ParameterStore Class Reference

Interface for object which can store parameters. More...

Detailed Description

Interface for object which can store parameters.

#include <ParameterStore.h>

Inheritance diagram for ParameterStore:

Public Member Functions
	ParameterStore (const OptionSet &options, NEML2Object *object)
const Storage< std::string, TensorValueBase > &	named_parameters () const
Storage< std::string, TensorValueBase > &	named_parameters ()
template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<T>, T>>>
T &	get_parameter (const std::string &name)
	}@
bool	has_nl_param () const
	Whether this parameter store has any nonlinear parameter.
const std::map< std::string, const VariableBase * > &	nl_params () const
	Get all nonlinear parameters.
const VariableBase *	nl_param (const std::string &) const
	Query the existence of a nonlinear parameter.
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<BatchTensorBase<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<BatchTensorBase<T>, T>>>
const T &	declare_parameter (const std::string &name, const std::string &input_option_name)
	Declare a parameter.

Constructor & Destructor Documentation

ParameterStore()

ParameterStore	(	const OptionSet &	options,
		NEML2Object *	object )

Member Function Documentation

declare_parameter() [1/2]

template<typename T , typename >

const T & declare_parameter ( const std::string & name, const std::string & input_option_name )

protected

Declare a parameter.

Note that all parameters are stored in the host (the object exposed to users). An object may be used multiple times in the host, and the same parameter may be declared multiple times. That is allowed, but only the first call to declare_parameter constructs the parameter value, and subsequent calls only returns a reference to the existing parameter.

Template Parameters

T	Parameter type. See Statically shaped tensors for supported types.

Parameters

name	Name of the model parameter.
input_option_name	Name of the input option that defines the value of the model parameter.

Returns

T The value of the registered model parameter.

declare_parameter() [2/2]

template<typename T , typename >

const T & declare_parameter ( const std::string & name, const T & rawval )

protected

Declare a parameter.

Note that all parameters are stored in the host (the object exposed to users). An object may be used multiple times in the host, and the same parameter may be declared multiple times. That is allowed, but only the first call to declare_parameter constructs the parameter value, and subsequent calls only returns a reference to the existing parameter.

Template Parameters

T	Buffer type. See Statically shaped tensors for supported types.

Parameters

name	Buffer name
rawval	Buffer value

Returns

Reference to buffer

get_parameter()

template<typename T , typename >

T & get_parameter

(

const std::string &

name

)

}@

Get a writable reference of a parameter

has_nl_param()

bool has_nl_param ( ) const

inline

Whether this parameter store has any nonlinear parameter.

named_parameters() [1/2]

Storage< std::string, TensorValueBase > & named_parameters

(

)

named_parameters() [2/2]

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

inline

Returns

the buffer storage

nl_param()

const VariableBase * nl_param

(

const std::string &

name

)

const

Query the existence of a nonlinear parameter.

Returns

const VariableBase* Pointer to the VariableBase if the parameter associated with the given parameter name is nonlinear. Returns nullptr otherwise.

nl_params()

const std::map< std::string, const VariableBase * > & nl_params ( ) const

inline

Get all nonlinear parameters.

send_parameters_to()

void send_parameters_to ( const torch::TensorOptions & options )

protectedvirtual

Send parameters to options.

Parameters

options

The target options