提交 ec0ea5ca 编写于 作者: S sangoly

complete deployment & add cxx demo

上级 cdddfe68
......@@ -221,10 +221,12 @@ add_subdirectory(gen_code)
add_subdirectory(tools)
# Deployment required
lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "mobilenet_v1.tar.gz")
if (WITH_TESTING)
lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "lite_naive_model.tar.gz")
if(LITE_WITH_LIGHT_WEIGHT_FRAMEWORK)
lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "mobilenet_v1.tar.gz")
lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "mobilenet_v2_relu.tar.gz")
lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "resnet50.tar.gz")
lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "inception_v4_simple.tar.gz")
......@@ -246,27 +248,44 @@ add_custom_target(publish_inference_cxx_lib ${TARGET}
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/cxx/lib"
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/bin"
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/cxx/include"
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/third_party"
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/demo/cxx"
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/demo/models"
COMMAND cp "${CMAKE_SOURCE_DIR}/paddle/fluid/lite/api/paddle_*.h" "${INFER_LITE_PUBLISH_ROOT}/cxx/include"
COMMAND cp "${CMAKE_BINARY_DIR}/libpaddle_api_full_bundled.a" "${INFER_LITE_PUBLISH_ROOT}/cxx/lib"
COMMAND cp "${CMAKE_BINARY_DIR}/paddle/fluid/lite/api/model_optimize_tool" "${INFER_LITE_PUBLISH_ROOT}/bin"
COMMAND cp "${CMAKE_BINARY_DIR}/paddle/fluid/lite/gen_code/paddle_code_generator" "${INFER_LITE_PUBLISH_ROOT}/bin"
COMMAND cp -r "${CMAKE_BINARY_DIR}/third_party/install/glog" "${INFER_LITE_PUBLISH_ROOT}/third_party"
COMMAND cp -r "${CMAKE_BINARY_DIR}/third_party/install/gflags" "${INFER_LITE_PUBLISH_ROOT}/third_party"
COMMAND cp -r "${CMAKE_SOURCE_DIR}/paddle/fluid/lite/demo/cxx/mobile_full" "${INFER_LITE_PUBLISH_ROOT}/demo/cxx"
COMMAND cp "${CMAKE_SOURCE_DIR}/paddle/fluid/lite/demo/cxx/Makefile.def" "${INFER_LITE_PUBLISH_ROOT}/demo/cxx"
COMMAND cp -r "${CMAKE_BINARY_DIR}/third_party/install/mobilenet_v1" "${INFER_LITE_PUBLISH_ROOT}/demo/models"
)
add_dependencies(publish_inference_cxx_lib model_optimize_tool)
add_dependencies(publish_inference_cxx_lib paddle_code_generator)
add_dependencies(publish_inference_cxx_lib bundle_full_api)
add_dependencies(publish_inference_cxx_lib extern_lite_download_mobilenet_v1_tar_gz)
add_dependencies(publish_inference_lite publish_inference_cxx_lib)
if (LITE_WITH_LIGHT_WEIGHT_FRAMEWORK)
#cc_library(inference_mobile_lib DEPS light_api_lite)
# copy cpp mobile_light demo/lib
add_custom_target(publish_inference_mobile_lib ${TARGET}
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/mobile/lib"
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/mobile/bin"
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/mobile/include"
COMMAND cp "${CMAKE_SOURCE_DIR}/paddle/fluid/lite/api/paddle_*.h" "${INFER_LITE_PUBLISH_ROOT}/mobile/include"
COMMAND cp "${CMAKE_BINARY_DIR}/libpaddle_api_light_bundled.a" "${INFER_LITE_PUBLISH_ROOT}/mobile/lib"
COMMAND cp "${CMAKE_BINARY_DIR}/libpaddle_api_light_bundled.a" "${INFER_LITE_PUBLISH_ROOT}/cxx/lib"
COMMAND cp -r "${CMAKE_SOURCE_DIR}/paddle/fluid/lite/demo/cxx/mobile_light" "${INFER_LITE_PUBLISH_ROOT}/demo/cxx"
)
add_dependencies(publish_inference_mobile_lib paddle_api_light bundle_light_api)
add_dependencies(publish_inference_lite publish_inference_mobile_lib)
if (LITE_WITH_JAVA AND LITE_WITH_ARM)
# copy java mobile_light demo/lib
add_custom_target(publish_java_inference_mobile_lib ${TARGET}
COMMAND mkdir -p "${INFER_LITE_PUBLISH_ROOT}/java/so"
COMMAND cp "${CMAKE_BINARY_DIR}/paddle/fluid/lite/api/android/jni/libpaddle_lite_jni.so" "${INFER_LITE_PUBLISH_ROOT}/java/so"
COMMAND cp -r "${CMAKE_SOURCE_DIR}/paddle/fluid/lite/api/android/jni/src" "${INFER_LITE_PUBLISH_ROOT}/java"
)
add_dependencies(publish_java_inference_mobile_lib paddle_lite_jni)
add_dependencies(publish_inference_lite publish_java_inference_mobile_lib)
endif()
endif()
......@@ -113,7 +113,7 @@ lite_cc_library(paddle_api_full SRCS cxx_api_impl.cc DEPS cxx_api_lite paddle_ap
ARM_DEPS ${arm_kernels}
CL_DEPS ${opencl_kernels})
# The final inference library for just MobileConfig.
lite_cc_library(paddle_api_light SRCS light_api_impl.cc DEPS light_api_lite paddle_api_lite)
lite_cc_library(paddle_api_light SRCS light_api_impl.cc DEPS light_api_lite paddle_api_lite mir_passes)
bundle_static_library(paddle_api_full paddle_api_full_bundled bundle_full_api)
bundle_static_library(paddle_api_light paddle_api_light_bundled bundle_light_api)
......
CXX_DEFINES = -DARM_WITH_OMP -DHPPL_STUB_FUNC -DLITE_WITH_ARM -DLITE_WITH_LIGHT_WEIGHT_FRAMEWORK \
-DLITE_WITH_LINUX -DPADDLE_DISABLE_PROFILER -DPADDLE_NO_PYTHON -DPADDLE_WITH_TESTING
LDFLAGS = -latomic -pthread -ldl
SYSROOT_COMPLILE = --sysroot=/opt/android-ndk-r17c/sysroot
THIRD_PARTY_LIBS = ../../../third_party/glog/lib/libglog.a \
../../../third_party/gflags/lib/libgflags.a
SYSTEM_INCLUDES = -I/opt/android-ndk-r17c/sources/cxx-stl/llvm-libc++/include \
-I/opt/android-ndk-r17c/sources/cxx-stl/llvm-libc++abi/include \
-I/opt/android-ndk-r17c/sources/android/support/include \
-I/opt/android-ndk-r17c/sysroot/usr/include \
THIRD_PARTY_INCLUDES = -I../../../third_party/gflags/include \
-I../../../third_party/glog/include
ifeq ($(ARM_ABI), arm8)
CC = /opt/android-ndk-r17c/toolchains/aarch64-linux-android-4.9/prebuilt/linux-x86_64/bin/aarch64-linux-android-g++
CXX_FLAGS = -funwind-tables -no-canonical-prefixes -D__ANDROID_API__=22 -fexceptions -frtti -std=c++11 -fopenmp -O3 -DNDEBUG -fPIE
CXXFLAGS_LINK = $(CXX_FLAGS) -pie -Wl,--gc-sections
SYSROOT_LINK = --sysroot=/opt/android-ndk-r17c/platforms/android-24/arch-arm64
SYSTEM_LIBS = /opt/android-ndk-r17c/sources/cxx-stl/llvm-libc++/libs/arm64-v8a/libc++_static.a \
/opt/android-ndk-r17c/sources/cxx-stl/llvm-libc++/libs/arm64-v8a/libc++abi.a
INCLUDES = $(SYSTEM_INCLUDES) -I/opt/android-ndk-r17c/sysroot/usr/include/aarch64-linux-android $(THIRD_PARTY_INCLUDES)
else
CC = /opt/android-ndk-r17c/toolchains/arm-linux-androideabi-4.9/prebuilt/linux-x86_64/bin/arm-linux-androideabi-g++
CXX_FLAGS = -march=armv7-a -mthumb -mfpu=neon -mfloat-abi=softfp -funwind-tables -no-canonical-prefixes \
-D__ANDROID_API__=22 -fexceptions -frtti -std=c++11 -fopenmp -O3 -DNDEBUG -fPIE
CXXFLAGS_LINK = $(CXX_FLAGS) -pie -Wl,--fix-cortex-a8 -Wl,--gc-sections -Wl,-z,nocopyreloc
SYSROOT_LINK = --sysroot=/opt/android-ndk-r17c/platforms/android-22/arch-arm
SYSTEM_LIBS = /opt/android-ndk-r17c/sources/cxx-stl/llvm-libc++/libs/armeabi-v7a/libc++_static.a \
/opt/android-ndk-r17c/sources/cxx-stl/llvm-libc++/libs/armeabi-v7a/libc++abi.a \
/opt/android-ndk-r17c/sources/cxx-stl/llvm-libc++/libs/armeabi-v7a/libandroid_support.a \
/opt/android-ndk-r17c/sources/cxx-stl/llvm-libc++/libs/armeabi-v7a/libunwind.a
INCLUDES = $(SYSTEM_INCLUDES) -I/opt/android-ndk-r17c/sysroot/usr/include/arm-linux-androideabi $(THIRD_PARTY_INCLUDES)
endif
ARM_ABI = arm8
export ARM_ABI
include ../Makefile.def
LITE_ROOT=../../../
CXX_INCLUDES = $(INCLUDES) -I$(LITE_ROOT)/cxx/include
CXX_LIBS = $(THIRD_PARTY_LIBS) $(LITE_ROOT)/cxx/lib/libpaddle_api_full_bundled.a $(SYSTEM_LIBS)
mobilenetv1_full_api: mobilenetv1_full_api.o
$(CC) $(SYSROOT_LINK) $(CXXFLAGS_LINK) mobilenetv1_full_api.o -o mobilenetv1_full_api $(CXX_LIBS) $(LDFLAGS)
mobilenetv1_full_api.o: mobilenetv1_full_api.cc
$(CC) $(SYSROOT_COMPLILE) $(CXX_DEFINES) $(CXX_INCLUDES) $(CXX_FLAGS) -o mobilenetv1_full_api.o -c mobilenetv1_full_api.cc
.PHONY: clean
clean:
rm mobilenetv1_full_api.o
rm mobilenetv1_full_api
// 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.
#include <gflags/gflags.h>
#include <glog/logging.h>
#include <iostream>
#include <vector>
#include "paddle_api.h" // NOLINT
#include "paddle_use_kernels.h" // NOLINT
#include "paddle_use_ops.h" // NOLINT
#include "paddle_use_passes.h" // NOLINT
using namespace paddle::lite_api; // NOLINT
DEFINE_string(model_dir, "", "Model dir path.");
DEFINE_string(optimized_model_dir, "", "Optimized model dir.");
int64_t ShapeProduction(const shape_t& shape) {
int64_t res = 1;
for (auto i : shape) res *= i;
return res;
}
void RunModel() {
// 1. Set CxxConfig
CxxConfig config;
config.set_model_dir(FLAGS_model_dir);
config.set_preferred_place(Place{TARGET(kX86), PRECISION(kFloat)});
config.set_valid_places({Place{TARGET(kX86), PRECISION(kFloat)},
Place{TARGET(kARM), PRECISION(kFloat)}});
// 2. Create PaddlePredictor by CxxConfig
std::shared_ptr<PaddlePredictor> predictor =
CreatePaddlePredictor<CxxConfig>(config);
// 3. Prepare input data
std::unique_ptr<Tensor> input_tensor(std::move(predictor->GetInput(0)));
input_tensor->Resize(shape_t({1, 3, 224, 224}));
auto* data = input_tensor->mutable_data<float>();
for (int i = 0; i < ShapeProduction(input_tensor->shape()); ++i) {
data[i] = 1;
}
// 4. Run predictor
predictor->Run();
// 5. Get output
std::unique_ptr<const Tensor> output_tensor(
std::move(predictor->GetOutput(0)));
LOG(INFO) << "Ouput dim: " << output_tensor->shape()[1] << std::endl;
for (int i = 0; i < ShapeProduction(output_tensor->shape()); i += 100) {
LOG(INFO) << "Output[" << i << "]: " << output_tensor->data<float>()[i]
<< std::endl;
}
// 6. Save optimition model
predictor->SaveOptimizedModel(FLAGS_optimized_model_dir);
}
int main(int argc, char** argv) {
google::ParseCommandLineFlags(&argc, &argv, true);
RunModel();
return 0;
}
ARM_ABI = arm8
export ARM_ABI
include ../Makefile.def
LITE_ROOT=../../../
CXX_INCLUDES = $(INCLUDES) -I$(LITE_ROOT)/cxx/include
CXX_LIBS = $(THIRD_PARTY_LIBS) $(LITE_ROOT)/cxx/lib/libpaddle_api_light_bundled.a $(SYSTEM_LIBS)
mobilenetv1_light_api: mobilenetv1_light_api.o
$(CC) $(SYSROOT_LINK) $(CXXFLAGS_LINK) mobilenetv1_light_api.o -o mobilenetv1_light_api $(CXX_LIBS) $(LDFLAGS)
mobilenetv1_light_api.o: mobilenetv1_light_api.cc
$(CC) $(SYSROOT_COMPLILE) $(CXX_DEFINES) $(CXX_INCLUDES) $(CXX_FLAGS) -o mobilenetv1_light_api.o -c mobilenetv1_light_api.cc
.PHONY: clean
clean:
rm mobilenetv1_light_api.o
rm mobilenetv1_light_api
// 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.
#include <gflags/gflags.h>
#include <glog/logging.h>
#include <iostream>
#include <vector>
#include "paddle_api.h" // NOLINT
#include "paddle_use_kernels.h" // NOLINT
#include "paddle_use_ops.h" // NOLINT
#include "paddle_use_passes.h" // NOLINT
using namespace paddle::lite_api; // NOLINT
DEFINE_string(model_dir, "", "Model dir path.");
int64_t ShapeProduction(const shape_t& shape) {
int64_t res = 1;
for (auto i : shape) res *= i;
return res;
}
void RunModel() {
// 1. Set MobileConfig
MobileConfig config;
config.set_model_dir(FLAGS_model_dir);
// 2. Create PaddlePredictor by MobileConfig
std::shared_ptr<PaddlePredictor> predictor =
CreatePaddlePredictor<MobileConfig>(config);
// 3. Prepare input data
std::unique_ptr<Tensor> input_tensor(std::move(predictor->GetInput(0)));
input_tensor->Resize({1, 3, 224, 224});
auto* data = input_tensor->mutable_data<float>();
for (int i = 0; i < ShapeProduction(input_tensor->shape()); ++i) {
data[i] = 1;
}
// 4. Run predictor
predictor->Run();
// 5. Get output
std::unique_ptr<const Tensor> output_tensor(
std::move(predictor->GetOutput(0)));
LOG(INFO) << "Ouput dim: " << output_tensor->shape()[1] << std::endl;
for (int i = 0; i < ShapeProduction(output_tensor->shape()); i += 100) {
LOG(INFO) << "Output[" << i << "]: " << output_tensor->data<float>()[i]
<< std::endl;
}
}
int main(int argc, char** argv) {
google::ParseCommandLineFlags(&argc, &argv, true);
RunModel();
return 0;
}
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