| @@ -1,5 +1,6 @@ | |||
| file (GLOB_RECURSE SOURCES ./*.cpp) | |||
| add_executable(lite_examples ${SOURCES}) | |||
| target_include_directories(lite_examples PUBLIC ./) | |||
| if(LITE_BUILD_WITH_RKNPU) | |||
| #rknn sdk1.0.0 depend on libc++_shared, use gold to remove NEEDED so symbol check | |||
| @@ -33,6 +34,7 @@ if(LITE_BUILD_WITH_RKNPU) | |||
| endif() | |||
| target_link_libraries(lite_examples_depends_shared lite_shared) | |||
| target_include_directories(lite_examples_depends_shared PUBLIC ./) | |||
| if(UNIX) | |||
| if(APPLE OR ANDROID) | |||
| @@ -49,57 +49,20 @@ ExampleFuncMap* get_example_function_map(); | |||
| bool register_example(std::string example_name, const ExampleFunc& fuction); | |||
| template <int> | |||
| struct Register; | |||
| #if LITE_BUILD_WITH_MGE | |||
| bool basic_load_from_path(const Args& args); | |||
| bool basic_load_from_path_with_loader(const Args& args); | |||
| bool basic_load_from_memory(const Args& args); | |||
| bool cpu_affinity(const Args& args); | |||
| bool network_share_same_weights(const Args& args); | |||
| bool reset_input(const Args& args); | |||
| bool reset_input_output(const Args& args); | |||
| bool config_user_allocator(const Args& args); | |||
| bool register_cryption_method(const Args& args); | |||
| bool update_cryption_key(const Args& args); | |||
| bool async_forward(const Args& args); | |||
| bool set_input_callback(const Args& arg); | |||
| bool set_output_callback(const Args& arg); | |||
| bool picture_classification(const Args& arg); | |||
| bool detect_yolox(const Args& arg); | |||
| #if LITE_WITH_CUDA | |||
| bool load_from_path_run_cuda(const Args& args); | |||
| bool device_input(const Args& args); | |||
| bool device_input_output(const Args& args); | |||
| bool pinned_host_input(const Args& args); | |||
| #endif | |||
| #endif | |||
| } // namespace example | |||
| } // namespace lite | |||
| #if LITE_BUILD_WITH_MGE | |||
| bool basic_c_interface(const lite::example::Args& args); | |||
| bool device_io_c_interface(const lite::example::Args& args); | |||
| bool async_c_interface(const lite::example::Args& args); | |||
| #endif | |||
| #define CONCAT_IMPL(a, b) a##b | |||
| #define MACRO_CONCAT(a, b) CONCAT_IMPL(a, b) | |||
| #define REGIST_EXAMPLE(name_, func_) REGIST_EXAMPLE_WITH_NUM(__COUNTER__, name_, func_) | |||
| #define REGIST_EXAMPLE_WITH_NUM(number_, name_, func_) \ | |||
| template <> \ | |||
| struct Register<number_> { \ | |||
| Register() { register_example(name_, func_); } \ | |||
| }; \ | |||
| namespace { \ | |||
| Register<number_> MACRO_CONCAT(example_function_, number_); \ | |||
| #define REGIST_EXAMPLE_WITH_NUM(number_, name_, func_) \ | |||
| struct Register_##func_ { \ | |||
| Register_##func_() { lite::example::register_example(name_, func_); } \ | |||
| }; \ | |||
| namespace { \ | |||
| Register_##func_ MACRO_CONCAT(func_, number_); \ | |||
| } | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||
| @@ -60,7 +60,8 @@ bool lite::example::register_example( | |||
| std::string example_name, const ExampleFunc& fuction) { | |||
| auto map = get_example_function_map(); | |||
| if (map->find(example_name) != map->end()) { | |||
| printf("Error!!! This example is registed yet\n"); | |||
| printf("example_name: %s Error!!! This example is registed yet\n", | |||
| example_name.c_str()); | |||
| return false; | |||
| } | |||
| (*map)[example_name] = fuction; | |||
| @@ -142,41 +143,5 @@ int main(int argc, char** argv) { | |||
| return -1; | |||
| } | |||
| } | |||
| namespace lite { | |||
| namespace example { | |||
| #if LITE_BUILD_WITH_MGE | |||
| #if LITE_WITH_CUDA | |||
| REGIST_EXAMPLE("load_from_path_run_cuda", load_from_path_run_cuda); | |||
| #endif | |||
| REGIST_EXAMPLE("basic_load_from_path", basic_load_from_path); | |||
| REGIST_EXAMPLE("basic_load_from_path_with_loader", basic_load_from_path_with_loader); | |||
| REGIST_EXAMPLE("basic_load_from_memory", basic_load_from_memory); | |||
| REGIST_EXAMPLE("cpu_affinity", cpu_affinity); | |||
| REGIST_EXAMPLE("register_cryption_method", register_cryption_method); | |||
| REGIST_EXAMPLE("update_cryption_key", update_cryption_key); | |||
| REGIST_EXAMPLE("network_share_same_weights", network_share_same_weights); | |||
| REGIST_EXAMPLE("reset_input", reset_input); | |||
| REGIST_EXAMPLE("reset_input_output", reset_input_output); | |||
| REGIST_EXAMPLE("config_user_allocator", config_user_allocator); | |||
| REGIST_EXAMPLE("async_forward", async_forward); | |||
| REGIST_EXAMPLE("set_input_callback", set_input_callback); | |||
| REGIST_EXAMPLE("set_output_callback", set_output_callback); | |||
| REGIST_EXAMPLE("basic_c_interface", basic_c_interface); | |||
| REGIST_EXAMPLE("device_io_c_interface", device_io_c_interface); | |||
| REGIST_EXAMPLE("async_c_interface", async_c_interface); | |||
| REGIST_EXAMPLE("picture_classification", picture_classification); | |||
| REGIST_EXAMPLE("detect_yolox", detect_yolox); | |||
| #if LITE_WITH_CUDA | |||
| REGIST_EXAMPLE("device_input", device_input); | |||
| REGIST_EXAMPLE("device_input_output", device_input_output); | |||
| REGIST_EXAMPLE("pinned_host_input", pinned_host_input); | |||
| #endif | |||
| #endif | |||
| } // namespace example | |||
| } // namespace lite | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||
| @@ -10,7 +10,7 @@ | |||
| */ | |||
| #include <thread> | |||
| #include "../example.h" | |||
| #include "example.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| #include <cstdio> | |||
| @@ -77,61 +77,8 @@ void output_data_info(std::shared_ptr<Network> network, size_t output_size) { | |||
| } | |||
| } // namespace | |||
| #if LITE_WITH_CUDA | |||
| bool lite::example::load_from_path_run_cuda(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| set_log_level(LiteLogLevel::DEBUG); | |||
| //! config the network running in CUDA device | |||
| lite::Config config{false, -1, LiteDeviceType::LITE_CUDA}; | |||
| //! set NetworkIO | |||
| NetworkIO network_io; | |||
| std::string input_name = "img0_comp_fullface"; | |||
| bool is_host = false; | |||
| IO device_input{input_name, is_host}; | |||
| network_io.inputs.push_back(device_input); | |||
| //! create and load the network | |||
| std::shared_ptr<Network> network = std::make_shared<Network>(config, network_io); | |||
| network->load_model(network_path); | |||
| std::shared_ptr<Tensor> input_tensor = network->get_input_tensor(0); | |||
| Layout input_layout = input_tensor->get_layout(); | |||
| //! read data from numpy data file | |||
| auto src_tensor = parse_npy(input_path); | |||
| //! malloc the device memory | |||
| auto tensor_device = Tensor(LiteDeviceType::LITE_CUDA, input_layout); | |||
| //! copy to the device memory | |||
| tensor_device.copy_from(*src_tensor); | |||
| //! Now the device memory if filled with user input data, set it to the | |||
| //! input tensor | |||
| input_tensor->reset(tensor_device.get_memory_ptr(), input_layout); | |||
| //! forward | |||
| { | |||
| lite::Timer ltimer("warmup"); | |||
| network->forward(); | |||
| network->wait(); | |||
| ltimer.print_used_time(0); | |||
| } | |||
| lite::Timer ltimer("forward_iter"); | |||
| for (int i = 0; i < 10; i++) { | |||
| ltimer.reset_start(); | |||
| network->forward(); | |||
| network->wait(); | |||
| ltimer.print_used_time(i); | |||
| } | |||
| //! get the output data or read tensor set in network_in | |||
| size_t output_size = network->get_all_output_name().size(); | |||
| output_info(network, output_size); | |||
| output_data_info(network, output_size); | |||
| return true; | |||
| } | |||
| #endif | |||
| bool lite::example::basic_load_from_path(const Args& args) { | |||
| namespace { | |||
| bool basic_load_from_path(const Args& args) { | |||
| set_log_level(LiteLogLevel::DEBUG); | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -193,7 +140,7 @@ bool lite::example::basic_load_from_path(const Args& args) { | |||
| return true; | |||
| } | |||
| bool lite::example::basic_load_from_path_with_loader(const Args& args) { | |||
| bool basic_load_from_path_with_loader(const Args& args) { | |||
| set_log_level(LiteLogLevel::DEBUG); | |||
| lite::set_loader_lib_path(args.loader_path); | |||
| std::string network_path = args.model_path; | |||
| @@ -251,7 +198,7 @@ bool lite::example::basic_load_from_path_with_loader(const Args& args) { | |||
| return true; | |||
| } | |||
| bool lite::example::basic_load_from_memory(const Args& args) { | |||
| bool basic_load_from_memory(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -307,7 +254,7 @@ bool lite::example::basic_load_from_memory(const Args& args) { | |||
| return true; | |||
| } | |||
| bool lite::example::async_forward(const Args& args) { | |||
| bool async_forward(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| Config config; | |||
| @@ -366,7 +313,7 @@ bool lite::example::async_forward(const Args& args) { | |||
| return true; | |||
| } | |||
| bool lite::example::set_input_callback(const Args& args) { | |||
| bool set_input_callback(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| Config config; | |||
| @@ -433,7 +380,7 @@ bool lite::example::set_input_callback(const Args& args) { | |||
| return true; | |||
| } | |||
| bool lite::example::set_output_callback(const Args& args) { | |||
| bool set_output_callback(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| Config config; | |||
| @@ -500,7 +447,73 @@ bool lite::example::set_output_callback(const Args& args) { | |||
| printf("max=%e, sum=%e\n", max, sum); | |||
| return true; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("basic_load_from_path", basic_load_from_path); | |||
| REGIST_EXAMPLE("basic_load_from_path_with_loader", basic_load_from_path_with_loader); | |||
| REGIST_EXAMPLE("basic_load_from_memory", basic_load_from_memory); | |||
| REGIST_EXAMPLE("async_forward", async_forward); | |||
| REGIST_EXAMPLE("set_input_callback", set_input_callback); | |||
| REGIST_EXAMPLE("set_output_callback", set_output_callback); | |||
| #if LITE_WITH_CUDA | |||
| namespace { | |||
| bool load_from_path_run_cuda(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| set_log_level(LiteLogLevel::DEBUG); | |||
| //! config the network running in CUDA device | |||
| lite::Config config{false, -1, LiteDeviceType::LITE_CUDA}; | |||
| //! set NetworkIO | |||
| NetworkIO network_io; | |||
| std::string input_name = "img0_comp_fullface"; | |||
| bool is_host = false; | |||
| IO device_input{input_name, is_host}; | |||
| network_io.inputs.push_back(device_input); | |||
| //! create and load the network | |||
| std::shared_ptr<Network> network = std::make_shared<Network>(config, network_io); | |||
| network->load_model(network_path); | |||
| std::shared_ptr<Tensor> input_tensor = network->get_input_tensor(0); | |||
| Layout input_layout = input_tensor->get_layout(); | |||
| //! read data from numpy data file | |||
| auto src_tensor = parse_npy(input_path); | |||
| //! malloc the device memory | |||
| auto tensor_device = Tensor(LiteDeviceType::LITE_CUDA, input_layout); | |||
| //! copy to the device memory | |||
| tensor_device.copy_from(*src_tensor); | |||
| //! Now the device memory if filled with user input data, set it to the | |||
| //! input tensor | |||
| input_tensor->reset(tensor_device.get_memory_ptr(), input_layout); | |||
| //! forward | |||
| { | |||
| lite::Timer ltimer("warmup"); | |||
| network->forward(); | |||
| network->wait(); | |||
| ltimer.print_used_time(0); | |||
| } | |||
| lite::Timer ltimer("forward_iter"); | |||
| for (int i = 0; i < 10; i++) { | |||
| ltimer.reset_start(); | |||
| network->forward(); | |||
| network->wait(); | |||
| ltimer.print_used_time(i); | |||
| } | |||
| //! get the output data or read tensor set in network_in | |||
| size_t output_size = network->get_all_output_name().size(); | |||
| output_info(network, output_size); | |||
| output_data_info(network, output_size); | |||
| return true; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("load_from_path_run_cuda", load_from_path_run_cuda); | |||
| #endif | |||
| #endif | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||
| @@ -9,13 +9,14 @@ | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| */ | |||
| #include "../example.h" | |||
| #include "example.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| using namespace lite; | |||
| using namespace example; | |||
| bool lite::example::cpu_affinity(const Args& args) { | |||
| namespace { | |||
| bool cpu_affinity(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -65,6 +66,9 @@ bool lite::example::cpu_affinity(const Args& args) { | |||
| printf("max=%e, sum=%e\n", max, sum); | |||
| return true; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("cpu_affinity", cpu_affinity); | |||
| #endif | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||
| @@ -10,7 +10,7 @@ | |||
| */ | |||
| #include <thread> | |||
| #include "../../example.h" | |||
| #include "example.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| #include <cstdio> | |||
| @@ -289,6 +289,10 @@ void decode_outputs( | |||
| void draw_objects( | |||
| uint8_t* image, int width, int height, int channel, | |||
| const std::vector<Object>& objects) { | |||
| (void)image; | |||
| (void)width; | |||
| (void)height; | |||
| (void)channel; | |||
| for (size_t i = 0; i < objects.size(); i++) { | |||
| const Object& obj = objects[i]; | |||
| @@ -297,9 +301,7 @@ void draw_objects( | |||
| } | |||
| } | |||
| } // namespace | |||
| bool lite::example::detect_yolox(const Args& args) { | |||
| bool detect_yolox(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -332,6 +334,9 @@ bool lite::example::detect_yolox(const Args& args) { | |||
| stbi_image_free(image); | |||
| return 0; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("detect_yolox", detect_yolox); | |||
| #endif | |||
| @@ -10,7 +10,7 @@ | |||
| */ | |||
| #include <thread> | |||
| #include "../../example.h" | |||
| #include "example.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| #include <cstdio> | |||
| @@ -80,9 +80,8 @@ void classfication_process( | |||
| } | |||
| printf("output tensor sum is %f\n", sum); | |||
| } | |||
| } // namespace | |||
| bool lite::example::picture_classification(const Args& args) { | |||
| bool picture_classification(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -109,6 +108,9 @@ bool lite::example::picture_classification(const Args& args) { | |||
| class_id, score); | |||
| return 0; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("picture_classification", picture_classification); | |||
| #endif | |||
| @@ -10,15 +10,17 @@ | |||
| */ | |||
| #include <thread> | |||
| #include "../example.h" | |||
| #include "example.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| #include "misc.h" | |||
| using namespace lite; | |||
| using namespace example; | |||
| #if LITE_WITH_CUDA | |||
| bool lite::example::device_input(const Args& args) { | |||
| namespace { | |||
| bool device_input(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -73,7 +75,7 @@ bool lite::example::device_input(const Args& args) { | |||
| return true; | |||
| } | |||
| bool lite::example::device_input_output(const Args& args) { | |||
| bool device_input_output(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -136,7 +138,7 @@ bool lite::example::device_input_output(const Args& args) { | |||
| return true; | |||
| } | |||
| bool lite::example::pinned_host_input(const Args& args) { | |||
| bool pinned_host_input(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -181,6 +183,11 @@ bool lite::example::pinned_host_input(const Args& args) { | |||
| printf("max=%e, sum=%e\n", max, sum); | |||
| return true; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("device_input", device_input); | |||
| REGIST_EXAMPLE("device_input_output", device_input_output); | |||
| REGIST_EXAMPLE("pinned_host_input", pinned_host_input); | |||
| #endif | |||
| #endif | |||
| @@ -9,7 +9,7 @@ | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| */ | |||
| #include "../example.h" | |||
| #include "example.h" | |||
| #include "misc.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| #include "lite-c/global_c.h" | |||
| @@ -218,5 +218,10 @@ bool async_c_interface(const lite::example::Args& args) { | |||
| printf("max=%e, sum=%e\n", max, sum); | |||
| return true; | |||
| } | |||
| REGIST_EXAMPLE("basic_c_interface", basic_c_interface); | |||
| REGIST_EXAMPLE("device_io_c_interface", device_io_c_interface); | |||
| REGIST_EXAMPLE("async_c_interface", async_c_interface); | |||
| #endif | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||
| @@ -9,13 +9,15 @@ | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| */ | |||
| #include "../example.h" | |||
| #include "example.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| using namespace lite; | |||
| using namespace example; | |||
| bool lite::example::network_share_same_weights(const Args& args) { | |||
| namespace { | |||
| bool network_share_same_weights(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -75,5 +77,9 @@ bool lite::example::network_share_same_weights(const Args& args) { | |||
| printf("max=%e, sum=%e\n", max, sum); | |||
| return true; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("network_share_same_weights", network_share_same_weights); | |||
| #endif | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||
| @@ -9,13 +9,15 @@ | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| */ | |||
| #include "../example.h" | |||
| #include "example.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| using namespace lite; | |||
| using namespace example; | |||
| bool lite::example::reset_input(const Args& args) { | |||
| namespace { | |||
| bool reset_input(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| lite::Config config; | |||
| @@ -53,7 +55,7 @@ bool lite::example::reset_input(const Args& args) { | |||
| return true; | |||
| } | |||
| bool lite::example::reset_input_output(const Args& args) { | |||
| bool reset_input_output(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| lite::Config config; | |||
| @@ -92,5 +94,10 @@ bool lite::example::reset_input_output(const Args& args) { | |||
| printf("max=%e, sum=%e\n", max, sum); | |||
| return true; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("reset_input", reset_input); | |||
| REGIST_EXAMPLE("reset_input_output", reset_input_output); | |||
| #endif | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||
| @@ -9,7 +9,7 @@ | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| */ | |||
| #include "../example.h" | |||
| #include "example.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| using namespace lite; | |||
| using namespace example; | |||
| @@ -42,9 +42,8 @@ public: | |||
| #endif | |||
| }; | |||
| }; | |||
| } // namespace | |||
| bool lite::example::config_user_allocator(const Args& args) { | |||
| bool config_user_allocator(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -87,5 +86,9 @@ bool lite::example::config_user_allocator(const Args& args) { | |||
| printf("max=%e, sum=%e\n", max, sum); | |||
| return true; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("config_user_allocator", config_user_allocator); | |||
| #endif | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||
| @@ -9,7 +9,7 @@ | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| */ | |||
| #include "../example.h" | |||
| #include "example.h" | |||
| #if LITE_BUILD_WITH_MGE | |||
| using namespace lite; | |||
| @@ -31,9 +31,8 @@ std::vector<uint8_t> decrypt_model( | |||
| return {}; | |||
| } | |||
| } | |||
| } // namespace | |||
| bool lite::example::register_cryption_method(const Args& args) { | |||
| bool register_cryption_method(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -75,7 +74,7 @@ bool lite::example::register_cryption_method(const Args& args) { | |||
| return true; | |||
| } | |||
| bool lite::example::update_cryption_key(const Args& args) { | |||
| bool update_cryption_key(const Args& args) { | |||
| std::string network_path = args.model_path; | |||
| std::string input_path = args.input_path; | |||
| @@ -120,5 +119,9 @@ bool lite::example::update_cryption_key(const Args& args) { | |||
| printf("max=%e, sum=%e\n", max, sum); | |||
| return true; | |||
| } | |||
| } // namespace | |||
| REGIST_EXAMPLE("register_cryption_method", register_cryption_method); | |||
| REGIST_EXAMPLE("update_cryption_key", update_cryption_key); | |||
| #endif | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||