Cropping1D

class Cropping1D(cropping: IntArray, name: String) : AbstractCropping

Cropping layer for 1D data (e.g. audio, time-series)

Crops input along the second dimension (i.e. temporal dimension).

Input shape: 3D tensor with shape (batch_size, steps, features).

Output shape: 3D tensor with shape (batch_size, cropped_steps, features).

Constructors

Cropping1D

fun Cropping1D(cropping: IntArray, 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

cropping

val cropping: IntArray

An integer array of size two ([begin_crop, end_crop]) indicating the number of elements to remove from the beginning and end of the cropping axis.

croppingInternal

val croppingInternal: Array<IntArray>

Cropping size values; currently, they are not used in the implementation of this abstract class and each subclassed layer uses its own copy of the cropping size values.

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.

paramCount

open override val paramCount: Int

Returns amount of neurons.

parentModel

var parentModel: TrainableModel? = null

Model where this layer is used.

weights

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

Layer's weights.