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Polish cmake files and runtime apis (#36)

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* Add custom operator for onnxruntime ans fix paddle backend

* Polish cmake files and runtime apis

* Remove copy libraries

* fix some issue

* fix bug

* fix bug
This commit is contained in:
Jason
2022-07-25 08:59:53 +08:00
committed by GitHub
parent 4b681581b1
commit 279c993483
20 changed files with 446 additions and 193 deletions
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114
fastdeploy/fastdeploy_runtime.cc
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@@ -77,23 +77,23 @@ bool CheckModelFormat(const std::string& model_file,
if (model_format == Frontend::PADDLE) {
if (model_file.size() < 8 ||
model_file.substr(model_file.size() - 8, 8) != ".pdmodel") {
FDLogger() << "With model format of Frontend::PADDLE, the model file "
"should ends with `.pdmodel`, but now it's "
<< model_file << std::endl;
FDERROR << "With model format of Frontend::PADDLE, the model file "
"should ends with `.pdmodel`, but now it's "
<< model_file << std::endl;
return false;
}
} else if (model_format == Frontend::ONNX) {
if (model_file.size() < 5 ||
model_file.substr(model_file.size() - 5, 5) != ".onnx") {
FDLogger() << "With model format of Frontend::ONNX, the model file "
"should ends with `.onnx`, but now it's "
<< model_file << std::endl;
FDERROR << "With model format of Frontend::ONNX, the model file "
"should ends with `.onnx`, but now it's "
<< model_file << std::endl;
return false;
}
} else {
FDLogger() << "Only support model format with frontend Frontend::PADDLE / "
"Frontend::ONNX."
<< std::endl;
FDERROR << "Only support model format with frontend Frontend::PADDLE / "
"Frontend::ONNX."
<< std::endl;
return false;
}
return true;
@@ -116,6 +116,101 @@ Frontend GuessModelFormat(const std::string& model_file) {
return Frontend::PADDLE;
}
void RuntimeOption::SetModelPath(const std::string& model_path,
const std::string& params_path,
const std::string& _model_format) {
if (_model_format == "paddle") {
model_file = model_path;
params_file = params_path;
model_format = Frontend::PADDLE;
} else if (_model_format == "onnx") {
model_file = model_path;
model_format = Frontend::ONNX;
} else {
FDASSERT(false, "The model format only can be 'paddle' or 'onnx'.");
}
}
void RuntimeOption::UseGpu(int gpu_id) {
#ifdef WITH_GPU
device = Device::GPU;
device_id = gpu_id;
#else
FDWARNING << "The FastDeploy didn't compile with GPU, will force to use CPU."
<< std::endl;
device = Device::CPU;
#endif
}
void RuntimeOption::UseCpu() { device = Device::CPU; }
void RuntimeOption::SetCpuThreadNum(int thread_num) {
FDASSERT(thread_num > 0, "The thread_num must be greater than 0.");
cpu_thread_num = thread_num;
}
// use paddle inference backend
void RuntimeOption::UsePaddleBackend() {
#ifdef ENABLE_PADDLE_BACKEND
backend = Backend::PDINFER;
#else
FDASSERT(false, "The FastDeploy didn't compile with Paddle Inference.");
#endif
}
// use onnxruntime backend
void RuntimeOption::UseOrtBackend() {
#ifdef ENABLE_ORT_BACKEND
backend = Backend::ORT;
#else
FDASSERT(false, "The FastDeploy didn't compile with OrtBackend.");
#endif
}
void RuntimeOption::UseTrtBackend() {
#ifdef ENABLE_TRT_BACKEND
backend = Backend::TRT;
#else
FDASSERT(false, "The FastDeploy didn't compile with TrtBackend.");
#endif
}
void RuntimeOption::EnablePaddleMKLDNN() { pd_enable_mkldnn = true; }
void RuntimeOption::DisablePaddleMKLDNN() { pd_enable_mkldnn = false; }
void RuntimeOption::SetPaddleMKLDNNCacheSize(int size) {
FDASSERT(size > 0, "Parameter size must greater than 0.");
pd_mkldnn_cache_size = size;
}
void RuntimeOption::SetTrtInputShape(const std::string& input_name,
const std::vector<int32_t>& min_shape,
const std::vector<int32_t>& opt_shape,
const std::vector<int32_t>& max_shape) {
trt_min_shape[input_name].clear();
trt_max_shape[input_name].clear();
trt_opt_shape[input_name].clear();
trt_min_shape[input_name].assign(min_shape.begin(), min_shape.end());
if (opt_shape.size() == 0) {
trt_opt_shape[input_name].assign(min_shape.begin(), min_shape.end());
} else {
trt_opt_shape[input_name].assign(opt_shape.begin(), opt_shape.end());
}
if (max_shape.size() == 0) {
trt_max_shape[input_name].assign(min_shape.begin(), min_shape.end());
} else {
trt_max_shape[input_name].assign(max_shape.begin(), max_shape.end());
}
FDINFO << trt_min_shape[input_name].size() << " "
<< trt_opt_shape[input_name].size() << " "
<< trt_max_shape[input_name].size() << std::endl;
}
void RuntimeOption::EnableTrtFP16() { trt_enable_fp16 = true; }
void RuntimeOption::DisableTrtFP16() { trt_enable_fp16 = false; }
bool Runtime::Init(const RuntimeOption& _option) {
option = _option;
if (option.model_format == Frontend::AUTOREC) {
@@ -229,7 +324,6 @@ void Runtime::CreateTrtBackend() {
trt_option.enable_int8 = option.trt_enable_int8;
trt_option.max_batch_size = option.trt_max_batch_size;
trt_option.max_workspace_size = option.trt_max_workspace_size;
trt_option.fixed_shape = option.trt_fixed_shape;
trt_option.max_shape = option.trt_max_shape;
trt_option.min_shape = option.trt_min_shape;
trt_option.opt_shape = option.trt_opt_shape;