apps/FastDeploy
1
0
Fork 0
mirror of https://github.com/PaddlePaddle/FastDeploy.git synced 2025-10-20 15:25:22 +08:00
Code Issues Actions 6 Packages Projects Releases Wiki Activity

[Other] Optimize code style (#1032)

Browse Source 
* Optimize code

* optimize code

* optimize code

* fix compile error
This commit is contained in:
Jason
2023-01-03 19:54:12 +08:00
committed by GitHub
parent ab49b41080
commit f51697d745
31 changed files with 594 additions and 580 deletions
Download Patch File Download Diff File Expand all files Collapse all files

38
fastdeploy/backends/ort/ort_backend.cc
View File

@@ -16,8 +16,8 @@
#include <memory>
#include "fastdeploy/backends/ort/ops/multiclass_nms.h"
#include "fastdeploy/backends/ort/ops/adaptive_pool2d.h"
#include "fastdeploy/backends/ort/ops/multiclass_nms.h"
#include "fastdeploy/backends/ort/utils.h"
#include "fastdeploy/core/float16.h"
#include "fastdeploy/utils/utils.h"
@@ -64,7 +64,7 @@ void OrtBackend::BuildOption(const OrtBackendOption& option) {
} else {
OrtCUDAProviderOptions cuda_options;
cuda_options.device_id = option.gpu_id;
if(option.external_stream_) {
if (option.external_stream_) {
cuda_options.has_user_compute_stream = 1;
cuda_options.user_compute_stream = option.external_stream_;
}
@@ -91,11 +91,11 @@ bool OrtBackend::InitFromPaddle(const std::string& model_file,
strcpy(ops[0].export_op_name, "MultiClassNMS");
strcpy(ops[1].op_name, "pool2d");
strcpy(ops[1].export_op_name, "AdaptivePool2d");
if (!paddle2onnx::Export(model_file.c_str(), params_file.c_str(),
&model_content_ptr, &model_content_size, 11, true,
verbose, true, true, true, ops.data(),
2, "onnxruntime", nullptr, 0, "", &save_external)) {
verbose, true, true, true, ops.data(), 2,
"onnxruntime", nullptr, 0, "", &save_external)) {
FDERROR << "Error occured while export PaddlePaddle to ONNX format."
<< std::endl;
return false;
@@ -105,11 +105,11 @@ bool OrtBackend::InitFromPaddle(const std::string& model_file,
model_content_ptr + model_content_size);
delete[] model_content_ptr;
model_content_ptr = nullptr;
if(save_external){
if (save_external) {
std::string model_file_name = "model.onnx";
std::fstream f(model_file_name, std::ios::out);
FDASSERT(f.is_open(), "Can not open file: %s to save model.",
model_file_name.c_str());
model_file_name.c_str());
f << onnx_model_proto;
f.close();
return InitFromOnnx(model_file_name, option, false);
@@ -182,7 +182,7 @@ bool OrtBackend::InitFromOnnx(const std::string& model_file,
}
void OrtBackend::OrtValueToFDTensor(const Ort::Value& value, FDTensor* tensor,
const std::string& name, bool copy_to_fd) {
const std::string& name, bool copy_to_fd) {
const auto info = value.GetTensorTypeAndShapeInfo();
const auto data_type = info.GetElementType();
size_t numel = info.GetElementCount();
@@ -216,15 +216,13 @@ void OrtBackend::OrtValueToFDTensor(const Ort::Value& value, FDTensor* tensor,
memcpy(tensor->MutableData(), value_ptr, numel);
} else {
tensor->name = name;
tensor->SetExternalData(
shape, dtype,
const_cast<void*>(value_ptr), Device::CPU);
tensor->SetExternalData(shape, dtype, const_cast<void*>(value_ptr),
Device::CPU);
}
}
bool OrtBackend::Infer(std::vector<FDTensor>& inputs,
std::vector<FDTensor>* outputs,
bool copy_to_fd) {
std::vector<FDTensor>* outputs, bool copy_to_fd) {
if (inputs.size() != inputs_desc_.size()) {
FDERROR << "[OrtBackend] Size of the inputs(" << inputs.size()
<< ") should keep same with the inputs of this model("
@@ -256,8 +254,8 @@ bool OrtBackend::Infer(std::vector<FDTensor>& inputs,
std::vector<Ort::Value> ort_outputs = binding_->GetOutputValues();
outputs->resize(ort_outputs.size());
for (size_t i = 0; i < ort_outputs.size(); ++i) {
OrtValueToFDTensor(ort_outputs[i], &((*outputs)[i]),
outputs_desc_[i].name, copy_to_fd);
OrtValueToFDTensor(ort_outputs[i], &((*outputs)[i]), outputs_desc_[i].name,
copy_to_fd);
}
return true;
@@ -310,11 +308,13 @@ void OrtBackend::InitCustomOperators() {
if (custom_operators_.size() == 0) {
MultiClassNmsOp* multiclass_nms = new MultiClassNmsOp{};
custom_operators_.push_back(multiclass_nms);
if(option_.use_gpu){
AdaptivePool2dOp* adaptive_pool2d = new AdaptivePool2dOp{"CUDAExecutionProvider"};
if (option_.use_gpu) {
AdaptivePool2dOp* adaptive_pool2d =
new AdaptivePool2dOp{"CUDAExecutionProvider"};
custom_operators_.push_back(adaptive_pool2d);
}else{
AdaptivePool2dOp* adaptive_pool2d = new AdaptivePool2dOp{"CPUExecutionProvider"};
} else {
AdaptivePool2dOp* adaptive_pool2d =
new AdaptivePool2dOp{"CPUExecutionProvider"};
custom_operators_.push_back(adaptive_pool2d);
}
}