apollo::perception::inference::ObstacleDetector类 参考

#include <libtorch_obstacle_detector.h>

类 apollo::perception::inference::ObstacleDetector 继承关系图:

apollo::perception::inference::ObstacleDetector 的协作图:

Public 成员函数
	ObstacleDetector (const std::string &net_file, const std::string &model_file, const std::vector< std::string > &outputs)
	ObstacleDetector (const std::string &net_file, const std::string &model_file, const std::vector< std::string > &outputs, const std::vector< std::string > &inputs)
virtual	~ObstacleDetector ()
bool	Init (const std::map< std::string, std::vector< int > > &shapes) override
void	Infer () override
base::BlobPtr< float >	get_blob (const std::string &name) override
Public 成员函数 继承自 apollo::perception::inference::Inference
	Inference ()=default
virtual	~Inference ()=default
virtual void	SetStream (cudaStream_t stream)
void	set_max_batch_size (const int &batch_size)
void	set_gpu_id (const int &gpu_id)
void	set_model_info (const std::string &proto_file, const std::vector< std::string > &net_input_names, const std::vector< std::string > &net_output_names)

Protected 成员函数
bool	shape (const std::string &name, std::vector< int > *res)

Protected 属性
torch::jit::script::Module	net_
Protected 属性 继承自 apollo::perception::inference::Inference
int	max_batch_size_ = 1
int	gpu_id_ = 0
std::string	proto_file_ = ""
std::vector< std::string >	net_output_names_
std::vector< std::string >	net_input_names_

详细描述

在文件 libtorch_obstacle_detector.h 第 34 行定义.

构造及析构函数说明

ObstacleDetector() [1/2]

apollo::perception::inference::ObstacleDetector::ObstacleDetector	(	const std::string &	net_file,
		const std::string &	model_file,
		const std::vector< std::string > &	outputs
	)

在文件 libtorch_obstacle_detector.cc 第 28 行定义.

    : net_file_(net_file), model_file_(model_file), output_names_(outputs) {}

ObstacleDetector() [2/2]

apollo::perception::inference::ObstacleDetector::ObstacleDetector	(	const std::string &	net_file,
		const std::string &	model_file,
		const std::vector< std::string > &	outputs,
		const std::vector< std::string > &	inputs
	)

在文件 libtorch_obstacle_detector.cc 第 33 行定义.

    : net_file_(net_file),
      model_file_(model_file),
      output_names_(outputs),
      input_names_(inputs) {}

~ObstacleDetector()

virtual apollo::perception::inference::ObstacleDetector::~ObstacleDetector ( )

inlinevirtual

在文件 libtorch_obstacle_detector.h 第 43 行定义.

{}

成员函数说明

get_blob()

std::shared_ptr< Blob< float > > apollo::perception::inference::ObstacleDetector::get_blob ( const std::string &  name )

overridevirtual

实现了 apollo::perception::inference::Inference.

在文件 libtorch_obstacle_detector.cc 第 96 行定义.

                           {
  auto iter = blobs_.find(name);
  if (iter == blobs_.end()) {
    return nullptr;
  }
  return iter->second;
}

Infer()

void apollo::perception::inference::ObstacleDetector::Infer ( )

overridevirtual

实现了 apollo::perception::inference::Inference.

在文件 libtorch_obstacle_detector.cc 第 115 行定义.

                             {
  torch::Device device(device_type_, device_id_);
  auto blob = blobs_[input_names_[0]];
  auto input_K = blobs_[input_names_[1]];
  auto input_ratio = blobs_[input_names_[2]];
 
  torch::Tensor tensor_image = torch::from_blob(
      blob->data()->mutable_gpu_data(),
      {blob->shape(0), blob->shape(1), blob->shape(2), blob->shape(3)},
      torch::kFloat32);
  torch::Tensor tensor_K = torch::from_blob(
      input_K->data()->mutable_cpu_data(),
      {input_K->shape(0), input_K->shape(1), input_K->shape(2)},
      torch::kFloat32);
  torch::Tensor tensor_ratio = torch::from_blob(
      input_ratio->data()->mutable_cpu_data(),
      {input_ratio->shape(0), input_ratio->shape(1)}, torch::kFloat32);
 
  std::vector<torch::jit::IValue> torch_inputs;
  torch_inputs.push_back(tensor_image.to(device));
  torch_inputs.push_back(
      std::make_tuple(tensor_K.to(device), tensor_ratio.to(device)));
 
  AINFO << "Start to do inference";
  auto outputs = net_.forward(torch_inputs).toTuple()->elements();
  AINFO << "Finished inference";
 
  for (size_t i = 0; i < output_names_.size(); ++i) {
    auto blob = get_blob(output_names_[i]);
    if (blob != nullptr) {
      torch::Tensor output_tensor = outputs[i].toTensor();
      std::vector<int64_t> output_size_ = output_tensor.sizes().vec();
      std::vector<int> output_size(begin(output_size_), end(output_size_));
      blob->Reshape(output_size);
      blob->set_gpu_data(output_tensor.data_ptr<float>());
    }
  }
}

Init()

bool apollo::perception::inference::ObstacleDetector::Init ( const std::map< std::string, std::vector< int > > &  shapes )

overridevirtual

实现了 apollo::perception::inference::Inference.

在文件 libtorch_obstacle_detector.cc 第 42 行定义.

                                                     {
  if (gpu_id_ >= 0) {
    device_type_ = torch::kCUDA;
    device_id_ = gpu_id_;
  } else {
    device_type_ = torch::kCPU;
  }
 
  for (const auto &name : output_names_) {
    auto iter = shapes.find(name);
    if (iter != shapes.end()) {
      auto blob = std::make_shared<Blob<float>>(iter->second);
      blobs_.emplace(name, blob);
    }
  }
 
  for (const auto &name : input_names_) {
    auto iter = shapes.find(name);
    if (iter != shapes.end()) {
      auto blob = std::make_shared<Blob<float>>(iter->second);
      blobs_.emplace(name, blob);
    }
  }
 
  // Load model without grad, equal to torch.no_grad()
  // torch::NoGradGuard no_grad;
  // Init net
  torch::Device device(device_type_, device_id_);
  net_ = torch::jit::load(model_file_, device);
  net_.eval();
 
  // run a fake inference at init time as first inference is relative slow
  int height_ = blobs_[input_names_[0]]->shape(1);
  int width_ = blobs_[input_names_[0]]->shape(2);
  torch::Tensor input_feature_tensor = torch::zeros({1, 3, height_, width_});
  std::array<float, 2> down_ratio{8.0f, 8.0f};
  torch::Tensor tensor_downratio = torch::from_blob(down_ratio.data(), {1, 2});
  std::array<float, 9> K{1.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 1.0f};
  torch::Tensor tensor_K = torch::from_blob(K.data(), {1, 3, 3});
 
  std::vector<torch::jit::IValue> torch_inputs;
  torch_inputs.push_back(input_feature_tensor.to(device));
  torch_inputs.push_back(
      std::make_tuple(tensor_K.to(device), tensor_downratio.to(device)));
  auto torch_output_tensor = net_.forward(torch_inputs).toTuple()->elements();
  if (torch_output_tensor[0].toTensor().requires_grad()) {
    AWARN << "Require grad";
  }
 
  emptyCache();
  return true;
}

shape()

bool apollo::perception::inference::ObstacleDetector::shape ( const std::string &  name, std::vector< int > *  res  )

protected

在文件 libtorch_obstacle_detector.cc 第 105 行定义.

                                                                       {
  auto blob = get_blob(name);
  if (blob == nullptr) {
    return false;
  }
 
  *res = blob->shape();
  return true;
}

类成员变量说明

net_

torch::jit::script::Module apollo::perception::inference::ObstacleDetector::net_

protected

在文件 libtorch_obstacle_detector.h 第 52 行定义.

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该类的文档由以下文件生成:

• modules/perception/common/inference/onnx/libtorch_obstacle_detector.h
• modules/perception/common/inference/onnx/libtorch_obstacle_detector.cc