
提交 b2222692 编写于 作者: C Chunwei
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refactor api and recover CI cache

上级 6c68024d
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Showing with 305 addition and 255 deletion
.gitlab-ci.yml
浏览文件 @ b2222692
......@@ -78,6 +78,7 @@ build:mobile_android:
paths:
- $MOBILE_LITE_CACHE0
- $MOBILE_LITE_CACHE1
- $MOBILE_LITE_CACHE2
- ~/.ccache
- $CI_PROJECT_DIR/build_mobile_ccache
script:
......@@ -98,6 +99,7 @@ build:mobile_armlinux:
paths:
- $MOBILE_LITE_CACHE0
- $MOBILE_LITE_CACHE1
- $MOBILE_LITE_CACHE2
- ~/.ccache
- $CI_PROJECT_DIR/build_mobile_ccache2
script:
......@@ -107,24 +109,13 @@ build:mobile_armlinux:
dependencies:
- build:server
cache:
key: mobile_thirdparty
paths:
- $MOBILE_LITE_CACHE0
- $MOBILE_LITE_CACHE1
- ~/.ccache
build:mobile_model_mobilenetv1:
tags:
- lite
stage: build_mobile
image: $MOBILE_LITE_DOCKER_IMAGE
cache:
key: mobile_thirdparty
paths:
- $MOBILE_LITE_CACHE0
- $MOBILE_LITE_CACHE1
- ~/.ccache
script:
- export CCACHE_DIR=$CI_PROJECT_DIR/build_mobile_model_mobilenetv1
- ./paddle/fluid/lite/tools/build.sh build_test_arm_model_mobilenetv1
......@@ -137,6 +128,7 @@ build:mobile_model_mobilenetv1:
paths:
- $MOBILE_LITE_CACHE0
- $MOBILE_LITE_CACHE1
- $MOBILE_LITE_CACHE2
- ~/.ccache
- $CI_PROJECT_DIR/build_mobile_model_mobilenetv1
......@@ -145,12 +137,7 @@ build:mobile_model_mobilenetv2:
- lite
stage: build_mobile
image: $MOBILE_LITE_DOCKER_IMAGE
cache:
key: mobile_thirdparty
paths:
- $MOBILE_LITE_CACHE0
- $MOBILE_LITE_CACHE1
- ~/.ccache
script:
- export CCACHE_DIR=$CI_PROJECT_DIR/build_mobile_model_mobilenetv2
- ./paddle/fluid/lite/tools/build.sh build_test_arm_model_mobilenetv2
......@@ -163,6 +150,7 @@ build:mobile_model_mobilenetv2:
paths:
- $MOBILE_LITE_CACHE0
- $MOBILE_LITE_CACHE1
- $MOBILE_LITE_CACHE2
- ~/.ccache
- $CI_PROJECT_DIR/build_mobile_model_mobilenetv2
......@@ -171,12 +159,7 @@ build:mobile_model_resnet50:
- lite
stage: build_mobile
image: $MOBILE_LITE_DOCKER_IMAGE
cache:
key: mobile_thirdparty
paths:
- $MOBILE_LITE_CACHE0
- $MOBILE_LITE_CACHE1
- ~/.ccache
script:
- export CCACHE_DIR=$CI_PROJECT_DIR/build_mobile_model_resnet50
- ./paddle/fluid/lite/tools/build.sh build_test_arm_model_resnet50
......@@ -189,6 +172,7 @@ build:mobile_model_resnet50:
paths:
- $MOBILE_LITE_CACHE0
- $MOBILE_LITE_CACHE1
- $MOBILE_LITE_CACHE2
- ~/.ccache
- $CI_PROJECT_DIR/build_mobile_model_resnet50
......
paddle/fluid/lite/CMakeLists.txt
浏览文件 @ b2222692
......@@ -24,8 +24,7 @@ function(lite_download_and_uncompress INSTALL_DIR URL FILENAME)
${EXTERNAL_PROJECT_NAME}
${EXTERNAL_PROJECT_LOG_ARGS}
PREFIX ${INSTALL_DIR}
DOWNLOAD_COMMAND wget --no-check-certificate -q -O ${INSTALL_DIR}/${FILENAME} ${URL}/${FILENAME} &&
${CMAKE_COMMAND} -E tar xzf ${INSTALL_DIR}/${FILENAME}
DOWNLOAD_COMMAND wget --no-check-certificate -q -O ${INSTALL_DIR}/${FILENAME} ${URL}/${FILENAME} && ${CMAKE_COMMAND} -E tar xzf ${INSTALL_DIR}/${FILENAME}
DOWNLOAD_DIR ${INSTALL_DIR}
DOWNLOAD_NO_PROGRESS 1
CONFIGURE_COMMAND ""
......@@ -143,6 +142,8 @@ function(lite_cc_binary TARGET)
HVY_DEPS ${args_HVY_DEPS}
)
cc_binary(${TARGET} SRCS ${args_SRCS} DEPS ${deps} ${args_DEPS})
# collect targets need to compile for lite
add_dependencies(lite_compile_deps ${TARGET})
endfunction()
# Add a unit-test name to file for latter offline manual test.
......
paddle/fluid/lite/api/CMakeLists.txt
浏览文件 @ b2222692
......@@ -12,7 +12,6 @@ lite_cc_library(lite_api_test_helper SRCS lite_api_test_helper.cc
CUDA_DEPS kernels_cuda
X86_DEPS ${x86_kernels}
)
lite_cc_library(cxx_api_lite SRCS cxx_api.cc DEPS lite_api_test_helper)
set(light_api_deps
scope_lite target_wrapper_host model_parser_lite program_lite)
......@@ -21,27 +20,34 @@ if(LITE_WITH_CUDA)
set(light_api_deps ${light_api_deps} target_wrapper_cuda)
endif()
lite_cc_library(light_api_lite SRCS light_api.cc
DEPS ${light_api_deps} ${ops_lite} ${host_kernels}
)
message(STATUS "get ops ${ops_lite}")
message(STATUS "get Host kernels ${host_kernels}")
message(STATUS "get ARM kernels ${arm_kernels}")
lite_cc_library(cxx_api_lite SRCS cxx_api.cc DEPS ${cxx_api_lite_deps} ${ops_lite} ${host_kernels} program_lite)
lite_cc_library(light_api_lite SRCS light_api.cc
DEPS scope_lite target_wrapper_host model_parser_lite
${light_api_deps} ${ops_lite} ${host_kernels} program_lite
CUDA_DEPS target_wrapper_cuda
X86_DEPS ${x86_kernels} operator
ARM_DEPS ${arm_kernels}
)
include(ExternalProject)
set(LITE_DEMO_INSTALL_DIR "${THIRD_PARTY_PATH}/inference_demo" CACHE STRING
"A path setting inference demo download directories.")
if(NOT LITE_WITH_LIGHT_WEIGHT_FRAMEWORK AND WITH_TESTING)
lite_cc_test(test_cxx_api_lite SRCS cxx_api_test.cc
DEPS cxx_api_lite mir_passes
DEPS cxx_api_lite mir_passes lite_api_test_helper
${ops_lite} ${host_kernels} ${x86_kernels}
ARGS --model_dir=${LITE_MODEL_DIR}/lite_naive_model
--optimized_model=${LITE_MODEL_DIR}/lite_naive_model_opt SERIAL)
add_dependencies(test_cxx_api_lite extern_lite_download_lite_naive_model_tar_gz)
endif()
if(LITE_WITH_LIGHT_WEIGHT_FRAMEWORK AND WITH_TESTING)
set(lite_model_test_DEPS cxx_api_lite mir_passes ${ops_lite} ${host_kernels} ${arm_kernels})
......@@ -68,25 +74,20 @@ endif()
# These tests needs CLI arguments, and is not supported in ARM CI.
# TODO(Superjomn) support latter.
if(NOT LITE_ON_MOBILE)
lite_cc_test(test_light_api SRCS light_api_test.cc
DEPS light_api_lite mir_passes
X86_DEPS ${x86_kernels}
ARGS --optimized_model=${LITE_MODEL_DIR}/lite_naive_model_opt
SERIAL)
lite_cc_test(test_light_api SRCS light_api_test.cc
DEPS light_api_lite program_lite mir_passes
ARGS --optimized_model=${LITE_MODEL_DIR}/lite_naive_model_opt
SERIAL)
if(NOT LITE_ON_MOBILE)
lite_cc_test(test_apis_lite SRCS apis_test.cc
DEPS cxx_api_lite light_api_lite ${ops_lite} mir_passes
X86_DEPS ${x86_kernels}
DEPS cxx_api_lite light_api_lite ${ops_lite}
X86_DEPS ${x86_kernels} operator
ARGS --model_dir=${LITE_MODEL_DIR}/lite_naive_model
--optimized_model=${LITE_MODEL_DIR}/lite_naive_model_opt SERIAL)
endif()
lite_cc_binary(cxx_api_lite_bin SRCS cxx_api_bin.cc
DEPS
cxx_api_lite
model_parser_lite
target_wrapper_host
mir_passes
${ops_lite} ${host_kernels}
ARM_DEPS ${arm_kernels})
#lite_cc_binary(cxx_api_lite_bin SRCS cxx_api_bin.cc
#X86_DEPS operator
#DEPS light_api_lite model_parser_lite target_wrapper_host mir_passes
#ARM_DEPS ${arm_kernels})
paddle/fluid/lite/api/apis_test.cc
浏览文件 @ b2222692
......@@ -39,7 +39,7 @@ void SetConstInput(lite::Tensor* x) {
}
}
bool CompareTensors(const std::string& name, const ExecutorLite& cxx_api,
bool CompareTensors(const std::string& name, const Predictor& cxx_api,
const LightPredictor& light_api) {
const auto* a = cxx_api.GetTensor(name);
const auto* b = light_api.GetTensor(name);
......@@ -48,8 +48,8 @@ bool CompareTensors(const std::string& name, const ExecutorLite& cxx_api,
#ifndef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
TEST(CXXApi_LightApi, save_and_load_model) {
lite::ExecutorLite cxx_api;
lite::LightPredictor light_api;
lite::Predictor cxx_api;
lite::LightPredictor light_api(FLAGS_optimized_model);
// CXXAPi
{
......@@ -69,8 +69,6 @@ TEST(CXXApi_LightApi, save_and_load_model) {
// LightApi
{
light_api.Build(FLAGS_optimized_model);
auto* x = light_api.GetInput(0);
SetConstInput(x);
......
paddle/fluid/lite/api/cxx_api.cc
浏览文件 @ b2222692
......@@ -17,19 +17,49 @@
#include <string>
#include <utility>
#include <vector>
#ifndef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
#include "paddle/fluid/platform/port.h"
#endif
#include "paddle/fluid/lite/utils/io.h"
namespace paddle {
namespace lite {
#ifndef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
void ExecutorLite::SaveModel(const std::string &dir) {
MkDirRecursively(dir.c_str());
void Predictor::SaveModel(const std::string &dir) {
#ifndef LITE_WITH_ARM
LOG(INFO) << "Save model to " << dir;
MkDirRecur(dir);
program_->PersistModel(dir, program_desc_);
}
#else
LOG(INFO) << "Save model to ./";
program_->PersistModel("./", program_desc_);
#endif
}
lite::Tensor *Predictor::GetInput(size_t offset) {
auto *_feed_list = program_->exec_scope()->FindVar("feed");
CHECK(_feed_list) << "no feed variable in exec_scope";
auto *feed_list = _feed_list->GetMutable<std::vector<lite::Tensor>>();
if (offset >= feed_list->size()) {
feed_list->resize(offset + 1);
}
return &feed_list->at(offset);
}
const lite::Tensor *Predictor::GetOutput(size_t offset) {
auto *_fetch_list = program_->exec_scope()->FindVar("fetch");
CHECK(_fetch_list) << "no fatch variable in exec_scope";
auto &fetch_list = *_fetch_list->GetMutable<std::vector<lite::Tensor>>();
CHECK_LT(offset, fetch_list.size()) << "offset " << offset << " overflow";
return &fetch_list.at(offset);
}
void Predictor::Build(const std::string &model_path, const Place &prefer_place,
const std::vector<Place> &valid_places) {
LoadModel(model_path, scope_.get(), &program_desc_);
Build(program_desc_, prefer_place, valid_places);
}
const framework::proto::ProgramDesc &Predictor::program_desc() const {
return program_desc_;
}
} // namespace lite
} // namespace paddle
paddle/fluid/lite/api/cxx_api.h
浏览文件 @ b2222692
......@@ -26,20 +26,20 @@
namespace paddle {
namespace lite {
struct Config {};
class ExecutorLite {
/*
* Predictor for inference, input a model, it will optimize and execute it.
*/
class Predictor {
public:
ExecutorLite() { scope_ = std::make_shared<Scope>(); }
explicit ExecutorLite(const std::shared_ptr<lite::Scope>& root_scope) {
scope_ = root_scope;
}
// Create an empty predictor.
Predictor() { scope_ = std::make_shared<Scope>(); }
// Create a predictor with the weight variable scope set.
explicit Predictor(const std::shared_ptr<lite::Scope>& root_scope)
: scope_(root_scope) {}
// Build from a model, with places set for hardware config.
void Build(const std::string& model_path, const Place& prefer_place,
const std::vector<Place>& valid_places) {
LoadModel(model_path, scope_.get(), &program_desc_);
Build(program_desc_, prefer_place, valid_places);
}
const std::vector<Place>& valid_places);
void Build(const framework::proto::ProgramDesc& desc,
const Place& prefer_place,
......@@ -55,40 +55,24 @@ class ExecutorLite {
program_ = optimizer_.GenRuntimeProgram();
}
// This method is disabled in mobile, or unnecessary dependencies required.
#ifndef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
void SaveModel(const std::string& dir);
#endif
// Run the predictor for a single batch of data.
void Run() { program_->Run(); }
// Get offset-th col of feed.
lite::Tensor* GetInput(size_t offset) {
auto* _feed_list = program_->exec_scope()->FindVar("feed");
CHECK(_feed_list) << "no feed variable in exec_scope";
auto* feed_list = _feed_list->GetMutable<std::vector<lite::Tensor>>();
if (offset >= feed_list->size()) {
feed_list->resize(offset + 1);
}
return &feed_list->at(offset);
}
// Get offset-th col of feed inputs.
lite::Tensor* GetInput(size_t offset);
const lite::Tensor* GetOutput(size_t offset) {
auto* _fetch_list = program_->exec_scope()->FindVar("fetch");
CHECK(_fetch_list) << "no fatch variable in exec_scope";
auto& fetch_list = *_fetch_list->GetMutable<std::vector<lite::Tensor>>();
CHECK_LT(offset, fetch_list.size()) << "offset " << offset << " overflow";
return &fetch_list.at(offset);
}
// Get offset-th col of fetch results.
const lite::Tensor* GetOutput(size_t offset);
// Return the program desc for debug.
const framework::proto::ProgramDesc& program_desc() const;
const lite::Tensor* GetTensor(const std::string& name) const {
auto* var = program_->exec_scope()->FindVar(name);
return &var->Get<lite::Tensor>();
}
void Run() { program_->Run(); }
const framework::proto::ProgramDesc& program_desc() const {
return program_desc_;
}
// This method is disabled in mobile, for unnecessary dependencies required.
void SaveModel(const std::string& dir);
private:
Optimizer optimizer_;
......@@ -97,6 +81,7 @@ class ExecutorLite {
std::unique_ptr<RuntimeProgram> program_;
};
#ifdef LITE_WITH_X86
/*
* An executor for training.
*
......@@ -120,13 +105,13 @@ class CXXTrainer {
: scope_(root_scope),
preferred_place_(preferred_place),
valid_places_(valid_places),
main_program_executor_(ExecutorLite(scope_)) {}
main_program_executor_(Predictor(scope_)) {}
// Build the RuntimeProgram cache for the main program. The cache will run
// multiple times for the epoches.
// NOTE Just support to execute the 0-th block currently.
ExecutorLite& BuildMainProgramExecutor(
const framework::proto::ProgramDesc& desc, int block_id = 0) {
Predictor& BuildMainProgramExecutor(const framework::proto::ProgramDesc& desc,
int block_id = 0) {
main_program_executor_.Build(desc, preferred_place_, valid_places_);
return main_program_executor_;
}
......@@ -134,7 +119,7 @@ class CXXTrainer {
// Run the startup program. It just executes once, no cache needed.
void RunStartupProgram(const framework::proto::ProgramDesc& desc,
int block_id = 0) {
ExecutorLite exe(scope_);
Predictor exe(scope_);
exe.Build(desc, preferred_place_, valid_places_);
exe.Run();
}
......@@ -146,8 +131,9 @@ class CXXTrainer {
std::vector<Place> valid_places_;
// The training program.
ExecutorLite main_program_executor_;
Predictor main_program_executor_;
};
#endif
} // namespace lite
} // namespace paddle
paddle/fluid/lite/api/cxx_api_bin.cc
浏览文件 @ b2222692
......@@ -34,7 +34,7 @@ void Run(const char* model_dir, int repeat, int thread_num) {
DeviceInfo::Init();
DeviceInfo::Global().SetRunMode(LITE_POWER_HIGH, thread_num);
#endif
lite::ExecutorLite predictor;
lite::Predictor predictor;
std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
Place{TARGET(kARM), PRECISION(kFloat)}});
......
paddle/fluid/lite/api/cxx_api_test.cc
浏览文件 @ b2222692
......@@ -42,7 +42,7 @@ TEST(CXXApi, test) {
}
TEST(CXXApi, save_model) {
lite::ExecutorLite predictor;
lite::Predictor predictor;
std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
Place{TARGET(kX86), PRECISION(kFloat)}});
predictor.Build(FLAGS_model_dir, Place{TARGET(kCUDA), PRECISION(kFloat)},
......
paddle/fluid/lite/api/inceptionv4_test.cc
浏览文件 @ b2222692
......@@ -30,7 +30,7 @@ namespace lite {
#ifdef LITE_WITH_ARM
TEST(InceptionV4, test) {
DeviceInfo::Init();
lite::ExecutorLite predictor;
lite::Predictor predictor;
std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
Place{TARGET(kARM), PRECISION(kFloat)}});
......
paddle/fluid/lite/api/light_api.cc
浏览文件 @ b2222692
......@@ -13,3 +13,67 @@
// limitations under the License.
#include "paddle/fluid/lite/api/light_api.h"
namespace paddle {
namespace lite {
void LightPredictor::Build(const std::string& model_dir) {
framework::proto::ProgramDesc desc;
LoadModel(model_dir, scope_.get(), &desc);
BuildRuntimeProgram(desc);
}
Tensor* LightPredictor::GetInput(size_t offset) {
auto* _feed_list = program_->exec_scope()->FindVar("feed");
CHECK(_feed_list) << "no feed variable in exec_scope";
auto* feed_list = _feed_list->GetMutable<std::vector<Tensor>>();
if (offset >= feed_list->size()) {
feed_list->resize(offset + 1);
}
return &feed_list->at(offset);
}
const Tensor* LightPredictor::GetOutput(size_t offset) {
auto* _fetch_list = program_->exec_scope()->FindVar("fetch");
CHECK(_fetch_list) << "no fatch variable in exec_scope";
auto& fetch_list = *_fetch_list->GetMutable<std::vector<lite::Tensor>>();
CHECK_LT(offset, fetch_list.size()) << "offset " << offset << " overflow";
return &fetch_list.at(offset);
}
void LightPredictor::BuildRuntimeProgram(
const framework::proto::ProgramDesc& prog) {
std::vector<Instruction> insts;
// 1. Create op first
Program program(prog, scope_, {});
// 2. Create Instructs
// Create the kernels of the target places, and filter out the specific
// kernel with the target alias.
for (auto& op : program.ops()) {
auto kernel_type = op->op_info()->GetAttr<std::string>(kKernelTypeAttr);
std::string op_type, alias;
Place place;
KernelBase::ParseKernelType(kernel_type, &op_type, &alias, &place);
auto kernels = op->CreateKernels({place});
// filter out a kernel
auto it = std::find_if(
kernels.begin(), kernels.end(),
[&](std::unique_ptr<KernelBase>& it) { return it->alias() == alias; });
CHECK(it != kernels.end());
(*it)->SetContext(ContextScheduler::Global().NewContext((*it)->target()));
insts.emplace_back(op, std::move(*it));
}
program_.reset(new RuntimeProgram(std::move(insts)));
CHECK(program.exec_scope());
program_->set_exec_scope(program.exec_scope());
}
LightPredictor::LightPredictor(const std::string& model_dir) {
scope_ = std::make_shared<Scope>();
Build(model_dir);
}
} // namespace lite
} // namespace paddle
paddle/fluid/lite/api/light_api.h
浏览文件 @ b2222692
......@@ -32,36 +32,21 @@
namespace paddle {
namespace lite {
/*
* The light weight predictor, mainly for mobile. It loads an optimized model,
* and will not depend on the MIR or perform latter optimization.
*/
class LightPredictor {
public:
LightPredictor() { scope_ = std::make_shared<Scope>(); }
void Build(const std::string& model_dir) {
framework::proto::ProgramDesc desc;
LoadModel(model_dir, scope_.get(), &desc);
BuildRuntimeProgram(desc);
}
explicit LightPredictor(const std::string& model_dir);
void Run() { program_->Run(); }
// Get offset-th col of feed.
Tensor* GetInput(size_t offset) {
auto* _feed_list = program_->exec_scope()->FindVar("feed");
CHECK(_feed_list) << "no feed variable in exec_scope";
auto* feed_list = _feed_list->GetMutable<std::vector<Tensor>>();
if (offset >= feed_list->size()) {
feed_list->resize(offset + 1);
}
return &feed_list->at(offset);
}
// Get offset-th col of feed inputs.
Tensor* GetInput(size_t offset);
const Tensor* GetOutput(size_t offset) {
auto* _fetch_list = program_->exec_scope()->FindVar("fetch");
CHECK(_fetch_list) << "no fatch variable in exec_scope";
auto& fetch_list = *_fetch_list->GetMutable<std::vector<lite::Tensor>>();
CHECK_LT(offset, fetch_list.size()) << "offset " << offset << " overflow";
return &fetch_list.at(offset);
}
// Get offset-th col of fetch outputs.
const Tensor* GetOutput(size_t offset);
const lite::Tensor* GetTensor(const std::string& name) const {
auto* var = program_->exec_scope()->FindVar(name);
......@@ -69,34 +54,8 @@ class LightPredictor {
}
private:
void BuildRuntimeProgram(const framework::proto::ProgramDesc& prog) {
std::vector<Instruction> insts;
// 1. Create op first
Program program(prog, scope_, {});
// 2. Create Instructs
// Create the kernels of the target places, and filter out the specific
// kernel with the target alias.
for (auto& op : program.ops()) {
auto kernel_type = op->op_info()->GetAttr<std::string>(kKernelTypeAttr);
std::string op_type, alias;
Place place;
KernelBase::ParseKernelType(kernel_type, &op_type, &alias, &place);
auto kernels = op->CreateKernels({place});
// filter out a kernel
auto it = std::find_if(kernels.begin(), kernels.end(),
[&](std::unique_ptr<KernelBase>& it) {
return it->alias() == alias;
});
CHECK(it != kernels.end());
(*it)->SetContext(ContextScheduler::Global().NewContext((*it)->target()));
insts.emplace_back(op, std::move(*it));
}
program_.reset(new RuntimeProgram(std::move(insts)));
CHECK(program.exec_scope());
program_->set_exec_scope(program.exec_scope());
}
void Build(const std::string& model_dir);
void BuildRuntimeProgram(const framework::proto::ProgramDesc& prog);
private:
std::shared_ptr<Scope> scope_;
......
paddle/fluid/lite/api/light_api_test.cc
浏览文件 @ b2222692
......@@ -25,8 +25,10 @@ namespace paddle {
namespace lite {
TEST(LightAPI, load) {
LightPredictor predictor;
predictor.Build(FLAGS_optimized_model);
if (FLAGS_optimized_model.empty()) {
FLAGS_optimized_model = "lite_naive_model";
}
LightPredictor predictor(FLAGS_optimized_model);
auto* input_tensor = predictor.GetInput(0);
input_tensor->Resize(DDim(std::vector<int64_t>({100, 100})));
......
paddle/fluid/lite/api/lite_api_test_helper.cc
浏览文件 @ b2222692
......@@ -22,7 +22,7 @@ namespace paddle {
namespace lite {
const lite::Tensor* RunHvyModel() {
lite::ExecutorLite predictor;
lite::Predictor predictor;
#ifndef LITE_WITH_CUDA
std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
Place{TARGET(kX86), PRECISION(kFloat)}});
......
paddle/fluid/lite/api/mobilenetv1_test.cc
浏览文件 @ b2222692
......@@ -30,7 +30,7 @@ namespace lite {
#ifdef LITE_WITH_ARM
TEST(MobileNetV1, test) {
DeviceInfo::Init();
lite::ExecutorLite predictor;
lite::Predictor predictor;
std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
Place{TARGET(kARM), PRECISION(kFloat)}});
......
paddle/fluid/lite/api/mobilenetv2_test.cc
浏览文件 @ b2222692
......@@ -30,7 +30,7 @@ namespace lite {
#ifdef LITE_WITH_ARM
TEST(MobileNetV2, test) {
DeviceInfo::Init();
lite::ExecutorLite predictor;
lite::Predictor predictor;
std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
Place{TARGET(kARM), PRECISION(kFloat)}});
......
paddle/fluid/lite/api/resnet50_test.cc
浏览文件 @ b2222692
......@@ -30,7 +30,7 @@ namespace lite {
#ifdef LITE_WITH_ARM
TEST(ResNet50, test) {
DeviceInfo::Init();
lite::ExecutorLite predictor;
lite::Predictor predictor;
std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
Place{TARGET(kARM), PRECISION(kFloat)}});
......
paddle/fluid/lite/core/CMakeLists.txt
浏览文件 @ b2222692
......@@ -25,7 +25,7 @@ cc_library(op_registry_lite SRCS op_registry.cc DEPS framework_proto_lite)
cc_library(scope_lite SRCS scope.cc DEPS ${tensor_lite})
cc_library(cpu_info_lite SRCS cpu_info.cc)
lite_cc_library(context_lite SRCS context.cc DEPS ${tensor_lite} any_lite cpu_info_lite eigen3)
cc_library(op_lite SRCS op_lite.cc DEPS scope_lite op_registry_lite target_wrapper_lite
cc_library(op_lite SRCS op_lite.cc DEPS scope_lite op_registry_lite target_wrapper_lite kernel_lite
cpp_op_desc_lite ${tensor_lite})
cc_library(types_lite SRCS types.cc)
cc_library(type_system SRCS type_system.cc DEPS ${tensor_lite} target_wrapper_lite)
......
paddle/fluid/lite/core/kernel.cc
浏览文件 @ b2222692
......@@ -13,6 +13,7 @@
// limitations under the License.
#include "paddle/fluid/lite/core/kernel.h"
#include <cstdlib>
namespace paddle {
namespace lite {
......@@ -49,6 +50,36 @@ std::string KernelBase::GenParamTypeKey() const {
return ss.str();
}
void KernelBase::ParseKernelType(const std::string &kernel_type,
std::string *op_type, std::string *alias,
Place *place) {
std::stringstream ss(kernel_type);
std::getline(ss, *op_type, '/');
std::getline(ss, *alias, '/');
std::string target, precision, layout;
std::getline(ss, target, '/');
std::getline(ss, precision, '/');
std::getline(ss, layout, '/');
place->target = static_cast<TargetType>(std::atoi(target.c_str()));
place->precision = static_cast<PrecisionType>(std::atoi(precision.c_str()));
place->layout = static_cast<DataLayoutType>(std::atoi(layout.c_str()));
}
std::string KernelBase::SerializeKernelType(const std::string &op_type,
const std::string &alias,
const Place &place) {
std::stringstream ss;
ss << op_type << "/";
ss << alias << "/";
// We serialize the place value not the string representation here for
// easier deserialization.
ss << static_cast<int>(place.target) << "/";
ss << static_cast<int>(place.precision) << "/";
ss << static_cast<int>(place.layout);
return ss.str();
}
bool ParamTypeRegistry::KeyCmp::operator()(
const ParamTypeRegistry::key_t &a,
const ParamTypeRegistry::key_t &b) const {
......
paddle/fluid/lite/core/kernel.h
浏览文件 @ b2222692
......@@ -118,33 +118,11 @@ class KernelBase {
static std::string SerializeKernelType(const std::string& op_type,
const std::string& alias,
const Place& place) {
std::stringstream ss;
ss << op_type << "/";
ss << alias << "/";
// We serialize the place value not the string representation here for
// easier deserialization.
ss << static_cast<int>(place.target) << "/";
ss << static_cast<int>(place.precision) << "/";
ss << static_cast<int>(place.layout);
return ss.str();
}
const Place& place);
static void ParseKernelType(const std::string& kernel_type,
std::string* op_type, std::string* alias,
Place* place) {
std::stringstream ss(kernel_type);
std::getline(ss, *op_type, '/');
std::getline(ss, *alias, '/');
std::string target, precision, layout;
std::getline(ss, target, '/');
std::getline(ss, precision, '/');
std::getline(ss, layout, '/');
place->target = static_cast<TargetType>(std::stoi(target));
place->precision = static_cast<PrecisionType>(std::stoi(precision));
place->layout = static_cast<DataLayoutType>(std::stoi(layout));
}
Place* place);
virtual ~KernelBase() = default;
void Torch() {}
......
paddle/fluid/lite/core/mir/fusion/fc_fuse_pass_test.cc
浏览文件 @ b2222692
......@@ -28,7 +28,7 @@ namespace lite {
namespace mir {
TEST(fc_fuse_pass, fuse_test) {
lite::ExecutorLite predictor;
lite::Predictor predictor;
#ifndef LITE_WITH_CUDA
std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
Place{TARGET(kX86), PRECISION(kFloat)}});
......@@ -69,7 +69,7 @@ TEST(fc_fuse_pass, fuse_test) {
#ifndef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
TEST(fc_fuse_pass, save_model_test) {
lite::ExecutorLite predictor;
lite::Predictor predictor;
std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
Place{TARGET(kX86), PRECISION(kFloat)}});
predictor.Build(FLAGS_model_dir, Place{TARGET(kX86), PRECISION(kFloat)},
......
paddle/fluid/lite/kernels/arm/CMakeLists.txt
浏览文件 @ b2222692
......@@ -51,5 +51,3 @@ set(arm_kernels
)
set(arm_kernels "${arm_kernels}" CACHE INTERNAL "arm kernels")
paddle/fluid/lite/kernels/arm/use_kernels.h 已删除 100644 → 0
浏览文件 @ 6c68024d
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// 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.
#pragma once
#include "paddle/fluid/lite/core/op_registry.h"
USE_LITE_KERNEL(fc, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(mul, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(scale, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(softmax, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(concat, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(pool, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(feed, kARM, kAny, kAny, def);
USE_LITE_KERNEL(fetch, kARM, kAny, kAny, def);
paddle/fluid/lite/kernels/use_kernels.h
浏览文件 @ b2222692
......@@ -12,14 +12,33 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
/*
* ATTENTION this header file can only include in .cc file.
*/
#pragma once
#include "paddle/fluid/lite/core/op_registry.h"
USE_LITE_KERNEL(feed, kHost, kAny, kAny, def);
USE_LITE_KERNEL(fetch, kHost, kAny, kAny, def);
#ifdef LITE_WITH_ARM
USE_LITE_KERNEL(fc, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(mul, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(scale, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(softmax, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(conv2d, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(depthwise_conv2d, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(elementwise_add, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(split, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(dropout, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(concat, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(pool2d, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(relu, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(transpose, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(transpose2, kARM, kFloat, kNCHW, def);
#endif
#ifdef LITE_WITH_X86
USE_LITE_KERNEL(relu, kX86, kFloat, kNCHW, def);
USE_LITE_KERNEL(mul, kX86, kFloat, kNCHW, def);
......@@ -36,21 +55,6 @@ USE_LITE_KERNEL(depthwise_conv2d, kX86, kFloat, kNCHW, def);
USE_LITE_KERNEL(pool2d, kX86, kFloat, kNCHW, def);
#endif
#ifdef LITE_WITH_ARM
USE_LITE_KERNEL(fc, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(mul, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(scale, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(conv2d, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(batch_norm, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(relu, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(depthwise_conv2d, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(pool2d, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(elementwise_add, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(softmax, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(concat, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(dropout, kARM, kFloat, kNCHW, def);
#endif
#ifdef LITE_WITH_CUDA
USE_LITE_KERNEL(mul, kCUDA, kFloat, kNCHW, def);
USE_LITE_KERNEL(io_copy, kCUDA, kAny, kAny, host_to_device);
......
paddle/fluid/lite/kernels/x86/CMakeLists.txt
浏览文件 @ b2222692
......@@ -44,10 +44,9 @@ set(x86_kernels
softmax_compute_x86
dropout_compute_x86
concat_compute_x86
conv_compute_x86
pool_compute_x86
batch_norm_compute_x86
conv_compute_x86
pool_compute_x86
batch_norm_compute_x86
)
set(x86_kernels "${x86_kernels}" CACHE INTERNAL "x86 kernels")
paddle/fluid/lite/operators/use_ops.h
浏览文件 @ b2222692
......@@ -13,9 +13,10 @@
// limitations under the License.
#pragma once
/*
* ATTENTION this header file can only include in .cc file.
*/
// ATTENTION This can only include in a .cc file.
#include "paddle/fluid/lite/core/op_registry.h"
USE_LITE_OP(mul);
USE_LITE_OP(fc);
......
paddle/fluid/lite/tools/build.sh
浏览文件 @ b2222692
......@@ -85,8 +85,8 @@ function build_test_server {
# test_arm_android <some_test_name> <adb_port_number>
function test_arm_android {
test_name=$1
port=$2
local test_name=$1
local port=$2
if [[ "${test_name}x" == "x" ]]; then
echo "test_name can not be empty"
exit 1
......@@ -99,12 +99,18 @@ function test_arm_android {
echo "test name: ${test_name}"
adb_work_dir="/data/local/tmp"
skip_list=("test_model_parser_lite" "test_mobilenetv1_lite" "test_mobilenetv2_lite" "test_resnet50_lite" "test_inceptionv4_lite")
skip_list=("test_model_parser_lite" "test_mobilenetv1_lite" "test_mobilenetv2_lite" "test_resnet50_lite" "test_inceptionv4_lite" "test_light_api")
for skip_name in ${skip_list[@]} ; do
[[ $skip_name =~ (^|[[:space:]])$test_name($|[[:space:]]) ]] && echo "skip $test_name" && return
done
testpath=$(find ./paddle/fluid -name ${test_name})
local testpath=$(find ./paddle/fluid -name ${test_name})
# if [[ "$test_name" == "test_light_api" ]]; then
# local model_path=$(find . -name "lite_naive_model")
# arm_push_necessary_file $port $model_path $adb_work_dir
# fi
adb -s emulator-${port} push ${testpath} ${adb_work_dir}
adb -s emulator-${port} shell chmod +x "${adb_work_dir}/${test_name}"
adb -s emulator-${port} shell "./${adb_work_dir}/${test_name}"
......@@ -204,6 +210,7 @@ function test_arm {
abi=$2
lang=$3
port=$4
if [[ ${os} == "armlinux" ]]; then
# TODO(hongming): enable test armlinux on armv8, armv7 and armv7hf
echo "Skip test arm linux yet. armlinux must in another docker"
......@@ -221,6 +228,7 @@ function test_arm {
return 0
fi
echo "test file: ${TESTS_FILE}"
for _test in $(cat $TESTS_FILE); do
test_arm_android $_test $port
......@@ -242,6 +250,14 @@ function prepare_emulator {
sleep 1m
}
function arm_push_necessary_file {
local port=$1
local testpath=$2
local adb_work_dir=$3
adb -s emulator-${port} push ${testpath} ${adb_work_dir}
}
# We split the arm unittest into several sub-tasks to parallel and reduce the overall CI timetime.
# sub-task1
......@@ -286,20 +302,22 @@ function build_test_arm_subtask_armlinux {
prepare_emulator $port_armv8 $port_armv7
cur=$PWD
# job 5
build_arm "armlinux" "armv8"
test_arm "armlinux" "armv8"
cd -
build_arm "armlinux" "armv8" "gcc" $port_armv8
test_arm "armlinux" "armv8" "gcc" $port_armv8
cd $cur
# job 6
build_arm "armlinux" "armv7"
test_arm "armlinux" "armv7"
cd -
build_arm "armlinux" "armv7" "gcc" $port_armv8
test_arm "armlinux" "armv7" "gcc" $port_armv8
cd $cur
# job 7
build_arm "armlinux" "armv7hf"
test_arm "armlinux" "armv7hf"
cd -
build_arm "armlinux" "armv7hf" "gcc" $port_armv8
test_arm "armlinux" "armv7hf" "gcc" $port_armv8
cd $cur
adb devices | grep emulator | cut -f1 | while read line; do adb -s $line emu kill; done
echo "Done"
......
paddle/fluid/lite/utils/io.h
浏览文件 @ b2222692
......@@ -14,15 +14,18 @@
#pragma once
#include <sys/stat.h>
#ifndef LITE_WITH_ARM
#include <bits/stdc++.h>
#endif
#include <fstream>
#include <string>
#include "paddle/fluid/lite/utils/cp_logging.h"
#include "paddle/fluid/lite/utils/string.h"
namespace paddle {
namespace lite {
static bool IsFileExists(const std::string &path) {
static bool IsFileExists(const std::string& path) {
std::ifstream file(path);
bool res = file.is_open();
if (res) {
......@@ -31,5 +34,13 @@ static bool IsFileExists(const std::string &path) {
return res;
}
// ARM mobile not support mkdir in C++
#ifndef LITE_WITH_ARM
static void MkDirRecur(const std::string& path) {
CHECK_EQ(system(string_format("mkdir -p %s", path.c_str()).c_str()), 0)
<< "Cann't mkdir " << path;
}
#endif
} // namespace lite
} // namespace paddle
paddle/fluid/lite/utils/string.h
浏览文件 @ b2222692
......@@ -74,5 +74,15 @@ static std::string Repr(const std::vector<std::string>& v) {
return "{" + Join(tmp, ",") + "}";
}
static std::vector<std::string> Split(const std::string& s, char delim) {
std::stringstream ss(s);
std::string line;
std::vector<std::string> res;
while (std::getline(ss, line, delim)) {
res.push_back(line);
}
return res;
}
} // namespace lite
} // namespace paddle
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