opennn::Loss Class Reference

#include <opennn/training/loss.h>

Classes
struct	EvaluationResult

Public Types
enum class	Error {   MeanSquaredError , MeanAbsoluteError , NormalizedSquaredError , WeightedSquaredError ,   CrossEntropy , CrossEntropy3d , MinkowskiError , Yolo }
enum class	Regularization { L1 , L2 , NoRegularization }

Public Member Functions
	Loss (Network *=nullptr, Dataset *=nullptr)
virtual	~Loss ()=default
const Network *	get_network () const noexcept
Network *	get_network ()
const Dataset *	get_dataset () const noexcept
Dataset *	get_dataset ()
void	set (Network *=nullptr, Dataset *=nullptr)
void	set_network (Network *new_network)
virtual void	set_dataset (Dataset *new_dataset)
string	get_regularization_method () const
void	set_regularization (const string &new_regularization_method)
void	set_regularization (Regularization new_regularization)
void	set_regularization_weight (const float new_regularization_weight)
void	set_minkowski_parameter (const float new_minkowski_parameter)
void	set_normalization_coefficient ()
EvaluationResult	calculate_error (const Batch &, const ForwardPropagation &) const
void	set_error (const Error &)
void	set_error (const string &)
Error	get_error () const noexcept
vector< Index >	get_output_delta_layer_indices () const
bool	output_delta_overwrites_outputs () const
void	back_propagate (const Batch &, ForwardPropagation &, BackPropagation &) const
bool	supports_device_epoch_metrics () const
bool	back_propagate_device_metrics (const Batch &, ForwardPropagation &, BackPropagation &, float *, float *) const
bool	calculate_error_device_metrics (const Batch &, const ForwardPropagation &, float *, float *) const
float	calculate_regularization (const VectorR &) const
float	calculate_regularization (const TensorView &) const
void	add_regularization_gradient (BackPropagation &) const
void	add_regularization_gradient (const TensorView &) const
void	from_JSON (const JsonDocument &)
void	to_JSON (JsonWriter &) const
void	regularization_from_JSON (const JsonDocument &)
void	regularization_to_JSON (JsonWriter &) const
const string &	get_name () const noexcept
void	set_yolo_lambda_noobj (float v)
void	set_yolo_lambda_class (float v)
void	set_yolo_lambda_giou (float v)
void	set_yolo_lambda_dfl (float v)
void	set_yolo_focal_gamma (float v)
void	set_yolo_obj_focal_gamma (float v)

Static Public Member Functions
static const EnumMap< Regularization > &	regularization_map ()
static const string &	regularization_to_string (Regularization regularization)
static Regularization	string_to_regularization (const string &name)

Protected Attributes
Error	error = Error::MeanSquaredError
float	normalization_coefficient = 1.0f
float	positives_weight = 1.0f
float	negatives_weight = 1.0f
Index	weighted_samples_number = 0
float	minkowski_parameter = 1.5f
float	yolo_lambda_giou = 5.0f
float	yolo_lambda_dfl = 1.5f
float	yolo_lambda_noobj = 0.5f
float	yolo_lambda_class = 1.0f
float	yolo_focal_gamma = 0.0f
float	yolo_obj_focal_gamma = 0.0f
Regularization	regularization_method = Regularization::NoRegularization
float	regularization_weight = 0.001f
Network *	network = nullptr
Dataset *	dataset = nullptr
string	name = "Loss"

Member Enumeration Documentation

Error

enum class opennn::Loss::Error

strong

Enumerator
MeanSquaredError
MeanAbsoluteError
NormalizedSquaredError
WeightedSquaredError
CrossEntropy
CrossEntropy3d
MinkowskiError
Yolo

Regularization

enum class opennn::Loss::Regularization

strong

Enumerator
L1
L2
NoRegularization

Constructor & Destructor Documentation

Loss()

opennn::Loss::Loss ( Network * = nullptr, Dataset * = nullptr )

explicit

~Loss()

virtual opennn::Loss::~Loss ( )

virtualdefault

Member Function Documentation

add_regularization_gradient() [1/2]

void opennn::Loss::add_regularization_gradient

(

BackPropagation &

)

const

add_regularization_gradient() [2/2]

void opennn::Loss::add_regularization_gradient

(

const TensorView &

)

const

back_propagate()

void opennn::Loss::back_propagate	(	const Batch &	,
		ForwardPropagation &	,
		BackPropagation &	) const

back_propagate_device_metrics()

bool opennn::Loss::back_propagate_device_metrics	(	const Batch &	,
		ForwardPropagation &	,
		BackPropagation &	,
		float *	,
		float *	) const

calculate_error()

EvaluationResult opennn::Loss::calculate_error	(	const Batch &	,
		const ForwardPropagation &	) const

calculate_error_device_metrics()

bool opennn::Loss::calculate_error_device_metrics	(	const Batch &	,
		const ForwardPropagation &	,
		float *	,
		float *	) const

calculate_regularization() [1/2]

float opennn::Loss::calculate_regularization

(

const TensorView &

)

const

calculate_regularization() [2/2]

float opennn::Loss::calculate_regularization

(

const VectorR &

)

const

from_JSON()

void opennn::Loss::from_JSON

(

const JsonDocument &

)

get_dataset() [1/2]

Dataset * opennn::Loss::get_dataset ( )

inline

get_dataset() [2/2]

const Dataset * opennn::Loss::get_dataset ( ) const

inlinenoexcept

get_error()

Error opennn::Loss::get_error ( ) const

inlinenoexcept

get_name()

const string & opennn::Loss::get_name ( ) const

inlinenoexcept

get_network() [1/2]

Network * opennn::Loss::get_network ( )

inline

get_network() [2/2]

const Network * opennn::Loss::get_network ( ) const

inlinenoexcept

get_output_delta_layer_indices()

vector< Index > opennn::Loss::get_output_delta_layer_indices

(

)

const

get_regularization_method()

string opennn::Loss::get_regularization_method ( ) const

inline

output_delta_overwrites_outputs()

bool opennn::Loss::output_delta_overwrites_outputs

(

)

const

regularization_from_JSON()

void opennn::Loss::regularization_from_JSON

(

const JsonDocument &

)

regularization_map()

static const EnumMap< Regularization > & opennn::Loss::regularization_map ( )

inlinestatic

regularization_to_JSON()

void opennn::Loss::regularization_to_JSON

(

JsonWriter &

)

const

regularization_to_string()

static const string & opennn::Loss::regularization_to_string ( Regularization regularization )

inlinestatic

set()

void opennn::Loss::set	(	Network *	= nullptr,
		Dataset *	= nullptr )

set_dataset()

virtual void opennn::Loss::set_dataset ( Dataset * new_dataset )

inlinevirtual

set_error() [1/2]

void opennn::Loss::set_error

(

const Error &

)

set_error() [2/2]

void opennn::Loss::set_error

(

const string &

)

set_minkowski_parameter()

void opennn::Loss::set_minkowski_parameter ( const float new_minkowski_parameter )

inline

set_network()

void opennn::Loss::set_network ( Network * new_network )

inline

set_normalization_coefficient()

void opennn::Loss::set_normalization_coefficient

(

)

set_regularization() [1/2]

void opennn::Loss::set_regularization ( const string & new_regularization_method )

inline

set_regularization() [2/2]

void opennn::Loss::set_regularization ( Regularization new_regularization )

inline

set_regularization_weight()

void opennn::Loss::set_regularization_weight ( const float new_regularization_weight )

inline

set_yolo_focal_gamma()

void opennn::Loss::set_yolo_focal_gamma ( float v )

inline

set_yolo_lambda_class()

void opennn::Loss::set_yolo_lambda_class ( float v )

inline

set_yolo_lambda_dfl()

void opennn::Loss::set_yolo_lambda_dfl ( float v )

inline

set_yolo_lambda_giou()

void opennn::Loss::set_yolo_lambda_giou ( float v )

inline

set_yolo_lambda_noobj()

void opennn::Loss::set_yolo_lambda_noobj ( float v )

inline

set_yolo_obj_focal_gamma()

void opennn::Loss::set_yolo_obj_focal_gamma ( float v )

inline

string_to_regularization()

static Regularization opennn::Loss::string_to_regularization ( const string & name )

inlinestatic

supports_device_epoch_metrics()

bool opennn::Loss::supports_device_epoch_metrics

(

)

const

to_JSON()

void opennn::Loss::to_JSON

(

JsonWriter &

)

const

Member Data Documentation

dataset

Dataset* opennn::Loss::dataset = nullptr

protected

error

Error opennn::Loss::error = Error::MeanSquaredError

protected

minkowski_parameter

float opennn::Loss::minkowski_parameter = 1.5f

protected

name

string opennn::Loss::name = "Loss"

protected

negatives_weight

float opennn::Loss::negatives_weight = 1.0f

protected

network

Network* opennn::Loss::network = nullptr

protected

normalization_coefficient

float opennn::Loss::normalization_coefficient = 1.0f

protected

positives_weight

float opennn::Loss::positives_weight = 1.0f

protected

regularization_method

Regularization opennn::Loss::regularization_method = Regularization::NoRegularization

protected

regularization_weight

float opennn::Loss::regularization_weight = 0.001f

protected

weighted_samples_number

Index opennn::Loss::weighted_samples_number = 0

protected

yolo_focal_gamma

float opennn::Loss::yolo_focal_gamma = 0.0f

protected

yolo_lambda_class

float opennn::Loss::yolo_lambda_class = 1.0f

protected

yolo_lambda_dfl

float opennn::Loss::yolo_lambda_dfl = 1.5f

protected

yolo_lambda_giou

float opennn::Loss::yolo_lambda_giou = 5.0f

protected

yolo_lambda_noobj

float opennn::Loss::yolo_lambda_noobj = 0.5f

protected

yolo_obj_focal_gamma

float opennn::Loss::yolo_obj_focal_gamma = 0.0f

protected