This is a basic multilayer perceptron neural network capable of basic training and feed forward operations. More...

#include <MultilayerPerceptron.h>

Inherits MachineLearning::INeuralNetwork.

Public Member Functions
	AZ_RTTI (MultilayerPerceptron, "{E12EF761-41A5-48C3-BF55-7179B280D45F}", INeuralNetwork)

	MultilayerPerceptron (const MultilayerPerceptron &)

	MultilayerPerceptron (AZStd::size_t activationCount)

MultilayerPerceptron &	operator= (const MultilayerPerceptron &)

MultilayerPerceptron &	operator= (const ModelAsset &)

void	AddLayer (AZStd::size_t layerDimensionality, ActivationFunctions activationFunction=ActivationFunctions::ReLU)
	Adds a new layer to the model.

Layer *	GetLayer (AZStd::size_t layerIndex)
	Retrieves a specific layer from the model, this is not thread safe and should only be used during unit testing to validate model parameters.


AZStd::string	GetName () const override

AZStd::string	GetAssetFile (AssetTypes assetType) const override
	Returns the file where model parameters are stored.

AZStd::size_t	GetInputDimensionality () const override
	Returns the number of input neurons the model supports.

AZStd::size_t	GetOutputDimensionality () const override
	Returns the number of output neurons the model supports.

AZStd::size_t	GetLayerCount () const override
	Returns the total number of layers in the network.

AZ::MatrixMxN	GetLayerWeights (AZStd::size_t layerIndex) const override
	Returns the weight matrix for the requested layer.

AZ::VectorN	GetLayerBiases (AZStd::size_t layerIndex) const override
	Returns the weight matrix for the requested layer.

AZStd::size_t	GetParameterCount () const override
	Returns the total number of parameters in the neural network.

IInferenceContextPtr	CreateInferenceContext () override

ITrainingContextPtr	CreateTrainingContext () override

const AZ::VectorN *	Forward (IInferenceContextPtr context, const AZ::VectorN &activations) override
	Performs a basic feed-forward operation to compute the output from a set of activation values.

void	Reverse (ITrainingContextPtr context, LossFunctions lossFunction, const AZ::VectorN &activations, const AZ::VectorN &expected) override
	Accumulates the loss gradients given a loss function, an activation vector and a corresponding label vector.

void	GradientDescent (ITrainingContextPtr context, float learningRate) override
	Performs a gradient descent step and resets all gradient accumulators to zero.

bool	LoadModel () override
	Loads the current model parameters from the associated asset file.

bool	SaveModel () override
	Saves the current model parameters to the associated asset file.

Public Member Functions inherited from MachineLearning::INeuralNetwork
	AZ_RTTI (INeuralNetwork, "{64E5B5B1-4A7D-489D-9A29-D9510BB7E17A}")

	INeuralNetwork (INeuralNetwork &&)=default

	INeuralNetwork (const INeuralNetwork &)=default

INeuralNetwork &	operator= (INeuralNetwork &&)=default

INeuralNetwork &	operator= (const INeuralNetwork &)=default

void	add_ref ()

void	release ()

Static Public Member Functions
static void	Reflect (AZ::ReflectContext *context)

Friends
class	MultilayerPerceptronEditorComponent

Detailed Description

This is a basic multilayer perceptron neural network capable of basic training and feed forward operations.

Member Function Documentation

◆ CreateInferenceContext()

IInferenceContextPtr MachineLearning::MultilayerPerceptron::CreateInferenceContext ( )

overridevirtual

Reimplemented from MachineLearning::INeuralNetwork.

◆ CreateTrainingContext()

ITrainingContextPtr MachineLearning::MultilayerPerceptron::CreateTrainingContext ( )

overridevirtual

Reimplemented from MachineLearning::INeuralNetwork.

◆ Forward()

const AZ::VectorN * MachineLearning::MultilayerPerceptron::Forward	(	IInferenceContextPtr	context,
		const AZ::VectorN &	activations
	)

overridevirtual

Performs a basic feed-forward operation to compute the output from a set of activation values.

Reimplemented from MachineLearning::INeuralNetwork.

◆ GetAssetFile()

AZStd::string MachineLearning::MultilayerPerceptron::GetAssetFile ( AssetTypes assetType ) const

overridevirtual

Returns the file where model parameters are stored.

Reimplemented from MachineLearning::INeuralNetwork.

◆ GetInputDimensionality()

AZStd::size_t MachineLearning::MultilayerPerceptron::GetInputDimensionality ( ) const

overridevirtual

Returns the number of input neurons the model supports.

Reimplemented from MachineLearning::INeuralNetwork.

◆ GetLayerBiases()

AZ::VectorN MachineLearning::MultilayerPerceptron::GetLayerBiases ( AZStd::size_t layerIndex ) const

overridevirtual

Returns the weight matrix for the requested layer.

Reimplemented from MachineLearning::INeuralNetwork.

◆ GetLayerCount()

AZStd::size_t MachineLearning::MultilayerPerceptron::GetLayerCount ( ) const

overridevirtual

Returns the total number of layers in the network.

Reimplemented from MachineLearning::INeuralNetwork.

◆ GetLayerWeights()

AZ::MatrixMxN MachineLearning::MultilayerPerceptron::GetLayerWeights ( AZStd::size_t layerIndex ) const

overridevirtual

Returns the weight matrix for the requested layer.

Reimplemented from MachineLearning::INeuralNetwork.

◆ GetName()

AZStd::string MachineLearning::MultilayerPerceptron::GetName ( ) const

overridevirtual

INeuralNetwork interface

Reimplemented from MachineLearning::INeuralNetwork.

◆ GetOutputDimensionality()

AZStd::size_t MachineLearning::MultilayerPerceptron::GetOutputDimensionality ( ) const

overridevirtual

Returns the number of output neurons the model supports.

Reimplemented from MachineLearning::INeuralNetwork.

◆ GetParameterCount()

AZStd::size_t MachineLearning::MultilayerPerceptron::GetParameterCount ( ) const

overridevirtual

Returns the total number of parameters in the neural network.

Reimplemented from MachineLearning::INeuralNetwork.

◆ GradientDescent()

void MachineLearning::MultilayerPerceptron::GradientDescent	(	ITrainingContextPtr	context,
		float	learningRate
	)

overridevirtual

Performs a gradient descent step and resets all gradient accumulators to zero.

Reimplemented from MachineLearning::INeuralNetwork.

◆ LoadModel()

bool MachineLearning::MultilayerPerceptron::LoadModel ( )

overridevirtual

Loads the current model parameters from the associated asset file.

Reimplemented from MachineLearning::INeuralNetwork.

◆ Reflect()

static void MachineLearning::MultilayerPerceptron::Reflect ( AZ::ReflectContext * context )

static

AzCore Reflection.

Parameters

context reflection context

◆ Reverse()

void MachineLearning::MultilayerPerceptron::Reverse	(	ITrainingContextPtr	context,
		LossFunctions	lossFunction,
		const AZ::VectorN &	activations,
		const AZ::VectorN &	expected
	)

overridevirtual

Accumulates the loss gradients given a loss function, an activation vector and a corresponding label vector.

Reimplemented from MachineLearning::INeuralNetwork.

◆ SaveModel()

bool MachineLearning::MultilayerPerceptron::SaveModel ( )

overridevirtual

Saves the current model parameters to the associated asset file.

Reimplemented from MachineLearning::INeuralNetwork.

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

Gems/MachineLearning/Code/Source/Models/MultilayerPerceptron.h

Public Member Functions

Static Public Member Functions

Friends

Detailed Description

Member Function Documentation

◆ CreateInferenceContext()

◆ CreateTrainingContext()

◆ Forward()

◆ GetAssetFile()

◆ GetInputDimensionality()

◆ GetLayerBiases()

◆ GetLayerCount()

◆ GetLayerWeights()

◆ GetName()

◆ GetOutputDimensionality()

◆ GetParameterCount()

◆ GradientDescent()

◆ LoadModel()

◆ Reflect()

◆ Reverse()

◆ SaveModel()