Conv2dWithSamePadding

class Conv2dWithSamePadding(filterShape: Shape, horizontalStride: Int, verticalStride: Int, activation: Activation, random: Random) : Conv2d

Functions

cpu

open override fun cpu(): Conv2d

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(): Conv2d

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): Conv2d

store

open override fun store(into: ByteBuffer): ByteBuffer

open fun to(device: Device): OnDevice

trainingStep

withTrainables

open override fun withTrainables(trainables: List<Trainable<*>>): Conv2d

wrap

open override fun wrap(wrapper: Wrapper): Conv2d

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

activation

filterShape

horizontalStride

paddingStyle

trainables

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

verticalStride