Class Trainer2D

Namespace

NeuralNetworks.Trainers

Assembly

NeuralNetworks.dll

public class Trainer2D : Trainer<float[,], float[,]>

Inheritance

object

Trainer<float[,], float[,]>

Trainer2D

Inherited Members

Trainer<float[,], float[,]>.Memo

Trainer<float[,], float[,]>.GenerateBatches(float[,], float[,], int)

Trainer<float[,], float[,]>.PermuteData(float[,], float[,], Random)

Trainer<float[,], float[,]>.GetRows(float[,])

Trainer<float[,], float[,]>.Fit(DataSource<float[,], float[,]>, EvalFunction<float[,], float[,]>, int, int, int, int, bool, bool, bool)

Trainer<float[,], float[,]>.Describe(int)

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

Trainer2D(Model<float[,], float[,]>, Optimizer, SeededRandom?, ILogger<Trainer2D>?, bool)

public Trainer2D(Model<float[,], float[,]> model, Optimizer optimizer, SeededRandom? random, ILogger<Trainer2D>? logger = null, bool operationBackendTimingEnabled = false)

Parameters

model Model<float[,], float[,]>

optimizer Optimizer

random SeededRandom

logger ILogger<Trainer2D>

operationBackendTimingEnabled bool

Methods

GenerateBatches(float[,], float[,], int)

Generates batches of input and output matrices.

protected override IEnumerable<(float[,] xBatch, float[,] yBatch)> GenerateBatches(float[,] x, float[,] y, int batchSize)

Parameters

x float[,]

The input matrix.

y float[,]

The output matrix.

batchSize int

The batch size.

Returns

IEnumerable<(float[,] xBatch, float[,] yBatch)>

An enumerable of batches.

GetRows(float[,])

protected override float GetRows(float[,] x)

Parameters

x float[,]

Returns

float

PermuteData(float[,], float[,], Random)

protected override void PermuteData(float[,] x, float[,] y, Random random)

Parameters

x float[,]

y float[,]

random Random