AvgPool2D

class AvgPool2D(poolSize: IntArray, strides: IntArray, padding: ConvPadding, name: String) : Layer

Average pooling layer for 2D inputs (e.g. images).

NOTE: Works with tensors which must have rank 4 (batch, height, width, channels).

Constructors

AvgPool2D

fun AvgPool2D(poolSize: IntArray = intArrayOf(1, 2, 2, 1), strides: IntArray = intArrayOf(1, 2, 2, 1), padding: ConvPadding = ConvPadding.VALID, name: String = "")

Creates AvgPool2D object.

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.

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

The padding method, either 'valid' or 'same' or 'full'.

paramCount

open override val paramCount: Int

Returns amount of neurons.

parentModel

var parentModel: TrainableModel? = null

Model where this layer is used.

poolSize

val poolSize: IntArray

The size of the sliding window for each dimension of input tensor (pool batch, pool height, pool width, pool channels). Usually, pool batch and pool channels are equal to 1.

strides

val strides: IntArray

Strides of the pooling operation for each dimension of input tensor.

weights

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

Layer's weights.