MaxPool1D

class MaxPool1D(poolSize: LongArray, strides: LongArray, padding: ConvPadding, name: String) : Layer

Max pooling operation for 1D temporal data (e.g. audio, timeseries).

Downsamples the input by taking maximum value over a temporal window of size poolSize.

Constructors

MaxPool1D

fun MaxPool1D(poolSize: LongArray = longArrayOf(1, 2, 1), strides: LongArray = longArrayOf(1, 2, 1), padding: ConvPadding = ConvPadding.VALID, name: String = "")

Functions

build

open override fun build(tf: Ops, kGraph: KGraph, inputShape: Shape)

Extend this function to define variables in layer.

buildFromInboundLayers

fun buildFromInboundLayers(tf: Ops, kGraph: KGraph)

Extend this function to define variables in layer.

computeOutputShape

open override fun computeOutputShape(inputShape: Shape): Shape

Computes output shape, based on inputShape and Layer type.

computeOutputShapeFromInboundLayers

open fun computeOutputShapeFromInboundLayers(): TensorShape

Computes output shape, based on input shapes of inbound layers.

forward

open override fun forward(tf: Ops, input: Operand<Float>, isTraining: Operand<Boolean>, numberOfLosses: Operand<Float>?): Operand<Float>

Builds main layer input transformation with tf. Depends on Layer type.

open fun forward(tf: Ops, input: List<Operand<Float>>, isTraining: Operand<Boolean>, numberOfLosses: Operand<Float>?): Operand<Float>

Builds main layer input transformation with tf. Depends on Layer type.

invoke

operator fun invoke(vararg layers: Layer): Layer

Important part of functional API. It takes layers as input and saves them to the inboundLayers of the given layer.

toString

open override fun toString(): String

Properties

hasActivation

open override val hasActivation: Boolean

Returns True, if layer has internal activation function.

inboundLayers

var inboundLayers: MutableList<Layer>

Returns inbound layers.

isTrainable

var isTrainable: Boolean = true

True, if layer's weights could be changed during training. If false, layer's weights are frozen and could be changed during the training.

name

var name: String

outboundLayers

var outboundLayers: MutableList<Layer>

Returns outbound layers.

outputShape

lateinit var outputShape: TensorShape

Output data tensor shape.

padding

val padding: ConvPadding

Padding strategy; can be either of ConvPadding.VALID which means no padding, or ConvPadding.SAME which means padding the input equally such that the output has the same dimension as the input.

paramCount

open override val paramCount: Int

Returns amount of neurons.

parentModel

var parentModel: TrainableModel? = null

Model where this layer is used.

poolSize

val poolSize: LongArray

Size of the temporal pooling window for each dimension of input.

strides

val strides: LongArray

The amount of shift for pooling window per each input dimension in each pooling step.

weights

open override var weights: Map<String, Array<*>>

Layer's weights.