AffineTransform

class AffineTransform(m: TrainableTensor, b: TrainableTensor) : TrainableLayerSingleInput<AffineTransform>

An affine transform. Multiplies by one tensor and then adds another. Like a Dense layer, except that where a dense layer performs a matmul, this one performs an element-wise multiplication.

Constructors

AffineTransform

fun AffineTransform(m: TrainableTensor, b: TrainableTensor)

Functions

cpu

open override fun cpu(): AffineTransform

equals

open operator override fun equals(other: Any?): Boolean

extractTangent

open override fun extractTangent(output: DTensor, extractor: (DTensor, DTensor) -> DTensor): TrainableComponent.Companion.Tangent

getSingleInput

open fun getSingleInput(inputs: Array<out DTensor>): DTensor

Helper to check that the layer was called with a single input. Returns that input if successful, else errors.

gpu

open override fun gpu(): AffineTransform

hashCode

open override fun hashCode(): Int

invoke

open operator override fun invoke(input: DTensor): DTensor

abstract operator fun invoke(vararg inputs: DTensor): DTensor

load

open override fun load(from: ByteBuffer): AffineTransform

store

open override fun store(into: ByteBuffer): ByteBuffer

open fun to(device: Device): OnDevice

trainingStep

open override fun trainingStep(optim: Optimizer<*>, tangent: Trainable.Tangent): AffineTransform

withTrainables

open override fun withTrainables(trainables: List<Trainable<*>>): AffineTransform

wrap

open override fun wrap(wrapper: Wrapper): AffineTransform

The wrap function should return the same static type it is declared on.

Properties

val b: TrainableTensor

val m: TrainableTensor

trainables

open override val trainables: List<Trainable<*>>