opennn::LevenbergMarquardt Class Reference

#include <opennn/training/levenberg_marquardt.h>

Inheritance diagram for opennn::LevenbergMarquardt:

Public Types
enum	DataSlot { ParameterUpdate }
Public Types inherited from opennn::Optimizer
using	StoppingCondition = opennn::StoppingCondition

Public Member Functions
	LevenbergMarquardt (Loss *=nullptr)
void	set_damping_parameter_factor (const float)
void	set_minimum_loss_decrease (const float new_minimum_loss_decrease)
TrainingResult	train () override
void	from_JSON (const JsonDocument &) override
void	to_JSON (JsonWriter &) const override
Public Member Functions inherited from opennn::Optimizer
	Optimizer (Loss *=nullptr)
virtual	~Optimizer ()
const Loss *	get_loss () const noexcept
bool	get_display () const noexcept
void	set (Loss *new_loss)
virtual void	set_display (bool new_display)
void	set_display_period (const Index new_display_period)
void	set_workers_number (int new_workers_number)
void	set_cuda_graph (bool enabled)
bool	get_cuda_graph_capture_failed () const noexcept
void	set_shuffle (bool enabled)
void	set_batch_pool_size (int size)
void	set_maximum_epochs (const Index new_maximum_epochs)
Index	get_maximum_epochs () const noexcept
void	set_maximum_time (const float new_maximum_time)
void	set_loss_goal (const float new_loss_goal)
void	set_maximum_validation_failures (const Index new_maximum_validation_failures)
void	set_validation_period (const Index n)
void	set_restore_best (bool enabled)
void	set_gradient_clip_norm (const float new_clip)
void	set_joint_gradient_arena (bool enabled) noexcept
Index	get_batch_size () const noexcept
void	set_batch_size (const Index new_batch_size)
virtual void	configure_for_task (NetworkTask)
Index	get_maximum_batch_size () const
const string &	get_name () const noexcept
void	save (const filesystem::path &) const
void	load (const filesystem::path &)

Additional Inherited Members
Public Attributes inherited from opennn::Optimizer
function< void(Index, float, float, Network *)>	post_epoch_callback
function< void(Network *)>	post_batch_callback
function< void(Index, float)>	post_best_callback
Protected Types inherited from opennn::Optimizer
enum class	UpdateMode { Standard , Capturable }
Protected Member Functions inherited from opennn::Optimizer
void	set_names ()
void	prepare_training_artifacts ()
Index	get_epoch_budget () const noexcept
optional< StoppingCondition >	find_stopping_condition (const EpochReport &, float minimum_loss_decrease=-MAX) const
void	close_training_result (TrainingResult &, const EpochReport &, bool has_validation) const
void	update_best_parameters (Network *, float, Index, Index &, BestModelSnapshot &)
void	restore_best_parameters (Network *, TrainingResult &, const BestModelSnapshot &)
void	write_common_json (JsonWriter &) const
void	read_common_json (const Json *)
void	setup_device_training ()
void	teardown_device_training ()
void	warmup_device_training (TrainingContext &, ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &, TrainingSession &, OptimizerData &, ForwardPropagation *validation_forward_propagation=nullptr, ThreadSafeQueue< Batch * > *validation_empty_queue=nullptr, const vector< vector< Index > > *validation_batches=nullptr)
void	prefetch_batch (Batch &)
void	sync_device (bool on_gpu, bool has_recurrent_layers, TrainingSession &)
bool	should_display (Index epoch) const noexcept
void	display_epoch_results (Index epoch, float training_error, float training_accuracy, float validation_error, float validation_accuracy, bool has_validation, bool validation_fresh, bool is_token_cross_entropy, float elapsed_time) const
void	setup_batch_pools (BatchPools &pools, Dataset &dataset, Network &network, Index training_batch_size, Index validation_batch_size, bool has_validation, TrainingSession &training_session)
unique_ptr< BatchPrefetchSession >	start_batch_prefetch (ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &, FillMode, WorkerProfileCounters *profile_counters=nullptr)
int	get_batch_pool_size (const Network &) const
Loss::EvaluationResult	run_epoch_loop (EpochLoopContext &)
void	prepare_full_batch_training (FullBatchContext &, const char *banner)
TrainingResult	train_full_batch (FullBatchContext &, const FullBatchHooks &)
virtual string	get_display_name () const
virtual void	setup_optimizer_data (OptimizerData &, Index, Device)
virtual void	update_parameters (BackPropagation &, OptimizerData &, UpdateMode=UpdateMode::Standard)
virtual bool	supports_cuda_graph () const noexcept
bool	network_has_active_dropout () const
bool	can_use_cuda_graph () const
virtual void	on_epoch_begin (Index, OptimizerData &)
bool	uses_joint_gradient_arena () const noexcept
Loss::EvaluationResult	run_graph_epoch (TrainingSession &, OptimizerData &, ForwardPropagation &, BackPropagation &, ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &)
Loss::EvaluationResult	train_epoch (TrainingContext &, ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &, TrainingSession &, OptimizerData &)
Loss::EvaluationResult	evaluate_epoch (ForwardPropagation &, ThreadSafeQueue< Batch * > &, const vector< vector< Index > > &, const FeatureSelection &, TrainingSession &)
Static Protected Member Functions inherited from opennn::Optimizer
static void	clip_gradient_norm (BackPropagation &, float)
Protected Attributes inherited from opennn::Optimizer
Loss *	loss = nullptr
float	training_loss_goal = 0.0f
Index	maximum_validation_failures = numeric_limits<Index>::max()
Index	validation_period = 1
float	gradient_clip_norm = 0.0f
bool	joint_gradient_arena = false
bool	restore_best = true
Index	maximum_epochs = 10000
Index	batch_size = 0
float	maximum_time = 360000.0f
Index	display_period = 10
bool	display = true
bool	shuffle_samples = true
int	batch_pool_size_override = 0
int	workers_number = default_workers_number
bool	use_cuda_graph = false
bool	cuda_graph_capture_failed = false
string	name
Static Protected Attributes inherited from opennn::Optimizer
static const int	default_workers_number

Member Enumeration Documentation

DataSlot

enum opennn::LevenbergMarquardt::DataSlot

Enumerator
ParameterUpdate

Constructor & Destructor Documentation

LevenbergMarquardt()

opennn::LevenbergMarquardt::LevenbergMarquardt ( Loss * = nullptr )

explicit

Member Function Documentation

from_JSON()

void opennn::LevenbergMarquardt::from_JSON ( const JsonDocument & )

overridevirtual

Reimplemented from opennn::Optimizer.

set_damping_parameter_factor()

void opennn::LevenbergMarquardt::set_damping_parameter_factor

(

const float

)

set_minimum_loss_decrease()

void opennn::LevenbergMarquardt::set_minimum_loss_decrease ( const float new_minimum_loss_decrease )

inline

to_JSON()

void opennn::LevenbergMarquardt::to_JSON ( JsonWriter & ) const

overridevirtual

Reimplemented from opennn::Optimizer.

train()

TrainingResult opennn::LevenbergMarquardt::train ( )

overridevirtual

Reimplemented from opennn::Optimizer.