nuroko.module

Class AComponent

java.lang.Object

nuroko.module.AComponent

All Implemented Interfaces:

Cloneable, IComponent, IGradientTrainable, IInput, IInputOutput, IInputState, IModule, IOutput, IOutputState, IParameterised, IThinker, ITrainable

Direct Known Subclasses:

ACompoundComponent, ALayerStack, Dropout, Normaliser, Operator

public abstract class AComponent
extends Object
implements IComponent

Constructor Summary

Constructors

Constructor and Description
AComponent()

Method Summary

Methods

Modifier and Type	Method and Description
void	applyConstraints()
abstract AComponent	clone() Creates a clone of a module, including a deep copy of any mutable state.
mikera.vectorz.AVector	generate(mikera.vectorz.AVector output)
void	generate(mikera.vectorz.AVector input, mikera.vectorz.AVector output)
IComponent	getComponent(int i)
int	getInputLength()
IInputState	getInputState()
List<IModule>	getModules() Returns a list of sub-components of this module
int	getOutputLength()
int	getParameterLength() Returns the length of the parameter vector for this model
boolean	isStochastic()
void	setInput(mikera.vectorz.AVector inputValues)
void	setOutput(mikera.vectorz.AVector outputValues)
mikera.vectorz.AVector	think(mikera.vectorz.AVector input)
void	think(mikera.vectorz.AVector input, mikera.vectorz.AVector output)
void	thinkInternalTraining() Thinks within the scope of the component.
IComponent	topComponent()
void	train(mikera.vectorz.AVector input, mikera.vectorz.AVector target)
void	train(mikera.vectorz.AVector input, mikera.vectorz.AVector target, LossFunction loss, double factor)
void	trainGradient(mikera.vectorz.AVector gradient, double factor) Trains with a output gradient, incrementing inputGradient and accumulated gradient for parameters.
abstract void	trainGradientInternal(double factor)

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface nuroko.core.IComponent

getComponents, thinkInternal

Methods inherited from interface nuroko.core.IParameterised

getGradient, getParameters

Methods inherited from interface nuroko.core.IInputState

getInput, getInputGradient

Methods inherited from interface nuroko.core.IOutputState

getOutput, getOutputGradient

Constructor Detail

AComponent

public AComponent()

Method Detail

topComponent

public IComponent topComponent()

think

public void think(mikera.vectorz.AVector input,
         mikera.vectorz.AVector output)

Specified by:

think in interface IThinker

thinkInternalTraining

public void thinkInternalTraining()

Description copied from interface: IComponent

Thinks within the scope of the component. Update's component's output. May be different from regular thinking.

Specified by:

thinkInternalTraining in interface IComponent

Specified by:

thinkInternalTraining in interface ITrainable

think

public mikera.vectorz.AVector think(mikera.vectorz.AVector input)

Specified by:

think in interface IThinker

generate

public mikera.vectorz.AVector generate(mikera.vectorz.AVector output)

generate

public void generate(mikera.vectorz.AVector input,
            mikera.vectorz.AVector output)

train

public void train(mikera.vectorz.AVector input,
         mikera.vectorz.AVector target)

Specified by:

train in interface ITrainable

train

public void train(mikera.vectorz.AVector input,
         mikera.vectorz.AVector target,
         LossFunction loss,
         double factor)

Specified by:

train in interface ITrainable

trainGradient

public void trainGradient(mikera.vectorz.AVector gradient,
                 double factor)

Description copied from interface: IGradientTrainable

Trains with a output gradient, incrementing inputGradient and accumulated gradient for parameters.

Specified by:

trainGradient in interface IGradientTrainable

factor - TODO

trainGradientInternal

public abstract void trainGradientInternal(double factor)

Specified by:

trainGradientInternal in interface IComponent

setInput

public void setInput(mikera.vectorz.AVector inputValues)

Specified by:

setInput in interface IInputState

setOutput

public void setOutput(mikera.vectorz.AVector outputValues)

Specified by:

setOutput in interface IOutputState

getParameterLength

public int getParameterLength()

Description copied from interface: IParameterised

Returns the length of the parameter vector for this model

Specified by:

getParameterLength in interface IParameterised

Returns:

getComponent

public IComponent getComponent(int i)

getModules

public List<IModule> getModules()

Description copied from interface: IModule

Returns a list of sub-components of this module

Specified by:

getModules in interface IModule

Returns:

getInputState

public IInputState getInputState()

Specified by:

getInputState in interface IComponent

getInputLength

public int getInputLength()

Specified by:

getInputLength in interface IInput

getOutputLength

public int getOutputLength()

Specified by:

getOutputLength in interface IOutput

isStochastic

public boolean isStochastic()

Specified by:

isStochastic in interface IComponent

applyConstraints

public void applyConstraints()

Specified by:

applyConstraints in interface IComponent

clone

public abstract AComponent clone()

Description copied from interface: IModule

Creates a clone of a module, including a deep copy of any mutable state.

Specified by:

clone in interface IComponent

Specified by:

clone in interface IModule

Specified by:

clone in interface IParameterised

Specified by:

clone in interface IThinker

Specified by:

clone in interface ITrainable

Overrides:

clone in class Object

Returns: