Class AdamOptimizer

Namespace

NeuralNetworks.Optimizers

Assembly

NeuralNetworks.dll

Implements the Adam optimizer for neural network training. Adam combines momentum and adaptive learning rates for each parameter.

public class AdamOptimizer : Optimizer

Inheritance

object

Optimizer

AdamOptimizer

Inherited Members

Optimizer.LearningRate

Optimizer.UpdateLearningRate(int, int)

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

Constructors

AdamOptimizer(LearningRate, float, float, float)

public AdamOptimizer(LearningRate learningRate, float beta1 = 0.9, float beta2 = 0.999, float eps = 1E-08)

Parameters

learningRate LearningRate

beta1 float

beta2 float

eps float

Methods

ToString()

Returns a string that represents the current object.

public override string ToString()

Returns

string

A string that represents the current object.

Update(Layer?, float[,,,], float[,,,])

public override void Update(Layer? layer, float[,,,] param, float[,,,] paramGradient)

Parameters

layer Layer

param float[,,,]

paramGradient float[,,,]

Update(Layer?, float[,], float[,])

public override void Update(Layer? layer, float[,] param, float[,] paramGradient)

Parameters

layer Layer

param float[,]

paramGradient float[,]

Update(Layer?, float[], float[])

public override void Update(Layer? layer, float[] param, float[] paramGradient)

Parameters

layer Layer

param float[]

paramGradient float[]