#include </home/runner/work/iganet/iganet/include/iganet/net/iganet.hpp>

Inheritance diagram for iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >:

Public Types
using	Base = IgABase< Inputs, Outputs, CollPts >
	Base type.

using	optimizer_options_type = optimizer_options_type< Optimizer >::type
	Type of the optimizer options.

using	optimizer_type = Optimizer
	Type of the optimizer.

using	value_type = Base::value_type
	Value type.

Public Member Functions
	IgANet (const IgANetOptions &defaults={}, iganet::Options< typename Base::value_type > options=iganet::Options< typename Base::value_type >{})
	Default constructor.

template<typename NumCoeffs >
	IgANet (const std::vector< int64_t > &layers, const std::vector< std::vector< std::any > > &activations, const NumCoeffs &numCoeffs, enum init init=init::greville, IgANetOptions defaults={}, iganet::Options< typename Base::value_type > options=iganet::Options< typename Base::value_type >{})
	Constructor: number of layers, activation functions, and number of spline coefficients (same for all inputs and outputs).

template<typename NumCoeffsInputs , typename NumCoeffsOutputs >
	IgANet (const std::vector< int64_t > &layers, const std::vector< std::vector< std::any > > &activations, const NumCoeffsInputs &numCoeffsInputs, const NumCoeffsOutputs &numCoeffsOutputs, enum init init=init::greville, IgANetOptions defaults={}, iganet::Options< typename Base::value_type > options=iganet::Options< typename Base::value_type >{})
	Constructor: number of layers, activation functions, and number of spline coefficients (same for all inputs and outputs).

virtual bool	epoch (int64_t)=0
	Initializes epoch.

void	eval ()
	Evaluate IgANet.

constexpr auto &	inputs ()
	Returns a non-constant reference to the tuple of input objects.

constexpr const auto &	inputs () const
	Returns a constant reference to the tuple of input objects.

virtual void	inputs (const torch::Tensor &tensor)
	Attaches the given tensor to the inputs.

virtual torch::Tensor	inputs (int64_t epoch) const
	Returns the network inputs as tensor.

void	load (const std::string &filename, const std::string &key="iganet")
	Loads the IgANet from file.

virtual torch::Tensor	loss (const torch::Tensor &, int64_t)=0
	Computes the loss function.

torch::OrderedDict< std::string, torch::Tensor >	named_parameters () const noexcept
	Returns a constant reference to the named parameters of the IgANet object.

IgANetGenerator< typename Base::value_type > &	net ()
	Returns a non-constant reference to the IgANet generator.

const IgANetGenerator< typename Base::value_type > &	net () const
	Returns a constant reference to the IgANet generator.

std::size_t	nparameters () const noexcept
	Returns the total number of parameters of the IgANet object.

bool	operator!= (const IgANet &other) const
	Returns true if both IgANet objects are different.

bool	operator== (const IgANet &other) const
	Returns true if both IgANet objects are the same.

optimizer_type &	optimizer ()
	Returns a non-constant reference to the optimizer.

const optimizer_type &	optimizer () const
	Returns a constant reference to the optimizer.

optimizer_options_type &	optimizerOptions (std::size_t param_group=0)
	Returns a non-constant reference to the optimizer options.

const optimizer_options_type &	optimizerOptions (std::size_t param_group=0) const
	Returns a constant reference to the optimizer options.

void	optimizerOptionsReset (const optimizer_options_type &options)
	Resets the optimizer options.

void	optimizerOptionsReset (const optimizer_options_type &options, std::size_t param_group)
	Resets the optimizer options.

void	optimizerOptionsReset (optimizer_options_type &&options)
	Resets the optimizer options.

void	optimizerOptionsReset (optimizer_options_type &&options, std::size_t param_group)
	Resets the optimizer options.

void	optimizerReset (bool resetOptions=true)
	Resets the optimizer.

void	optimizerReset (const optimizer_options_type &optimizerOptions)
	Resets the optimizer.

auto &	options ()
	Returns a non-constant reference to the options structure.

const auto &	options () const
	Returns a constant reference to the options structure.

constexpr auto &	outputs ()
	Returns a non-constant reference to the tuple of output objects.

constexpr const auto &	outputs () const
	Returns a constant reference to the tuple of output objects.

virtual void	outputs (const torch::Tensor &tensor)
	Attaches the given tensor to the outputs.

virtual torch::Tensor	outputs (int64_t epoch) const
	Returns the network outputs as tensor.

std::vector< torch::Tensor >	parameters () const noexcept
	Returns a constant reference to the parameters of the IgANet object.

void	pretty_print (std::ostream &os) const noexcept override
	Returns a string representation of the IgANet object.

torch::serialize::InputArchive &	read (torch::serialize::InputArchive &archive, const std::string &key="iganet")
	Loads the IgANet from a torch::serialize::InputArchive object.

torch::Tensor &	register_parameter (std::string name, torch::Tensor tensor, bool requires_grad=true)
	Registers a parameter.

void	save (const std::string &filename, const std::string &key="iganet") const
	Saves the IgANet to file.

nlohmann::json	to_json () const override
	Returns the IgANet object as JSON object.

virtual void	train ()
	Trains the IgANet.

template<typename DataLoader >
void	train (DataLoader &loader)
	Trains the IgANet.

torch::serialize::OutputArchive &	write (torch::serialize::OutputArchive &archive, const std::string &key="iganet") const
	Writes the IgANet into a torch::serialize::OutputArchive object.

Protected Attributes
IgANetGenerator< typename Base::value_type >	net_
	IgANet generator.

std::unique_ptr< optimizer_type >	opt_
	Optimizer.

IgANetOptions	options_
	Options.

Additional Inherited Members
Private Member Functions inherited from iganet::utils::Serializable
virtual	~Serializable ()=default
	Destructor.

Private Member Functions inherited from iganet::utils::FullQualifiedName
virtual	~FullQualifiedName ()=default

virtual const std::string &	name () const noexcept
	Returns the full qualified name of the object.

Private Attributes inherited from iganet::utils::FullQualifiedName
at::optional< std::string >	name_
	String storing the full qualified name of the object.

Detailed Description

template<typename Optimizer, typename Inputs, typename Outputs, typename CollPts = void>
requires OptimizerType<Optimizer>
class iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >

IgANet.

This class implements the core functionality of IgANets.

Member Typedef Documentation

◆ Base

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

using iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::Base = IgABase<Inputs, Outputs, CollPts>

Base type.

◆ optimizer_options_type

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

using iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizer_options_type = optimizer_options_type<Optimizer>::type

Type of the optimizer options.

◆ optimizer_type

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

using iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizer_type = Optimizer

Type of the optimizer.

◆ value_type

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

using iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::value_type = Base::value_type

Value type.

Constructor & Destructor Documentation

◆ IgANet() [1/3]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::IgANet	(	const IgANetOptions &	defaults = `{}`,
		iganet::Options< typename Base::value_type >	options = `iganet::Options<typename Base::value_type>{}`
	)

inlineexplicit

Default constructor.

Parameters

defaults	Value of `defaults`.
options	Configuration options.

◆ IgANet() [2/3]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

template<typename NumCoeffs >

iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::IgANet	(	const std::vector< int64_t > &	layers,
		const std::vector< std::vector< std::any > > &	activations,
		const NumCoeffs &	numCoeffs,
		enum init	init = `init::greville`,
		IgANetOptions	defaults = `{}`,
		iganet::Options< typename Base::value_type >	options = `iganet::Options<typename Base::value_type>{}`
	)

inline

Constructor: number of layers, activation functions, and number of spline coefficients (same for all inputs and outputs).

Template Parameters

NumCoeffs Template parameter NumCoeffs.

Parameters

layers	Value of `layers`.
activations	Value of `activations`.
numCoeffs	Value of `numCoeffs`.
init	Value of `init`.
defaults	Value of `defaults`.
options	Configuration options.

◆ IgANet() [3/3]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

template<typename NumCoeffsInputs , typename NumCoeffsOutputs >

iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::IgANet	(	const std::vector< int64_t > &	layers,
		const std::vector< std::vector< std::any > > &	activations,
		const NumCoeffsInputs &	numCoeffsInputs,
		const NumCoeffsOutputs &	numCoeffsOutputs,
		enum init	init = `init::greville`,
		IgANetOptions	defaults = `{}`,
		iganet::Options< typename Base::value_type >	options = `iganet::Options<typename Base::value_type>{}`
	)

inline

Constructor: number of layers, activation functions, and number of spline coefficients (same for all inputs and outputs).

Template Parameters

NumCoeffsInputs	Template parameter `NumCoeffsInputs`.
NumCoeffsOutputs	Template parameter `NumCoeffsOutputs`.

Parameters

layers	Value of `layers`.
activations	Value of `activations`.
numCoeffsInputs	Value of `numCoeffsInputs`.
numCoeffsOutputs	Value of `numCoeffsOutputs`.
init	Value of `init`.
defaults	Value of `defaults`.
options	Configuration options.

Member Function Documentation

◆ epoch()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

virtual bool iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::epoch ( int64_t )

pure virtual

Initializes epoch.

Returns: Result of the operation.

◆ eval()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::eval ( )

inline

Evaluate IgANet.

◆ inputs() [1/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

constexpr auto & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::inputs ( )

inlineconstexpr

Returns a non-constant reference to the tuple of input objects.

Returns: Result of the operation.

◆ inputs() [2/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

constexpr const auto & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::inputs ( ) const

inlineconstexpr

Returns a constant reference to the tuple of input objects.

Returns: Result of the operation.

◆ inputs() [3/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

virtual void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::inputs ( const torch::Tensor & tensor )

inlinevirtual

Attaches the given tensor to the inputs.

Parameters

tensor Tensor to process.

◆ inputs() [4/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

virtual torch::Tensor iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::inputs ( int64_t epoch ) const

inlinevirtual

Returns the network inputs as tensor.

Parameters

epoch Value of epoch.

Returns: Result of the operation.

◆ load()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::load	(	const std::string &	filename,
		const std::string &	key = `"iganet"`
	)

inline

Loads the IgANet from file.

Parameters

filename	Path of the file to process.
key	Serialization key.

◆ loss()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

virtual torch::Tensor iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::loss	(	const torch::Tensor &	,
		int64_t
	)

pure virtual

Computes the loss function.

Returns: Result of the operation.

◆ named_parameters()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

torch::OrderedDict< std::string, torch::Tensor > iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::named_parameters ( ) const

inlinenoexcept

Returns a constant reference to the named parameters of the IgANet object.

Returns: Result of the operation.

◆ net() [1/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

IgANetGenerator< typename Base::value_type > & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::net ( )

inline

Returns a non-constant reference to the IgANet generator.

Returns: Result of the operation.

◆ net() [2/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

const IgANetGenerator< typename Base::value_type > & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::net ( ) const

inline

Returns a constant reference to the IgANet generator.

Returns: Result of the operation.

◆ nparameters()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

std::size_t iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::nparameters ( ) const

inlinenoexcept

Returns the total number of parameters of the IgANet object.

Returns: Result of the operation.

◆ operator!=()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

bool iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::operator!= ( const IgANet< Optimizer, Inputs, Outputs, CollPts > & other ) const

inline

Returns true if both IgANet objects are different.

Parameters

other Second input value.

Returns: Result of the operation.

◆ operator==()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

bool iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::operator== ( const IgANet< Optimizer, Inputs, Outputs, CollPts > & other ) const

inline

Returns true if both IgANet objects are the same.

Parameters

other Second input value.

Returns: Result of the operation.

◆ optimizer() [1/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

optimizer_type & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizer ( )

inline

Returns a non-constant reference to the optimizer.

Returns: Result of the operation.

◆ optimizer() [2/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

const optimizer_type & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizer ( ) const

inline

Returns a constant reference to the optimizer.

Returns: Result of the operation.

◆ optimizerOptions() [1/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

optimizer_options_type & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizerOptions ( std::size_t param_group = 0 )

inline

Returns a non-constant reference to the optimizer options.

Parameters

param_group Value of param_group.

Returns: Result of the operation.

◆ optimizerOptions() [2/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

const optimizer_options_type & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizerOptions ( std::size_t param_group = 0 ) const

inline

Returns a constant reference to the optimizer options.

Parameters

param_group Value of param_group.

Returns: Result of the operation.

◆ optimizerOptionsReset() [1/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizerOptionsReset ( const optimizer_options_type & options )

inline

Resets the optimizer options.

Parameters

options Configuration options.

◆ optimizerOptionsReset() [2/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizerOptionsReset	(	const optimizer_options_type &	options,
		std::size_t	param_group
	)

inline

Resets the optimizer options.

Parameters

options	Configuration options.
param_group	Value of `param_group`.

◆ optimizerOptionsReset() [3/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizerOptionsReset ( optimizer_options_type && options )

inline

Resets the optimizer options.

Parameters

options Configuration options.

◆ optimizerOptionsReset() [4/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizerOptionsReset	(	optimizer_options_type &&	options,
		std::size_t	param_group
	)

inline

Resets the optimizer options.

Parameters

options	Configuration options.
param_group	Value of `param_group`.

◆ optimizerReset() [1/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizerReset ( bool resetOptions = true )

inline

Resets the optimizer.

Parameters

[in] resetOptions Flag to indicate whether the optimizer options should be resetted.

◆ optimizerReset() [2/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::optimizerReset ( const optimizer_options_type & optimizerOptions )

inline

Resets the optimizer.

Parameters

optimizerOptions Value of optimizerOptions.

◆ options() [1/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

auto & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::options ( )

inline

Returns a non-constant reference to the options structure.

Returns: Result of the operation.

◆ options() [2/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

const auto & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::options ( ) const

inline

Returns a constant reference to the options structure.

Returns: Result of the operation.

◆ outputs() [1/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

constexpr auto & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::outputs ( )

inlineconstexpr

Returns a non-constant reference to the tuple of output objects.

Returns: Result of the operation.

◆ outputs() [2/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

constexpr const auto & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::outputs ( ) const

inlineconstexpr

Returns a constant reference to the tuple of output objects.

Returns: Result of the operation.

◆ outputs() [3/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

virtual void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::outputs ( const torch::Tensor & tensor )

inlinevirtual

Attaches the given tensor to the outputs.

Parameters

tensor Tensor to process.

◆ outputs() [4/4]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

virtual torch::Tensor iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::outputs ( int64_t epoch ) const

inlinevirtual

Returns the network outputs as tensor.

Parameters

epoch Value of epoch.

Returns: Result of the operation.

◆ parameters()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

std::vector< torch::Tensor > iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::parameters ( ) const

inlinenoexcept

Returns a constant reference to the parameters of the IgANet object.

Returns: Result of the operation.

◆ pretty_print()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::pretty_print ( std::ostream & os ) const

inlineoverridevirtualnoexcept

Returns a string representation of the IgANet object.

Parameters

os	Output stream.

Implements iganet::utils::Serializable.

◆ read()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

torch::serialize::InputArchive & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::read	(	torch::serialize::InputArchive &	archive,
		const std::string &	key = `"iganet"`
	)

inline

Loads the IgANet from a torch::serialize::InputArchive object.

Parameters

archive	Serialization archive.
key	Serialization key.

Returns: Result of the operation.

◆ register_parameter()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

torch::Tensor & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::register_parameter	(	std::string	name,
		torch::Tensor	tensor,
		bool	requires_grad = `true`
	)

inline

Registers a parameter.

Parameters

name	Value of `name`.
tensor	Tensor to process.
requires_grad	Value of `requires_grad`.

Returns: Result of the operation.

◆ save()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::save	(	const std::string &	filename,
		const std::string &	key = `"iganet"`
	)		const

inline

Saves the IgANet to file.

Parameters

filename	Path of the file to process.
key	Serialization key.

◆ to_json()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

nlohmann::json iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::to_json ( ) const

inlineoverridevirtual

Returns the IgANet object as JSON object.

Returns: Result of the operation.

Implements iganet::utils::Serializable.

◆ train() [1/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

virtual void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::train ( )

inlinevirtual

Trains the IgANet.

◆ train() [2/2]

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

template<typename DataLoader >

void iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::train ( DataLoader & loader )

inline

Trains the IgANet.

Template Parameters

DataLoader Template parameter DataLoader.

Parameters

loader Training data loader.

◆ write()

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

torch::serialize::OutputArchive & iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::write	(	torch::serialize::OutputArchive &	archive,
		const std::string &	key = `"iganet"`
	)		const

inline

Writes the IgANet into a torch::serialize::OutputArchive object.

Parameters

archive	Serialization archive.
key	Serialization key.

Returns: Result of the operation.

Member Data Documentation

◆ net_

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

IgANetGenerator<typename Base::value_type> iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::net_

protected

IgANet generator.

◆ opt_

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

std::unique_ptr<optimizer_type> iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::opt_

protected

Optimizer.

◆ options_

template<typename Optimizer , typename Inputs , typename Outputs , typename CollPts = void>

IgANetOptions iganet::IgANet< Optimizer, Inputs, Outputs, CollPts >::options_

protected

Options.

The documentation for this class was generated from the following file:

include/iganet/net/iganet.hpp

Public Types

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ Base

◆ optimizer_options_type

◆ optimizer_type

◆ value_type

Constructor & Destructor Documentation

◆ IgANet() [1/3]

◆ IgANet() [2/3]

◆ IgANet() [3/3]

Member Function Documentation

◆ epoch()

◆ eval()

◆ inputs() [1/4]

◆ inputs() [2/4]

◆ inputs() [3/4]

◆ inputs() [4/4]

◆ load()

◆ loss()

◆ named_parameters()

◆ net() [1/2]

◆ net() [2/2]

◆ nparameters()

◆ operator!=()

◆ operator==()

◆ optimizer() [1/2]

◆ optimizer() [2/2]

◆ optimizerOptions() [1/2]

◆ optimizerOptions() [2/2]

◆ optimizerOptionsReset() [1/4]

◆ optimizerOptionsReset() [2/4]

◆ optimizerOptionsReset() [3/4]

◆ optimizerOptionsReset() [4/4]

◆ optimizerReset() [1/2]

◆ optimizerReset() [2/2]

◆ options() [1/2]

◆ options() [2/2]

◆ outputs() [1/4]

◆ outputs() [2/4]

◆ outputs() [3/4]

◆ outputs() [4/4]

◆ parameters()

◆ pretty_print()

◆ read()

◆ register_parameter()

◆ save()

◆ to_json()

◆ train() [1/2]

◆ train() [2/2]

◆ write()

Member Data Documentation

◆ net_

◆ opt_

◆ options_