apollo::prediction::network 命名空间参考

apollo::prediction::network 更多...

类
class	Activation
	Activation is an activation network layer. 更多...
class	AvgPool1d
	AvgPool1d is the average Pool 1d network layer. 更多...
class	BatchNormalization
class	Concatenate
	concatenates a vector of inputs, return a single matrix. 更多...
class	Conv1d
	Conv1d is the convolution 1d network layer. 更多...
class	Dense
	Dense is the forward fully connected network layer. 更多...
class	Flatten
	network layer to flatten a matrix into vector. 更多...
class	Input
	the input layer for a network, which specified the shape of input matrix 更多...
class	Layer
	Layer is a base class for specific network layers It contains a pure virtual function Run which must be implemented in derived class 更多...
class	LSTM
	Long-Short Term Memory unit - Hochreiter 1997. 更多...
class	MaxPool1d
	MaxPool1d is the max Pool 1d network layer. 更多...
class	NetModel
	NetModel is a base class for specific network model It contains a pure virtual function Run which must be implemented in derived class 更多...
class	RnnModel
	RnnModel is a derived class from NetModel, it has a specific layers structure. 更多...

函数
float	sigmoid (const float x)
	sigmoid function: f(x) = 1 / (1 + exp(-x))
float	tanh (const float x)
	hyperbolic tangent function: f(x) = (1 + exp(-2x)) / (1 - exp(-2x))
float	linear (const float x)
	linear function: f(x) = x
float	hard_sigmoid (const float x)
	"hard" sigmoid function: | 0.0 x in (-oo, 0) f(x) = | 0.2x + 0.5 x in [0, 2.5] | 1.0 x in (2.5, +oo)
float	relu (const float x)
	relu function: | 0.0 x in (-oo, 0.0) f(x) = | | x x in [0.0, +oo)
Eigen::MatrixXf	FlattenMatrix (const Eigen::MatrixXf &matrix)
	flatten a matrix to a row vector
std::function< float(float)>	serialize_to_function (const std::string &str)
	translate a string into a network activation function
bool	LoadTensor (const TensorParameter &tensor_pb, Eigen::MatrixXf *matrix)
	load matrix value from a protobuf message
bool	LoadTensor (const TensorParameter &tensor_pb, Eigen::VectorXf *vector)
	load vector value from a protobuf message
bool	LoadTensor (const TensorParameter &tensor_pb, std::vector< Eigen::MatrixXf > *const tensor3d)
	load matrix value from a protobuf message

详细描述

apollo::prediction::network

函数说明

FlattenMatrix()

Eigen::MatrixXf apollo::prediction::network::FlattenMatrix

(

const Eigen::MatrixXf &

matrix

)

flatten a matrix to a row vector

参数

Input

matrix

返回

Flattened matrix

在文件 net_util.cc 第 40 行定义.

                                                         {
  CHECK_GT(matrix.rows(), 0);
  CHECK_GT(matrix.cols(), 0);
  int output_size = static_cast<int>(matrix.rows() * matrix.cols());
  Eigen::MatrixXf output_matrix;
  output_matrix.resize(1, output_size);
  int output_index = 0;
  for (int i = 0; i < matrix.rows(); ++i) {
    for (int j = 0; j < matrix.cols(); ++j) {
      output_matrix(0, output_index) = matrix(i, j);
      ++output_index;
    }
  }
  return output_matrix;
}

hard_sigmoid()

float apollo::prediction::network::hard_sigmoid

(

const float

x

)

"hard" sigmoid function: | 0.0 x in (-oo, 0) f(x) = | 0.2x + 0.5 x in [0, 2.5] | 1.0 x in (2.5, +oo)

在文件 net_util.cc 第 33 行定义.

                                  {
  const float z = 0.2f * x + 0.5f;
  return z <= 0.0f ? 0.0f : (z <= 1.0f ? z : 1.0f);
}

linear()

float apollo::prediction::network::linear

(

const float

x

)

linear function: f(x) = x

在文件 net_util.cc 第 31 行定义.

{ return x; }

LoadTensor() [1/3]

bool apollo::prediction::network::LoadTensor	(	const TensorParameter &	tensor_pb,
		Eigen::MatrixXf *	matrix
	)

load matrix value from a protobuf message

参数

protobuf	message in the form of TensorParameter
Eigen::MatrixXf	will be returned

返回

True if load data successively, otherwise False

在文件 net_util.cc 第 66 行定义.

                                                                         {
  if (tensor_pb.data().empty() || tensor_pb.shape().empty()) {
    AERROR << "Fail to load the necessary fields!";
    return false;
  }
  if (tensor_pb.shape_size() < 2) {
    ADEBUG << "Load tensor size: (1, " << tensor_pb.shape(0) << ")";
    matrix->resize(1, tensor_pb.shape(0));
    for (int i = 0; i < tensor_pb.shape(0); ++i) {
      (*matrix)(0, i) = static_cast<float>(tensor_pb.data(i));
    }
    return true;
  }
  ADEBUG << "Load tensor size: (" << tensor_pb.shape(0) << ", "
         << tensor_pb.shape(1) << ")";
  CHECK_EQ(tensor_pb.shape_size(), 2);
  matrix->resize(tensor_pb.shape(0), tensor_pb.shape(1));
  for (int i = 0; i < tensor_pb.shape(0); ++i) {
    for (int j = 0; j < tensor_pb.shape(1); ++j) {
      (*matrix)(i, j) =
          static_cast<float>(tensor_pb.data(i * tensor_pb.shape(1) + j));
    }
  }
  return true;
}

LoadTensor() [2/3]

bool apollo::prediction::network::LoadTensor	(	const TensorParameter &	tensor_pb,
		Eigen::VectorXf *	vector
	)

load vector value from a protobuf message

参数

protobuf	message in the form of TensorParameter
Eigen::VectorXf	will be returned

返回

True if load data successively, otherwise False

在文件 net_util.cc 第 92 行定义.

                                                                         {
  if (tensor_pb.data().empty() || tensor_pb.shape().empty()) {
    AERROR << "Fail to load the necessary fields!";
    return false;
  }
  ADEBUG << "Load tensor size: (" << tensor_pb.shape(0) << ", 1)";
  CHECK_EQ(tensor_pb.shape_size(), 1);
  if (tensor_pb.shape_size() == 1) {
    vector->resize(tensor_pb.shape(0));
    for (int i = 0; i < tensor_pb.shape(0); ++i) {
      (*vector)(i) = static_cast<float>(tensor_pb.data(i));
    }
  }
  return true;
}

LoadTensor() [3/3]

bool apollo::prediction::network::LoadTensor	(	const TensorParameter &	tensor_pb,
		std::vector< Eigen::MatrixXf > *const	tensor3d
	)

load matrix value from a protobuf message

参数

protobuf	message in the form of TensorParameter
vector	of Eigen::MatrixXf will be returned

返回

True if load data successively, otherwise False

在文件 net_util.cc 第 108 行定义.

                                                          {
  if (tensor_pb.data().empty() || tensor_pb.shape_size() != 3) {
    AERROR << "Fail to load the necessary fields!";
    return false;
  }
  int num_depth = tensor_pb.shape(0);
  int num_row = tensor_pb.shape(1);
  int num_col = tensor_pb.shape(2);
  CHECK_EQ(tensor_pb.data_size(), num_depth * num_row * num_col);
  int tensor_pb_index = 0;
  for (int k = 0; k < num_depth; ++k) {
    Eigen::MatrixXf matrix = Eigen::MatrixXf::Zero(num_row, num_col);
    for (int i = 0; i < num_row; ++i) {
      for (int j = 0; j < num_col; ++j) {
        matrix(i, j) = tensor_pb.data(tensor_pb_index);
        ++tensor_pb_index;
      }
    }
    tensor3d->push_back(matrix);
  }
  CHECK_EQ(tensor_pb_index, num_depth * num_row * num_col);
  return true;
}

relu()

float apollo::prediction::network::relu

(

const float

x

)

relu function: | 0.0 x in (-oo, 0.0) f(x) = | | x x in [0.0, +oo)

在文件 net_util.cc 第 38 行定义.

{ return (x > 0.0f) ? x : 0.0f; }

serialize_to_function()

std::function< float(float)> apollo::prediction::network::serialize_to_function

(

const std::string &

str

)

translate a string into a network activation function

参数

string

返回

activation function map to the string

在文件 net_util.cc 第 56 行定义.

                                                                      {
  static const std::unordered_map<std::string, std::function<float(float)>>
      func_map({{"linear", linear},
                {"tanh", tanh},
                {"sigmoid", sigmoid},
                {"hard_sigmoid", hard_sigmoid},
                {"relu", relu}});
  return func_map.at(str);
}

sigmoid()

float apollo::prediction::network::sigmoid

(

const float

x

)

sigmoid function: f(x) = 1 / (1 + exp(-x))

在文件 net_util.cc 第 27 行定义.

{ return 1.0f / (1.0f + std::exp(-x)); }

tanh()

float apollo::prediction::network::tanh

(

const float

x

)

hyperbolic tangent function: f(x) = (1 + exp(-2x)) / (1 - exp(-2x))

在文件 net_util.cc 第 29 行定义.

{ return std::tanh(x); }