BatchNormTrainingBase

Functions

cpu

open override fun cpu(): T

equals

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

extractTangent

getSingleInput

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

gpu

open override fun gpu(): T

hashCode

open override fun hashCode(): Int

invoke

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

abstract operator fun invoke(input: DTensor): DTensor

load

open override fun load(from: ByteBuffer): T

store

open override fun store(into: ByteBuffer): ByteBuffer

open fun to(device: Device): OnDevice

trainingStep

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

withTrainables

abstract fun withTrainables(trainables: List<Trainable<*>>): T

wrap

open override fun wrap(wrapper: Wrapper): T

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

inferenceMode

Freeze the batch norm transform that was used during training, returning an affine transform to be used for inference.

stats

The computed running mean and variance.

trainables

BatchNormTraining

BatchNormTrainingV1