VariableStore Class Reference

#include <VariableStore.h>

Inheritance diagram for VariableStore:

Public Types
using	VariableStorage = std::map<VariableName, std::unique_ptr<VariableBase>>
using	DerivSparsity = std::vector<std::pair<VariableBase *, const VariableBase *>>
using	SecDerivSparsity

Public Member Functions
	VariableStore (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)
const TensorOptions &	variable_options () const
	Current tensor options for variables.
virtual void	zero_undefined_input ()
	Fill undefined input variables with zeros.
LabeledAxis &	input_axis ()
const LabeledAxis &	input_axis () const
LabeledAxis &	output_axis ()
const LabeledAxis &	output_axis () const
VariableStorage &	input_variables ()
const VariableStorage &	input_variables () const
VariableStorage &	output_variables ()
const VariableStorage &	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
virtual void	clear_input ()
virtual void	clear_output ()
virtual void	clear_derivatives ()
void	cache_derivative_sparsity ()
void	cache_second_derivative_sparsity ()
	Cache sparsity of second derivatives.
const std::optional< DerivSparsity > &	derivative_sparsity () const
	Derivative sparsity.
const std::optional< SecDerivSparsity > &	second_derivative_sparsity () const
	Second derivative sparsity.
void	assign_input (const ValueMap &vals, bool assembly=false)
void	assign_output (const ValueMap &vals, bool assembly=false)
void	assign_output_derivatives (const DerivMap &derivs, bool assembly=false)
ValueMap	collect_input (bool assembly=false) const
ValueMap	collect_output (bool assembly=false) const
DerivMap	collect_output_derivatives (bool assembly=false) const
SecDerivMap	collect_output_second_derivatives (bool assembly=false) const
void	set_input_intmd_sizes (const VariableName &, TensorShapeRef)
	Tag intermediate shapes for variables.
void	set_output_intmd_sizes (const VariableName &, TensorShapeRef)

Protected Member Functions
virtual void	send_variables_to (const TensorOptions &options)
	Send padding variables to options.
template<typename T >
const Variable< T > &	declare_input_variable (const char *name, TensorShapeRef dep_intmd_dims={}, bool allow_duplicate=false)
	Declare an input variable.
template<typename T >
const Variable< T > &	declare_input_variable (const VariableName &name, TensorShapeRef dep_intmd_dims={}, bool allow_duplicate=false)
	Declare an input variable.
template<typename T >
Variable< T > &	declare_output_variable (const char *name, TensorShapeRef dep_intmd_dims={})
	Declare an output variable.
template<typename T >
Variable< T > &	declare_output_variable (const VariableName &name, TensorShapeRef dep_intmd_dims={})
	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.
void	assign_input_stack (jit::Stack &stack)
	Assign stack to input variables.
void	assign_output_stack (jit::Stack &stack, bool out, bool dout, bool d2out)
	Assign stack to output variables and derivatives.
jit::Stack	collect_input_stack () const
	Collect stack from input variables.
jit::Stack	collect_output_stack (bool out, bool dout, bool d2out) const
	Collect stack from output variables and derivatives.

Friends
template<typename T >
const T &	resolve_tensor_name (const TensorName< T > &tn, Model *caller, const std::string &pname)

Member Typedef Documentation

DerivSparsity

using DerivSparsity = std::vector<std::pair<VariableBase *, const VariableBase *>>

SecDerivSparsity

using SecDerivSparsity

Initial value:

 
      std::vector<std::tuple<VariableBase *, const VariableBase *, const VariableBase *>>

VariableStorage

using VariableStorage = std::map<VariableName, std::unique_ptr<VariableBase>>

Constructor & Destructor Documentation

VariableStore() [1/3]

VariableStore

(

Model *

object

)

VariableStore() [2/3]

VariableStore ( const VariableStore & )

delete

VariableStore() [3/3]

VariableStore ( VariableStore && )

delete

~VariableStore()

virtual ~VariableStore ( )

virtualdefault

Member Function Documentation

assign_input()

void assign_input	(	const ValueMap &	vals,
		bool	assembly = false )

Assign input variable values assembly indicates if vals are in assembly format

assign_input_stack()

void assign_input_stack ( jit::Stack & stack )

protected

Assign stack to input variables.

assign_output()

void assign_output	(	const ValueMap &	vals,
		bool	assembly = false )

Assign output variable values assembly indicates if vals are in assembly format

assign_output_derivatives()

void assign_output_derivatives	(	const DerivMap &	derivs,
		bool	assembly = false )

Assign variable derivatives assembly indicates if derivs are in assembly format

assign_output_stack()

void assign_output_stack ( jit::Stack & stack, bool out, bool dout, bool d2out )

protected

Assign stack to output variables and derivatives.

cache_derivative_sparsity()

void cache_derivative_sparsity

(

)

Cache sparsity of first derivatives

cache_second_derivative_sparsity()

void cache_second_derivative_sparsity

(

)

Cache sparsity of second derivatives.

clear_derivatives()

void clear_derivatives ( )

virtual

clear_input()

void clear_input ( )

virtual

Release allocated tensor

Reimplemented in Model.

clear_output()

void clear_output ( )

virtual

Reimplemented in Model.

clone_input_variable()

const VariableBase * clone_input_variable ( const VariableBase & var, const VariableName & new_name = {} )

protected

Clone a variable and put it on the input axis.

clone_output_variable()

VariableBase * clone_output_variable ( const VariableBase & var, const VariableName & new_name = {} )

protected

Clone a variable and put it on the output axis.

collect_input()

ValueMap collect_input

(

bool

assembly = false

)

const

Collect input variable values assembly indicates if the returned map should be in assembly format

collect_input_stack()

jit::Stack collect_input_stack ( ) const

protected

Collect stack from input variables.

collect_output()

ValueMap collect_output

(

bool

assembly = false

)

const

Collect output variable values assembly indicates if the returned map should be in assembly format

collect_output_derivatives()

DerivMap collect_output_derivatives

(

bool

assembly = false

)

const

Collect variable derivatives assembly indicates if the returned map should be in assembly format

collect_output_second_derivatives()

SecDerivMap collect_output_second_derivatives

(

bool

assembly = false

)

const

Collect variable second derivatives assembly indicates if the returned map should be in assembly format

collect_output_stack()

jit::Stack collect_output_stack ( bool out, bool dout, bool d2out ) const

protected

Collect stack from output variables and derivatives.

declare_axis()

LabeledAxis & declare_axis

(

const std::string &

name

)

declare_input_variable() [1/2]

template<typename T >

const Variable< T > & declare_input_variable ( const char * name, TensorShapeRef dep_intmd_dims = {}, bool allow_duplicate = false )

protected

Declare an input variable.

declare_input_variable() [2/2]

template<typename T >

const Variable< T > & declare_input_variable ( const VariableName & name, TensorShapeRef dep_intmd_dims = {}, bool allow_duplicate = false )

protected

Declare an input variable.

declare_output_variable() [1/2]

template<typename T >

Variable< T > & declare_output_variable ( const char * name, TensorShapeRef dep_intmd_dims = {} )

protected

Declare an output variable.

declare_output_variable() [2/2]

template<typename T >

Variable< T > & declare_output_variable ( const VariableName & name, TensorShapeRef dep_intmd_dims = {} )

protected

Declare an output variable.

derivative_sparsity()

const std::optional< VariableStore::DerivSparsity > & derivative_sparsity

(

)

const

Derivative sparsity.

input_axis() [1/2]

LabeledAxis & input_axis

(

)

Input axis describing the assembly layout of input variables

input_axis() [2/2]

const LabeledAxis & input_axis

(

)

const

input_variable() [1/2]

VariableBase & input_variable

(

const VariableName &

name

)

Lookup a variable by name

input_variable() [2/2]

const VariableBase & input_variable

(

const VariableName &

name

)

const

input_variables() [1/2]

VariableStorage & input_variables ( )

inline

Variables

input_variables() [2/2]

const VariableStorage & input_variables ( ) const

inline

operator=() [1/2]

VariableStore & operator= ( const VariableStore & )

delete

operator=() [2/2]

VariableStore & operator= ( VariableStore && )

delete

output_axis() [1/2]

LabeledAxis & output_axis

(

)

Output axis describing the assembly layout of output variables

output_axis() [2/2]

const LabeledAxis & output_axis

(

)

const

output_variable() [1/2]

VariableBase & output_variable

(

const VariableName &

name

)

output_variable() [2/2]

const VariableBase & output_variable

(

const VariableName &

name

)

const

output_variables() [1/2]

VariableStorage & output_variables ( )

inline

output_variables() [2/2]

const VariableStorage & output_variables ( ) const

inline

second_derivative_sparsity()

const std::optional< VariableStore::SecDerivSparsity > & second_derivative_sparsity

(

)

const

Second derivative sparsity.

send_variables_to()

void send_variables_to ( const TensorOptions & options )

protectedvirtual

Send padding variables to options.

Parameters

options

The target options

set_input_intmd_sizes()

void set_input_intmd_sizes	(	const VariableName &	name,
		TensorShapeRef	shape )

Tag intermediate shapes for variables.

This is needed for two purposes:

1. By default we initialize undefined input variables to zero before evaluating the model. If a variable is tagged with an non-empty intermediate shape, the zero tensor will be created with that shape.
2. When using input/output axis for assembly, we need to know the intermediate sizes of each variable to correctly convert between variable format and assembly format. Variables are added to the LabeledAxis assuming zero intermediate dimension. If the actual intermediate shape is different, we need to use this method to inform the LabeledAxis about the correct shapes.

Note

This manual tagging is only necessary for the external-facing host models. We have the appropriate caching mechanism for sub-models (e.g., inside a ComposedModel) when they are being evaluated. In other words, this manual tagging is only necessary if variable intermediate shapes are needed before any model evaluation.

Warning

We spend no effort on verifying the correctness of the tagged shapes. It is the user's responsibility to ensure the correctness of the tagged shapes.

set_output_intmd_sizes()

void set_output_intmd_sizes	(	const VariableName &	name,
		TensorShapeRef	shape )

variable_options()

const TensorOptions & variable_options ( ) const

inline

Current tensor options for variables.

zero_undefined_input()

void zero_undefined_input ( )

virtual

Fill undefined input variables with zeros.

Reimplemented in Model.

Friends And Related Symbol Documentation

resolve_tensor_name

template<typename T >

const T & resolve_tensor_name ( const TensorName< T > & tn, Model * caller, const std::string & pname )

friend