@@ -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}}} |