The base class for all constitutive models. More...

Detailed Description

The base class for all constitutive models.

A model maps some input to output. The forward operator (and its derivative) is defined in the method Model::set_value. All concrete models must provide the implementation of the forward operator by overriding the Model::set_value method.

#include <Model.h>

Inherits enable_shared_from_this< Model >, Data, ParameterStore, VariableStore, NonlinearSystem, DependencyDefinition< VariableName >, and DiagnosticsInterface.

Inherited by ElasticityInterface< Model, 2 >, NonlinearParameter< Scalar >, NonlinearParameter< SSR4 >, AssociativeJ2FlowDirection, BackwardEulerTimeIntegration< T >, ComposedModel, CopyVariable< T >, CrystalMean< T >, Eigenstrain, ElasticStrainRate, Elasticity, FixOrientation, FlowRule, ForwardEulerTimeIntegration< T >, GTNYieldFunction, GursonCavitation, ImplicitUpdate, IsotropicHardening, IsotropicHardeningStaticRecovery, KinematicHardening, KinematicHardeningStaticRecovery, KocksMeckingActivationEnergy, KocksMeckingFlowSwitch, LinearCombination< T >, MandelStress, MixedControlSetup, NonlinearParameter< T >, Normality, OlevskySinteringStress, OrientationRate, PlasticDeformationRate, PlasticFlowRate, PlasticVorticity, RateIndependentPlasticFlowConstraint, ResolvedShear, RotationMatrix, SR2Invariant, SingleSlipHardeningRule, SlipRule, SlipStrengthMap, SumSlipRates, TwoStageThermalAnnealing< T >, VariableRate< T >, WR2ExplicitExponentialTimeIntegration, WR2ImplicitExponentialTimeIntegration, and YieldFunction.

Public Member Functions
	Model (const OptionSet &options)
	Construct a new Model object.

virtual void	to (const torch::TensorOptions &options)
	Send model to a different device or dtype.

void	diagnose (std::vector< Diagnosis > &) const override
	Check for common problems.

virtual bool	is_nonlinear_system () const
	Whether this model defines one or more nonlinear equations to be solved.

const std::vector< Model * > &	registered_models () const
	The models that may be used during the evaluation of this model.

Model *	registered_model (const std::string &name) const
	Get a registered model by its name.

std::set< VariableName >	consumed_items () const override
	The variables that this model depends on.

std::set< VariableName >	provided_items () const override
	The variables that this model defines as part of its output.

void	clear_input () override

void	clear_output () override

void	zero_input () override

void	zero_output () override

void	request_AD (VariableBase &y, const VariableBase &u)
	Request to use AD to compute the first derivative of a variable.

void	request_AD (VariableBase &y, const VariableBase &u1, const VariableBase &u2)
	Request to use AD to compute the second derivative of a variable.

virtual void	value ()
	Evalute the model.

virtual void	value_and_dvalue ()
	Evalute the model and compute its derivative.

virtual void	dvalue ()
	Evalute the derivative.

virtual void	value_and_dvalue_and_d2value ()
	Evalute the model and compute its first and second derivatives.

virtual void	d2value ()
	Evalute the second derivatives.

virtual void	dvalue_and_d2value ()
	Evalute the first and second derivatives.

virtual ValueMap	value (const ValueMap &in)
	Convenient shortcut to construct and return the model value.

virtual std::tuple< ValueMap, DerivMap >	value_and_dvalue (const ValueMap &in)
	Convenient shortcut to construct and return the model value and its derivative.

virtual DerivMap	dvalue (const ValueMap &in)
	Convenient shortcut to construct and return the derivative.

virtual std::tuple< ValueMap, DerivMap, SecDerivMap >	value_and_dvalue_and_d2value (const ValueMap &in)
	Convenient shortcut to construct and return the model's value, first and second derivative.

virtual SecDerivMap	d2value (const ValueMap &in)
	Convenient shortcut to construct and return the model's second derivative.

virtual std::tuple< DerivMap, SecDerivMap >	dvalue_and_d2value (const ValueMap &in)
	Convenient shortcut to construct and return the model's first and second derivative.

Public Member Functions inherited from Data
	Data (const OptionSet &options)
	Construct a new Data object.

const std::vector< Data * > &	registered_data () const
	All the registered data objects.

Public Member Functions inherited from NEML2Object
	NEML2Object ()=delete

	NEML2Object (NEML2Object &&)=delete

	NEML2Object (const NEML2Object &)=delete

NEML2Object &	operator= (const NEML2Object &)=delete

NEML2Object &	operator= (NEML2Object &&)=delete

virtual	~NEML2Object ()=default

	NEML2Object (const OptionSet &options)
	Construct a new NEML2Object object.

const OptionSet &	input_options () const

const std::string &	name () const
	A readonly reference to the object's name.

const std::string &	type () const
	A readonly reference to the object's type.

const std::string &	path () const
	A readonly reference to the object's path.

const std::string &	doc () const
	A readonly reference to the object's docstring.

template<typename T = NEML2Object>
const T *	host () const
	Get a readonly pointer to the host.

template<typename T = NEML2Object>
T *	host ()
	Get a writable pointer to the host.

Public Member Functions inherited from BufferStore
	BufferStore (OptionSet options, NEML2Object *object)

	BufferStore (const BufferStore &)=delete

	BufferStore (BufferStore &&)=delete

BufferStore &	operator= (const BufferStore &)=delete

BufferStore &	operator= (BufferStore &&)=delete

virtual	~BufferStore ()=default

const Storage< std::string, TensorValueBase > &	named_buffers () const

Storage< std::string, TensorValueBase > &	named_buffers ()

TensorValueBase &	get_buffer (const std::string &name)
	}@

const TensorValueBase &	get_buffer (const std::string &name) const
	Get a read-only reference of a buffer.

Public Member Functions inherited from ParameterStore
	ParameterStore (OptionSet options, NEML2Object *object)

	ParameterStore (const ParameterStore &)=delete

	ParameterStore (ParameterStore &&)=delete

ParameterStore &	operator= (const ParameterStore &)=delete

ParameterStore &	operator= (ParameterStore &&)=delete

virtual	~ParameterStore ()=default

const Storage< std::string, TensorValueBase > &	named_parameters () const

Storage< std::string, TensorValueBase > &	named_parameters ()

void	set_parameter (const std::string &, const Tensor &)
	}@

void	set_parameters (const std::map< std::string, Tensor > &)
	Set values for parameters.

TensorValueBase &	get_parameter (const std::string &name)
	Get a writable reference of a parameter.

const TensorValueBase &	get_parameter (const std::string &name) const
	Get a read-only reference of a parameter.

bool	has_nl_param () const
	Whether this parameter store has any nonlinear parameter.

const VariableBase *	nl_param (const std::string &) const
	Query the existence of a nonlinear parameter.

virtual std::map< std::string, const VariableBase * >	named_nonlinear_parameters (bool recursive=false) const
	Get all nonlinear parameters.

virtual std::map< std::string, Model * >	named_nonlinear_parameter_models (bool recursive=false) const
	Get all nonlinear parameters' models.

Public Member Functions inherited from VariableStore
	VariableStore (OptionSet options, Model *object)

	VariableStore (const VariableStore &)=delete

	VariableStore (VariableStore &&)=delete

VariableStore &	operator= (const VariableStore &)=delete

VariableStore &	operator= (VariableStore &&)=delete

virtual	~VariableStore ()=default

LabeledAxis &	declare_axis (const std::string &name)

virtual void	setup_layout ()
	Setup the layout of all the registered axes.

const torch::TensorOptions &	tensor_options () const
	Current tensor options.

LabeledAxis &	input_axis ()

const LabeledAxis &	input_axis () const

LabeledAxis &	output_axis ()

const LabeledAxis &	output_axis () const

Storage< VariableName, VariableBase > &	input_variables ()

const Storage< VariableName, VariableBase > &	input_variables () const

Storage< VariableName, VariableBase > &	output_variables ()

const Storage< VariableName, VariableBase > &	output_variables () const

VariableBase &	input_variable (const VariableName &)

const VariableBase &	input_variable (const VariableName &) const

VariableBase &	output_variable (const VariableName &)

const VariableBase &	output_variable (const VariableName &) const

void	assign_input (const ValueMap &vals)

void	assign_output (const ValueMap &vals)

void	assign_output_derivatives (const DerivMap &derivs)
	Assign variable derivatives.

ValueMap	collect_input () const

ValueMap	collect_output () const

DerivMap	collect_output_derivatives () const
	Collect variable derivatives.

SecDerivMap	collect_output_second_derivatives () const
	Collect variable second derivatives.

Public Member Functions inherited from NonlinearSystem
	NonlinearSystem (const NonlinearSystem &)=default

	NonlinearSystem (NonlinearSystem &&) noexcept=default

NonlinearSystem &	operator= (const NonlinearSystem &)=delete

NonlinearSystem &	operator= (NonlinearSystem &&)=delete

virtual	~NonlinearSystem ()=default

	NonlinearSystem (const OptionSet &options)

virtual void	init_scaling (const Sol< false > &x, const bool verbose=false)
	Compute algebraic Jacobian-based automatic scaling following https://cs.stanford.edu/people/paulliu/files/cs517-project.pdf.

Res< true >	scale (const Res< false > &r) const
	Apply scaling to the residual.

Res< false >	unscale (const Res< true > &r) const
	Remove scaling to the residual.

Jac< true >	scale (const Jac< false > &J) const
	Apply scaling to the Jacobian.

Jac< false >	unscale (const Jac< true > &J) const
	Remove scaling to the Jacobian.

Sol< true >	scale (const Sol< false > &u) const
	Apply scaling to the solution.

Sol< false >	unscale (const Sol< true > &u) const
	Remove scaling to the solution.

virtual void	set_guess (const Sol< true > &x) final
	Set the current guess.

template<bool scaled>
Res< scaled >	residual ()
	Assemble and return the residual.

template<bool scaled>
Res< scaled >	residual (const Sol< scaled > &x)
	Convenient shortcut to set the current guess, assemble and return the residual.

template<bool scaled>
Jac< scaled >	Jacobian ()
	Assemble and return the Jacobian.

template<bool scaled>
Jac< scaled >	Jacobian (const Sol< scaled > &x)
	Convenient shortcut to set the current guess, assemble and return the Jacobian.

template<bool scaled>
std::tuple< Res< scaled >, Jac< scaled > >	residual_and_Jacobian ()
	Assemble and return the residual and Jacobian.

template<bool scaled>
std::tuple< Res< scaled >, Jac< scaled > >	residual_and_Jacobian (const Sol< scaled > &x)
	Convenient shortcut to set the current guess, assemble and return the residual and Jacobian.

Public Member Functions inherited from DependencyDefinition< VariableName >
	DependencyDefinition ()=default

	DependencyDefinition (DependencyDefinition &&)=delete

	DependencyDefinition (const DependencyDefinition &)=delete

DependencyDefinition &	operator= (const DependencyDefinition &)=delete

DependencyDefinition &	operator= (DependencyDefinition &&)=delete

virtual	~DependencyDefinition ()=default

Public Member Functions inherited from DiagnosticsInterface
	DiagnosticsInterface ()=delete

	DiagnosticsInterface (NEML2Object *object)

	DiagnosticsInterface (DiagnosticsInterface &&)=delete

	DiagnosticsInterface (const DiagnosticsInterface &)=delete

DiagnosticsInterface &	operator= (const DiagnosticsInterface &)=delete

DiagnosticsInterface &	operator= (DiagnosticsInterface &&)=delete

virtual	~DiagnosticsInterface ()=default

template<typename... Args>
void	diagnostic_assert (std::vector< Diagnosis > &diagnoses, bool assertion, Args &&... args) const

void	diagnostic_assert_state (std::vector< Diagnosis > &diagnoses, const VariableBase &v) const

void	diagnostic_assert_old_state (std::vector< Diagnosis > &diagnoses, const VariableBase &v) const

void	diagnostic_assert_force (std::vector< Diagnosis > &diagnoses, const VariableBase &v) const

void	diagnostic_assert_old_force (std::vector< Diagnosis > &diagnoses, const VariableBase &v) const

void	diagnostic_assert_residual (std::vector< Diagnosis > &diagnoses, const VariableBase &v) const

void	diagnostic_check_input_variable (std::vector< Diagnosis > &diagnoses, const VariableBase &v) const

void	diagnostic_check_output_variable (std::vector< Diagnosis > &diagnoses, const VariableBase &v) const

Static Public Member Functions
static OptionSet	expected_options ()

Static Public Member Functions inherited from Data
static OptionSet	expected_options ()

Static Public Member Functions inherited from NEML2Object
static OptionSet	expected_options ()

Static Public Member Functions inherited from NonlinearSystem
static OptionSet	expected_options ()

static void	disable_automatic_scaling (OptionSet &options)

static void	enable_automatic_scaling (OptionSet &options)

Protected Member Functions
void	setup () override
	Setup this object.

virtual void	link_input_variables ()

virtual void	link_input_variables (Model *submodel)

virtual void	link_output_variables ()

virtual void	link_output_variables (Model *submodel)

virtual void	request_AD ()

void	diagnose_nl_sys (std::vector< Diagnosis > &diagnoses) const
	Additional diagnostics for a nonlinear system.

virtual void	set_value (bool out, bool dout_din, bool d2out_din2)=0
	The map between input -> output, and optionally its derivatives.

template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<Model, T>>>
T &	register_model (const std::string &name, bool nonlinear=false, bool merge_input=true)
	Register a model that the current model may use during its evaluation.

void	set_guess (const Sol< false > &) override
	Set the unscaled current guess.

void	assemble (Res< false > , Jac< false > ) override
	Compute the unscaled residual and Jacobian.

Protected Member Functions inherited from Data
template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<Data, T>>>
T &	register_data (const std::string &name)

Protected Member Functions inherited from BufferStore
virtual void	send_buffers_to (const torch::TensorOptions &options)
	Send all buffers to `options`.

template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<TensorBase<T>, T>>>
const T &	declare_buffer (const std::string &name, const T &rawval)
	Declare a buffer.

template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<TensorBase<T>, T>>>
const T &	declare_buffer (const std::string &name, const CrossRef< T > &crossref)
	Declare a buffer.

template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<TensorBase<T>, T>>>
const T &	declare_buffer (const std::string &name, const std::string &input_option_name)
	Declare a buffer.

Protected Member Functions inherited from ParameterStore
virtual void	send_parameters_to (const torch::TensorOptions &options)
	Send parameters to options.

template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<TensorBase<T>, T>>>
const T &	declare_parameter (const std::string &name, const T &rawval)
	Declare a parameter.

template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<TensorBase<T>, T>>>
const T &	declare_parameter (const std::string &name, const CrossRef< T > &crossref, bool allow_nonlinear)
	Declare a parameter.

template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<TensorBase<T>, T>>>
const T &	declare_parameter (const std::string &name, const std::string &input_option_name, bool allow_nonlinear=false)
	Declare a parameter.

Protected Member Functions inherited from VariableStore
template<typename T , typename S >
const Variable< T > &	declare_input_variable (S &&name, TensorShapeRef list_shape={}, TensorShapeRef base_shape={})
	Declare an input variable.

template<typename T , typename S >
Variable< T > &	declare_output_variable (S &&name, TensorShapeRef list_shape={}, TensorShapeRef base_shape={})
	Declare an output variable.

const VariableBase *	clone_input_variable (const VariableBase &var, const VariableName &new_name={})
	Clone a variable and put it on the input axis.

VariableBase *	clone_output_variable (const VariableBase &var, const VariableName &new_name={})
	Clone a variable and put it on the output axis.

Protected Attributes
std::vector< Model * >	_registered_models
	Models this model may use during its evaluation.

Protected Attributes inherited from Data
std::vector< Data * >	_registered_data
	Registered Data objects.

Protected Attributes inherited from ParameterStore
std::map< std::string, const VariableBase * >	_nl_params
	Map from nonlinear parameter names to their corresponding variable views.

std::map< std::string, Model * >	_nl_param_models
	Map from nonlinear parameter names to models which evaluate them.

Protected Attributes inherited from NonlinearSystem
const bool	_autoscale
	If true, do automatic scaling.

const Real	_autoscale_tol
	Tolerance for convergence check of the iterative automatic scaling algorithm.

const unsigned int	_autoscale_miter
	Maximum number of iterations allowed for the iterative automatic scaling algorithm.

bool	_scaling_matrices_initialized
	Flag to indicate whether scaling matrices have been computed.

Tensor	_row_scaling
	Row scaling "matrix" – since it's a batched diagonal matrix, we are only storing its diagonals.

Tensor	_col_scaling
	Column scaling "matrix" – since it's a batched diagonal matrix, we are only storing its diagonals.

Friends
class	ParameterStore
	Declaration of nonlinear parameters may require manipulation of input.

class	ComposedModel
	ComposedModel's set_value need to call submodel's set_value.

Constructor & Destructor Documentation

◆ Model()

Model ( const OptionSet & options )

Construct a new Model object.

Parameters

options The options extracted from the input file

Member Function Documentation

◆ assemble()

void assemble	(	Res< false > *	r,
		Jac< false > *	J )

overrideprotectedvirtual

Compute the unscaled residual and Jacobian.

Parameters

r	Pointer to the residual vector – nullptr if not requested
J	Pointer to the Jacobian matrix – nullptr if not requested

Implements NonlinearSystem.

◆ clear_input()

void clear_input ( )

overridevirtual

Release allocated tensor

Reimplemented from VariableStore.

◆ clear_output()

void clear_output ( )

overridevirtual

Reimplemented from VariableStore.

◆ consumed_items()

std::set< VariableName > consumed_items ( ) const

overridevirtual

The variables that this model depends on.

Implements DependencyDefinition< VariableName >.

◆ d2value() [1/2]

void d2value ( )

virtual

Evalute the second derivatives.

◆ d2value() [2/2]

SecDerivMap d2value ( const ValueMap & in )

virtual

Convenient shortcut to construct and return the model's second derivative.

◆ diagnose()

void diagnose ( std::vector< Diagnosis > & diagnoses ) const

overridevirtual

Check for common problems.

This method serves as the entry point for diagnosing common problems in object setup. The idea behind this method is that while some errors could be detected at construction time, i.e., when the object's constructor is called, it doesn't hinder other objects' creation. We therefore would like to defer the detection of errors until after all objects have been created, collect all errors at once, and present the user with a complete understanding of all errors encountered.

Note, however, if an error could interfere with other objects' creation, it should be raised right away inside the constructor, instead of inside this method.

Parameters

diagnoses A vector of exceptions of type Diagnosis for each of the detected problem.

Implements DiagnosticsInterface.

Reimplemented in VariableRate< T >, WR2ExplicitExponentialTimeIntegration, and WR2ImplicitExponentialTimeIntegration.

◆ diagnose_nl_sys()

void diagnose_nl_sys ( std::vector< Diagnosis > & diagnoses ) const

protected

Additional diagnostics for a nonlinear system.

◆ dvalue() [1/2]

void dvalue ( )

virtual

Evalute the derivative.

◆ dvalue() [2/2]

DerivMap dvalue ( const ValueMap & in )

virtual

Convenient shortcut to construct and return the derivative.

◆ dvalue_and_d2value() [1/2]

void dvalue_and_d2value ( )

virtual

Evalute the first and second derivatives.

◆ dvalue_and_d2value() [2/2]

std::tuple< DerivMap, SecDerivMap > dvalue_and_d2value ( const ValueMap & in )

virtual

Convenient shortcut to construct and return the model's first and second derivative.

◆ expected_options()

OptionSet expected_options ( )

static

◆ is_nonlinear_system()

virtual bool is_nonlinear_system ( ) const

inlinevirtual

Whether this model defines one or more nonlinear equations to be solved.

◆ link_input_variables() [1/2]

void link_input_variables ( )

protectedvirtual

◆ link_input_variables() [2/2]

void link_input_variables ( Model * submodel )

protectedvirtual

Reimplemented in ComposedModel.

◆ link_output_variables() [1/2]

void link_output_variables ( )

protectedvirtual

Reimplemented in ImplicitUpdate.

◆ link_output_variables() [2/2]

void link_output_variables ( Model * submodel )

protectedvirtual

Reimplemented in ComposedModel.

◆ provided_items()

std::set< VariableName > provided_items ( ) const

overridevirtual

The variables that this model defines as part of its output.

Implements DependencyDefinition< VariableName >.

◆ register_model()

template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<Model, T>>>

T & register_model	(	const std::string &	name,
		bool	nonlinear = false,
		bool	merge_input = true )

inlineprotected

Register a model that the current model may use during its evaluation.

If merge_input is set to true, this model will also consume the consumed variables of model, which will affect dependency resolution inside a ComposedModel.

Parameters

name	The model to register
nonlinear	Set to true if the registered model defines a nonlinear system to be solved
merge_input	Whether to merge the input axis of the registered model into this model's input axis. This will make sure that the input variables of the registered model are "ready" by the time this model is evaluated.

◆ registered_model()

Model * registered_model ( const std::string & name ) const

Get a registered model by its name.

◆ registered_models()

const std::vector< Model * > & registered_models ( ) const

inline

The models that may be used during the evaluation of this model.

◆ request_AD() [1/3]

virtual void request_AD ( )

inlineprotectedvirtual

Request the use of automatic differentiation to compute variable derivatives

Model implementations which require automatic differentiation to compute variable derivatives shall override this method and mark variable derivatives. Variable derivatives are marked as,

// To request first derivative of foo with respect to bar
request_AD(foo, bar);
 
// To request second derivative of foo with respect to bar and baz
request_AD(foo, bar, baz);

◆ request_AD() [2/3]

void request_AD	(	VariableBase &	y,
		const VariableBase &	u )

Request to use AD to compute the first derivative of a variable.

◆ request_AD() [3/3]

void request_AD	(	VariableBase &	y,
		const VariableBase &	u1,
		const VariableBase &	u2 )

Request to use AD to compute the second derivative of a variable.

◆ set_guess()

void set_guess ( const Sol< false > & x )

overrideprotectedvirtual

Set the unscaled current guess.

Implements NonlinearSystem.

◆ set_value()

virtual void set_value	(	bool	out,
		bool	dout_din,
		bool	d2out_din2 )

protectedpure virtual

The map between input -> output, and optionally its derivatives.

Implemented in ArrheniusParameter, BackwardEulerTimeIntegration< T >, ConstantParameter< T >, CopyVariable< T >, ForwardEulerTimeIntegration< T >, ImplicitUpdate, InputParameter< T >, LinearCombination< T >, LinearInterpolation< T >, RotationMatrix, AssociativeIsotropicPlasticHardening, AssociativeKinematicPlasticHardening, AssociativePlasticFlow, ChabochePlasticHardening, CrystalMean< T >, ElasticStrainRate, FixOrientation, LinearSingleSlipHardeningRule, OrientationRate, PlasticDeformationRate, PlasticVorticity, PowerLawSlipRule, ResolvedShear, SingleSlipStrengthMap, SumSlipRates, VoceSingleSlipHardeningRule, CubicElasticityTensor, GeneralElasticity, IsotropicElasticityTensor, LinearIsotropicElasticity, FredrickArmstrongPlasticHardening, GTNYieldFunction, GursonCavitation, IsotropicMandelStress, KocksMeckingActivationEnergy, KocksMeckingFlowSwitch, KocksMeckingFlowViscosity, KocksMeckingIntercept, KocksMeckingRateSensitivity, KocksMeckingYieldStress, LinearIsotropicElasticJ2TrialStressUpdate, LinearIsotropicHardening, LinearKinematicHardening, MixedControlSetup, Normality, OlevskySinteringStress, PerzynaPlasticFlowRate, PowerLawIsotropicHardeningStaticRecovery, PowerLawKinematicHardeningStaticRecovery, RateIndependentPlasticFlowConstraint, SlopeSaturationVoceIsotropicHardening, TwoStageThermalAnnealing< T >, VoceIsotropicHardening, YieldFunction, SR2Invariant, VariableRate< T >, WR2ExplicitExponentialTimeIntegration, WR2ImplicitExponentialTimeIntegration, ComposedModel, AssociativeJ2FlowDirection, and ThermalEigenstrain.

◆ setup()

void setup ( )

overrideprotectedvirtual

Setup this object.

This method is called automatically if you use the Factory method get_object or get_object_ptr, right after construction. This serves as the entry point for things that are not convenient/possible to do at construction time, but are necessary before this object can be used (by others).

Reimplemented from NEML2Object.

◆ to()

void to ( const torch::TensorOptions & options )

virtual

Send model to a different device or dtype.

◆ value() [1/2]

void value ( )

virtual

Evalute the model.

◆ value() [2/2]

ValueMap value ( const ValueMap & in )

virtual

Convenient shortcut to construct and return the model value.

◆ value_and_dvalue() [1/2]

void value_and_dvalue ( )

virtual

Evalute the model and compute its derivative.

◆ value_and_dvalue() [2/2]

std::tuple< ValueMap, DerivMap > value_and_dvalue ( const ValueMap & in )

virtual

Convenient shortcut to construct and return the model value and its derivative.

◆ value_and_dvalue_and_d2value() [1/2]

void value_and_dvalue_and_d2value ( )

virtual

Evalute the model and compute its first and second derivatives.

◆ value_and_dvalue_and_d2value() [2/2]

std::tuple< ValueMap, DerivMap, SecDerivMap > value_and_dvalue_and_d2value ( const ValueMap & in )

virtual

Convenient shortcut to construct and return the model's value, first and second derivative.

◆ zero_input()

void zero_input ( )

overridevirtual

Zero variable values

Reimplemented from VariableStore.

◆ zero_output()

void zero_output ( )

overridevirtual

Reimplemented from VariableStore.

Friends And Related Symbol Documentation

◆ ComposedModel

friend class ComposedModel

friend

ComposedModel's set_value need to call submodel's set_value.

◆ ParameterStore

friend class ParameterStore

friend

Declaration of nonlinear parameters may require manipulation of input.

Member Data Documentation

◆ _registered_models

std::vector<Model *> _registered_models

protected

Models this model may use during its evaluation.

Detailed Description

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Friends

Constructor & Destructor Documentation

◆ Model()

Member Function Documentation

◆ assemble()

◆ clear_input()

◆ clear_output()

◆ consumed_items()

◆ d2value() [1/2]

◆ d2value() [2/2]

◆ diagnose()

◆ diagnose_nl_sys()

◆ dvalue() [1/2]

◆ dvalue() [2/2]

◆ dvalue_and_d2value() [1/2]

◆ dvalue_and_d2value() [2/2]

◆ expected_options()

◆ is_nonlinear_system()

◆ link_input_variables() [1/2]

◆ link_input_variables() [2/2]

◆ link_output_variables() [1/2]

◆ link_output_variables() [2/2]

◆ provided_items()

◆ register_model()

◆ registered_model()

◆ registered_models()

◆ request_AD() [1/3]

◆ request_AD() [2/3]

◆ request_AD() [3/3]

◆ set_guess()

◆ set_value()

◆ setup()

◆ to()

◆ value() [1/2]

◆ value() [2/2]

◆ value_and_dvalue() [1/2]

◆ value_and_dvalue() [2/2]

◆ value_and_dvalue_and_d2value() [1/2]

◆ value_and_dvalue_and_d2value() [2/2]

◆ zero_input()

◆ zero_output()

Friends And Related Symbol Documentation

◆ ComposedModel

◆ ParameterStore

Member Data Documentation

◆ _registered_models