未验证 提交 6a08d3ac 编写于 作者: Y ysh329 提交者: GitHub

[OPENCL][API] add opencl valid api for device. test=develop (#3951)

* add opencl valid api for device
上级 0db9f728
......@@ -37,14 +37,25 @@ rm ./lite/api/paddle_use_kernels.h
rm ./lite/api/paddle_use_ops.h
# 设置编译参数并开始编译
# android-armv7:cpu+gpu+cv+extra
./lite/tools/build_android.sh \
--arch=armv7 \
--toolchain=clang \
--with_cv=OFF \
--with_log=OFF \
--with_extra=OFF \
--with_extra=ON \
--with_cv=ON \
--with_opencl=ON
# android-armv8:cpu+gpu+cv+extra
./lite/tools/build_android.sh \
--arch=armv8 \
--toolchain=clang \
--with_log=OFF \
--with_extra=ON \
--with_cv=ON \
--with_opencl=ON
# 注:编译帮助请执行: ./lite/tools/build_android.sh help
```
......@@ -206,7 +217,7 @@ adb shell "export GLOG_v=4; \
## 3. 如何在Code中使用
即编译产物`demo/cxx/mobile_light`目录下的代码,在线版参考GitHub仓库[./lite/demo/cxx/mobile_light/mobilenetv1_light_api.cc](https://github.com/PaddlePaddle/Paddle-Lite/blob/develop/lite/demo/cxx/mobile_light/mobilenetv1_light_api.cc);
即编译产物`demo/cxx/mobile_light`目录下的代码,在线版参考GitHub仓库[./lite/demo/cxx/mobile_light/mobilenetv1_light_api.cc](https://github.com/PaddlePaddle/Paddle-Lite/blob/develop/lite/demo/cxx/mobile_light/mobilenetv1_light_api.cc),其中也包括判断当前设备是否支持OpenCL的方法;
注:这里给出的链接会跳转到线上最新develop分支的代码,很可能与您本地的代码存在差异,建议参考自己本地位于`lite/demo/cxx/`目录的代码,查看如何使用。
......
......@@ -32,9 +32,22 @@
#include "lite/backends/mlu/target_wrapper.h"
#endif
#ifdef LITE_WITH_OPENCL
#include "lite/backends/opencl/cl_runtime.h"
#endif
namespace paddle {
namespace lite_api {
bool IsOpenCLBackendValid() {
bool opencl_valid = false;
#ifdef LITE_WITH_OPENCL
opencl_valid = paddle::lite::CLRuntime::Global()->OpenCLAvaliableForDevice();
#endif
LOG(INFO) << "opencl_valid:" << opencl_valid;
return opencl_valid;
}
Tensor::Tensor(void *raw) : raw_tensor_(raw) {}
// TODO(Superjomn) refine this by using another `const void* const_raw`;
......
......@@ -33,6 +33,9 @@ using lod_t = std::vector<std::vector<uint64_t>>;
enum class LiteModelType { kProtobuf = 0, kNaiveBuffer, UNK };
// return true if current device supports OpenCL model
LITE_API bool IsOpenCLBackendValid();
struct LITE_API Tensor {
explicit Tensor(void* raw);
explicit Tensor(const void* raw);
......
......@@ -38,17 +38,20 @@ CLRuntime::~CLRuntime() {
}
bool CLRuntime::Init() {
if (initialized_) {
if (is_cl_runtime_initialized_) {
return true;
}
bool is_platform_init = InitializePlatform();
bool is_device_init = InitializeDevice();
is_init_success_ = is_platform_init && is_device_init;
initialized_ = true;
context_ = CreateContext();
command_queue_ = CreateCommandQueue(context());
return initialized_;
LOG(INFO) << "is_platform_init:" << is_platform_init;
LOG(INFO) << "is_device_init:" << is_device_init;
if ((is_platform_init == true) && (is_device_init == true)) {
is_platform_device_init_success_ = true;
context_ = CreateContext();
command_queue_ = CreateCommandQueue(context());
is_cl_runtime_initialized_ = true;
}
return is_cl_runtime_initialized_;
}
cl::Platform& CLRuntime::platform() {
......@@ -64,7 +67,9 @@ cl::Context& CLRuntime::context() {
}
cl::Device& CLRuntime::device() {
CHECK(device_ != nullptr) << "device_ is not initialized!";
if (device_ == nullptr) {
LOG(ERROR) << "device_ is not initialized!";
}
return *device_;
}
......@@ -150,6 +155,14 @@ GpuType CLRuntime::ParseGpuTypeFromDeviceName(std::string device_name) {
}
bool CLRuntime::InitializeDevice() {
VLOG(3) << "device_info_.size():" << device_info_.size();
for (auto i : device_info_) {
VLOG(3) << ">>> " << i.first << " " << i.second;
}
if (device_info_.size() > 0 && device_info_.size() <= 2) {
return false;
}
device_info_["PLACEHOLDER"] = 1;
// ===================== BASIC =====================
// CL_DEVICE_TYPE_GPU
// CL_DEVICE_NAME
......@@ -160,7 +173,7 @@ bool CLRuntime::InitializeDevice() {
status_ = platform_->getDevices(CL_DEVICE_TYPE_GPU, &all_devices);
CL_CHECK_ERROR(status_);
if (all_devices.empty()) {
LOG(FATAL) << "No OpenCL GPU device found!";
LOG(ERROR) << "No available OpenCL GPU device found!";
return false;
}
device_ = std::make_shared<cl::Device>();
......@@ -313,9 +326,6 @@ bool CLRuntime::InitializeDevice() {
}
std::map<std::string, size_t>& CLRuntime::GetDeviceInfo() {
if (0 != device_info_.size()) {
return device_info_;
}
InitializeDevice();
return device_info_;
}
......
......@@ -18,6 +18,7 @@ limitations under the License. */
#include <vector>
#include "lite/backends/opencl/cl_include.h"
#include "lite/backends/opencl/cl_utility.h"
#include "lite/backends/opencl/cl_wrapper.h"
typedef enum {
UNKNOWN = 0,
......@@ -68,6 +69,28 @@ class CLRuntime {
public:
static CLRuntime* Global();
bool OpenCLAvaliableForDevice() {
bool opencl_lib_found = paddle::lite::CLWrapper::Global()->OpenclLibFound();
LOG(INFO) << "opencl_lib_found:" << opencl_lib_found;
if (opencl_lib_found == false) return false;
bool dlsym_success = paddle::lite::CLWrapper::Global()->DlsymSuccess();
LOG(INFO) << "dlsym_success:" << dlsym_success;
if (opencl_lib_found == false) return false;
InitializeDevice();
bool support_fp16 =
static_cast<bool>(device_info_["CL_DEVICE_EXTENSIONS_FP16"]);
LOG(INFO) << "support_fp16:" << support_fp16;
if (support_fp16 == false) return false;
is_device_avaliable_for_opencl_ =
dlsym_success && opencl_lib_found && support_fp16;
LOG(INFO) << "is_device_avaliable_for_opencl_:"
<< is_device_avaliable_for_opencl_;
return is_device_avaliable_for_opencl_;
}
bool Init();
cl::Platform& platform();
......@@ -85,7 +108,7 @@ class CLRuntime {
bool BuildProgram(cl::Program* program, const std::string& options = "");
bool IsInitSuccess() { return is_init_success_; }
bool IsInitSuccess() { return is_platform_device_init_success_; }
std::string cl_path() { return cl_path_; }
......@@ -167,9 +190,11 @@ class CLRuntime {
cl_int status_{CL_SUCCESS};
bool initialized_{false};
bool is_device_avaliable_for_opencl_{false};
bool is_cl_runtime_initialized_{false};
bool is_init_success_{false};
bool is_platform_device_init_success_{false};
};
} // namespace lite
......
......@@ -19,14 +19,16 @@ limitations under the License. */
namespace paddle {
namespace lite {
CLWrapper *CLWrapper::Global() {
static CLWrapper wrapper;
return &wrapper;
}
CLWrapper::CLWrapper() {
CHECK(InitHandle()) << "Fail to initialize the OpenCL library!";
InitFunctions();
opencl_lib_found_ = InitHandle();
CHECK(opencl_lib_found_) << "Fail to initialize the OpenCL library!";
dlsym_success_ = InitFunctions();
}
bool CLWrapper::InitHandle() {
......@@ -68,15 +70,17 @@ bool CLWrapper::InitHandle() {
}
}
void CLWrapper::InitFunctions() {
bool CLWrapper::InitFunctions() {
CHECK(handle_ != nullptr) << "The library handle can't be null!";
bool dlsym_success = true;
#define PADDLE_DLSYM(cl_func) \
do { \
cl_func##_ = (cl_func##Type)dlsym(handle_, #cl_func); \
if (cl_func##_ == nullptr) { \
LOG(FATAL) << "Cannot find the " << #cl_func \
LOG(ERROR) << "Cannot find the " << #cl_func \
<< " symbol in libOpenCL.so!"; \
dlsym_success = false; \
break; \
} \
VLOG(4) << "Loaded the " << #cl_func << " symbol successfully."; \
......@@ -137,6 +141,7 @@ void CLWrapper::InitFunctions() {
PADDLE_DLSYM(clEnqueueCopyImage);
#undef PADDLE_DLSYM
return dlsym_success;
}
} // namespace lite
......
......@@ -508,13 +508,20 @@ class CLWrapper final {
return clEnqueueCopyImage_;
}
bool OpenclLibFound() { return opencl_lib_found_; }
bool DlsymSuccess() { return dlsym_success_; }
private:
CLWrapper();
CLWrapper(const CLWrapper &) = delete;
CLWrapper &operator=(const CLWrapper &) = delete;
bool InitHandle();
void InitFunctions();
bool InitFunctions();
bool opencl_lib_found_{true};
bool dlsym_success_{true};
void *handle_{nullptr};
clGetPlatformIDsType clGetPlatformIDs_{nullptr};
clGetPlatformInfoType clGetPlatformInfo_{nullptr};
clBuildProgramType clBuildProgram_{nullptr};
......
......@@ -78,6 +78,28 @@ void RunModel(std::string model_dir,
// 1. Set MobileConfig
MobileConfig config;
config.set_model_from_file(model_dir);
// NOTE: Use android gpu with opencl, you should ensure:
// first, [compile **cpu+opencl** paddlelite
// lib](https://github.com/PaddlePaddle/Paddle-Lite/blob/develop/docs/demo_guides/opencl.md);
// second, [convert and use opencl nb
// model](https://github.com/PaddlePaddle/Paddle-Lite/blob/develop/docs/user_guides/opt/opt_bin.md).
//
/* Uncomment code below to enable OpenCL
bool is_opencl_backend_valid = ::IsOpenCLBackendValid();
std::cout << "is_opencl_backend_valid:" << is_opencl_backend_valid <<
std::endl;
if (is_opencl_backend_valid) {
// give opencl nb model dir
config.set_model_from_file(model_dir);
} else {
std::cout << "Unsupport opencl nb model." << std::endl;
exit(1);
// you can give backup cpu nb model instead
// config.set_model_from_file(cpu_nb_model_dir);
}
*/
// NOTE: To load model transformed by model_optimize_tool before
// release/v2.3.0, plese use `set_model_dir` API as listed below.
// config.set_model_dir(model_dir);
......
......@@ -39,8 +39,8 @@ readonly THIRDPARTY_TAR=https://paddle-inference-dist.bj.bcebos.com/PaddleLite/t
readonly workspace=$PWD
# if operating in mac env, we should expand the maximum file num
os_nmae=`uname -s`
if [ ${os_nmae} == "Darwin" ]; then
os_name=`uname -s`
if [ ${os_name} == "Darwin" ]; then
ulimit -n 1024
fi
......
......@@ -21,8 +21,8 @@ USE_ADB_EMULATOR=ON
LITE_WITH_COVERAGE=OFF
# if operating in mac env, we should expand the maximum file num
os_nmae=`uname -s`
if [ ${os_nmae} == "Darwin" ]; then
os_name=`uname -s`
if [ ${os_name} == "Darwin" ]; then
ulimit -n 1024
fi
......
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