IgANet< Optimizer, GeometryMap, Variable > Class Template Reference

Inheritance diagram for IgANet< Optimizer, GeometryMap, Variable >:

Public Member Functions
bool	epoch (int64_t epoch) override
	Initializes epoch.
torch::Tensor	loss (const torch::Tensor &outputs, int64_t epoch) override
	Computes the loss function.
Public Member Functions inherited from iganet::IgANet< Optimizer, GeometryMap, Variable >
	IgANet (const IgANetOptions &defaults={}, iganet::Options< typename Base::value_type > options=iganet::Options< typename Base::value_type >{})
	Default constructor.
	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)
	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)
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.
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.
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.

Private Types
using	Base = iganet::IgANet< Optimizer, GeometryMap, Variable >

Private Attributes
Base::variable_collPts_type	collPts_

Additional Inherited Members
Public Types inherited from iganet::IgANet< Optimizer, GeometryMap, Variable >
using	Base = IgABase< GeometryMap, Variable, void >
	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.
Protected Attributes inherited from iganet::IgANet< Optimizer, GeometryMap, Variable >
IgANetGenerator< typename Base::value_type >	net_
	IgANet generator.
std::unique_ptr< optimizer_type >	opt_
	Optimizer.
IgANetOptions	options_
	Options.

Member Typedef Documentation

Base

template<typename Optimizer , typename GeometryMap , typename Variable >

using IgANet< Optimizer, GeometryMap, Variable >::Base = iganet::IgANet<Optimizer, GeometryMap, Variable>

private

Member Function Documentation

epoch()

template<typename Optimizer , typename GeometryMap , typename Variable >

bool IgANet< Optimizer, GeometryMap, Variable >::epoch ( int64_t  )

inlineoverridevirtual

Initializes epoch.

Implements iganet::IgANet< Optimizer, GeometryMap, Variable >.

loss()

template<typename Optimizer , typename GeometryMap , typename Variable >

torch::Tensor IgANet< Optimizer, GeometryMap, Variable >::loss ( const torch::Tensor &  , int64_t    )

inlineoverridevirtual

Computes the loss function.

Implements iganet::IgANet< Optimizer, GeometryMap, Variable >.

Member Data Documentation

collPts_

template<typename Optimizer , typename GeometryMap , typename Variable >

Base::variable_collPts_type IgANet< Optimizer, GeometryMap, Variable >::collPts_

private

---

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

• optional/unittests/src/unittest_iganet.cxx